Fine_tuning_BERT.ipynb

{
  "nbformat": 4,
  "nbformat_minor": 0,
  "metadata": {
    "colab": {
      "name": "Fine_tuning_BERT.ipynb",
      "provenance": [],
      "collapsed_sections": [],
      "include_colab_link": true
    },
    "kernelspec": {
      "name": "python3",
      "display_name": "Python 3"
    },
    "accelerator": "TPU"
  },
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "view-in-github",
        "colab_type": "text"
      },
      "source": [
        "<a href=\"https://colab.research.google.com/github/Inyrkz/Question-Answering-using-BERT/blob/master/Fine_tuning_BERT.ipynb\" target=\"_parent\"><img src=\"https://colab.research.google.com/assets/colab-badge.svg\" alt=\"Open In Colab\"/></a>"
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "MZvsjaZrsxcB",
        "colab_type": "code",
        "outputId": "533d1e24-4379-4f89-f500-d01a1124e477",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 170
        }
      },
      "source": [
        "#Installing wget\n",
        "pip install wget"
      ],
      "execution_count": 3,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Collecting wget\n",
            "  Downloading https://files.pythonhosted.org/packages/47/6a/62e288da7bcda82b935ff0c6cfe542970f04e29c756b0e147251b2fb251f/wget-3.2.zip\n",
            "Building wheels for collected packages: wget\n",
            "  Building wheel for wget (setup.py) ... \u001b[?25l\u001b[?25hdone\n",
            "  Created wheel for wget: filename=wget-3.2-cp36-none-any.whl size=9681 sha256=373b61e6d0111c5d33c5303f0f10f73634a8c88f6d8e80342ef9ce64deff8ae7\n",
            "  Stored in directory: /root/.cache/pip/wheels/40/15/30/7d8f7cea2902b4db79e3fea550d7d7b85ecb27ef992b618f3f\n",
            "Successfully built wget\n",
            "Installing collected packages: wget\n",
            "Successfully installed wget-3.2\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "4cavDDihQlwQ",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Let's import our libraries\n",
        "import zipfile\n",
        "import os\n",
        "import shutil\n",
        "import pandas as pd\n",
        "import numpy as np\n",
        "import wget"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "7oahVfi5vq-G",
        "colab_type": "code",
        "outputId": "ea6fd2f7-9a32-46dc-9203-9b1264fce4bb",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "#mounting google drive to colab\n",
        "from google.colab import drive\n",
        "drive.mount('/content/drive')\n",
        "print(os.listdir(\"/content/drive/My Drive/SQuAD JSON-v2.0\"))"
      ],
      "execution_count": 6,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "Drive already mounted at /content/drive; to attempt to forcibly remount, call drive.mount(\"/content/drive\", force_remount=True).\n",
            "['dev-v2.0.json', 'train-v2.0.json']\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "hs6aU6BFzxOp",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Downloading our uncased BERT large model\n",
        "URL = 'https://storage.googleapis.com/bert_models/2018_10_18/uncased_L-24_H-1024_A-16.zip'\n",
        "FILENAME = wget.download(URL)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "i7FSlAFPwXdN",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "REPO = 'model_repo'\n",
        "with zipfile.ZipFile(\"uncased_L-24_H-1024_A-16.zip\",\"r\") as zip_ref:\n",
        "    zip_ref.extractall(REPO)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "By0HkGbA3PuM",
        "colab_type": "code",
        "outputId": "401d521f-682f-4d7a-d8fd-d212c1643082",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        }
      },
      "source": [
        "#Listing the files in the model\n",
        "os.listdir('model_repo/uncased_L-24_H-1024_A-16')"
      ],
      "execution_count": 9,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['bert_model.ckpt.meta',\n",
              " 'vocab.txt',\n",
              " 'bert_config.json',\n",
              " 'bert_model.ckpt.data-00000-of-00001',\n",
              " 'bert_model.ckpt.index']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 9
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "e49XM2h84EZZ",
        "colab_type": "code",
        "outputId": "70d67378-a9f0-4d47-fc59-3bfce6f94dac",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 34
        }
      },
      "source": [
        "#Listing files in the model_repo\n",
        "os.listdir('model_repo')"
      ],
      "execution_count": 10,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['uncased_L-24_H-1024_A-16']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 10
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "n6_fFjx24M_i",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Downloading some python files from Google's BERT needed for training\n",
        "URL1 = 'https://raw.githubusercontent.com/google-research/bert/master/modeling.py'\n",
        "URL2 = 'https://raw.githubusercontent.com/google-research/bert/master/optimization.py'\n",
        "URL3 = 'https://raw.githubusercontent.com/google-research/bert/master/run_squad.py'\n",
        "URL4 = 'https://raw.githubusercontent.com/google-research/bert/master/tokenization.py'\n",
        "FILENAME1 = wget.download(URL1)\n",
        "FILENAME2 = wget.download(URL2)\n",
        "FILENAME3 = wget.download(URL3)\n",
        "FILENAME4 = wget.download(URL4)"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "HiowJhk55YDP",
        "colab_type": "code",
        "outputId": "c349d841-739a-406e-b626-2ee889b3f90b",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 51
        }
      },
      "source": [
        "#Creating an output directory for our output\n",
        "#Creating a bert pretrained directory\n",
        "#Available pretrained model checkpoints:\n",
        "#uncased_L-12_H-768_A-12: uncased BERT base model\n",
        "#uncased_L-24_H-1024_A-16: uncased BERT large model\n",
        "#cased_L-12_H-768_A-12: cased BERT large model\n",
        "BERT_MODEL = 'uncased_L-24_H-1024_A-16'\n",
        "BERT_PRETRAINED_DIR = f'{REPO}/uncased_L-24_H-1024_A-16'\n",
        "OUTPUT_DIR = f'{REPO}/outputs'\n",
        "print(f'***** Model output directory: {OUTPUT_DIR} *****')\n",
        "print(f'***** BERT pretrained directory: {BERT_PRETRAINED_DIR} *****')"
      ],
      "execution_count": 12,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "***** Model output directory: model_repo/outputs *****\n",
            "***** BERT pretrained directory: model_repo/uncased_L-24_H-1024_A-16 *****\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "83OtIMXX5wNU",
        "colab_type": "code",
        "outputId": "63455c6a-c42e-4502-f543-c99de2990096",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 221
        }
      },
      "source": [
        "#The wget command helps us to download the SQuAD 2.0 dataset from the internet\n",
        "URL5 = 'https://rajpurkar.github.io/SQuAD-explorer/dataset/train-v2.0.json'\n",
        "URL6 = 'https://rajpurkar.github.io/SQuAD-explorer/dataset/dev-v2.0.json'\n",
        "HN = 'https://worksheets.codalab.org/rest/bundles/0x6b567e1cf2e041ec80d7098f031c5c9e/contents/blob/'\n",
        "URL7 = HN\n",
        "FILENAME5 = wget.download(URL5)\n",
        "FILENAME6 = wget.download(URL6)\n",
        "FILENAME7 = wget.download(URL7)\n",
        "os.listdir()"
      ],
      "execution_count": 13,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['.config',\n",
              " 'evaluate-v2.0.py',\n",
              " 'run_squad.py',\n",
              " 'optimization.py',\n",
              " 'model_repo',\n",
              " 'drive',\n",
              " 'dev-v2.0.json',\n",
              " 'modeling.py',\n",
              " 'train-v2.0.json',\n",
              " 'tokenization.py',\n",
              " 'uncased_L-24_H-1024_A-16.zip',\n",
              " 'sample_data']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 13
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "_3Vvix8h6E_-",
        "colab_type": "code",
        "outputId": "38c4a3c0-4be6-4f2d-b388-fbd84954f08d",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 102
        }
      },
      "source": [
        "os.listdir('model_repo/uncased_L-24_H-1024_A-16')"
      ],
      "execution_count": 14,
      "outputs": [
        {
          "output_type": "execute_result",
          "data": {
            "text/plain": [
              "['bert_model.ckpt.meta',\n",
              " 'vocab.txt',\n",
              " 'bert_config.json',\n",
              " 'bert_model.ckpt.data-00000-of-00001',\n",
              " 'bert_model.ckpt.index']"
            ]
          },
          "metadata": {
            "tags": []
          },
          "execution_count": 14
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "ut6go3hJ6qYI",
        "colab_type": "code",
        "colab": {}
      },
      "source": [
        "#Creating a new directory\n",
        "os.mkdir('output')"
      ],
      "execution_count": 0,
      "outputs": []
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "oz7568Mo6_Lo",
        "colab_type": "code",
        "outputId": "07cdb1e2-f488-4f6b-9db0-853666383b30",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        }
      },
      "source": [
        "#Code to run the run_squad.py file with training set and test set of SQuAD 2.0\n",
        "!python3 run_squad.py \\\n",
        "--vocab_file = model_repo/uncased_L-24_H-1024_A-16/vocab.txt \\\n",
        "--bert_config_file = model_repo/uncased_L-24_H-1024_A-16/bert_config.json \\\n",
        "--init_checkpoint = model_repo/uncased_L-24_H-1024_A-16/bert_model.ckpt \\\n",
        "--do_train = True \\\n",
        "--train_file = train-v2.0.json \\\n",
        "--do_predict = True \\\n",
        "--predict_file = dev-v2.0.json \\\n",
        "--train_batch_size = 24 \\\n",
        "--learning_rate = 3e-5 \\\n",
        "--num_train_epochs = 2.0 \\\n",
        "--max_seq_length = 384 \\\n",
        "--doc_stride = 128 \\\n",
        "--version_2_with_negative = True \\\n",
        "--output_dir = /content/output\n",
        "#--use_tpu=True \\\n",
        "#--tpu_name=v2-128 \\"
      ],
      "execution_count": 0,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /content/optimization.py:87: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:1283: The name tf.app.run is deprecated. Please use tf.compat.v1.app.run instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:1127: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.\n",
            "\n",
            "W1012 15:05:00.397206 140273920317312 module_wrapper.py:139] From run_squad.py:1127: The name tf.logging.set_verbosity is deprecated. Please use tf.compat.v1.logging.set_verbosity instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:1127: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.\n",
            "\n",
            "W1012 15:05:00.397429 140273920317312 module_wrapper.py:139] From run_squad.py:1127: The name tf.logging.INFO is deprecated. Please use tf.compat.v1.logging.INFO instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/modeling.py:93: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "W1012 15:05:00.397602 140273920317312 module_wrapper.py:139] From /content/modeling.py:93: The name tf.gfile.GFile is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:1133: The name tf.gfile.MakeDirs is deprecated. Please use tf.io.gfile.makedirs instead.\n",
            "\n",
            "W1012 15:05:00.398646 140273920317312 module_wrapper.py:139] From run_squad.py:1133: The name tf.gfile.MakeDirs is deprecated. Please use tf.io.gfile.makedirs instead.\n",
            "\n",
            "WARNING:tensorflow:\n",
            "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
            "For more information, please see:\n",
            "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
            "  * https://github.com/tensorflow/addons\n",
            "  * https://github.com/tensorflow/io (for I/O related ops)\n",
            "If you depend on functionality not listed there, please file an issue.\n",
            "\n",
            "W1012 15:05:00.487938 140273920317312 lazy_loader.py:50] \n",
            "The TensorFlow contrib module will not be included in TensorFlow 2.0.\n",
            "For more information, please see:\n",
            "  * https://github.com/tensorflow/community/blob/master/rfcs/20180907-contrib-sunset.md\n",
            "  * https://github.com/tensorflow/addons\n",
            "  * https://github.com/tensorflow/io (for I/O related ops)\n",
            "If you depend on functionality not listed there, please file an issue.\n",
            "\n",
            "I1012 15:05:01.594735 140273920317312 utils.py:141] NumExpr defaulting to 2 threads.\n",
            "WARNING:tensorflow:From run_squad.py:229: The name tf.gfile.Open is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "W1012 15:05:02.770600 140273920317312 module_wrapper.py:139] From run_squad.py:229: The name tf.gfile.Open is deprecated. Please use tf.io.gfile.GFile instead.\n",
            "\n",
            "WARNING:tensorflow:Estimator's model_fn (<function model_fn_builder.<locals>.model_fn at 0x7f93dac61950>) includes params argument, but params are not passed to Estimator.\n",
            "W1012 15:05:11.790107 140273920317312 estimator.py:1994] Estimator's model_fn (<function model_fn_builder.<locals>.model_fn at 0x7f93dac61950>) includes params argument, but params are not passed to Estimator.\n",
            "INFO:tensorflow:Using config: {'_model_dir': '/content/output', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': 1000, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true\n",
            "graph_options {\n",
            "  rewrite_options {\n",
            "    meta_optimizer_iterations: ONE\n",
            "  }\n",
            "}\n",
            ", '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': None, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f93daca3ac8>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1, '_tpu_config': TPUConfig(iterations_per_loop=1000, num_shards=8, num_cores_per_replica=None, per_host_input_for_training=3, tpu_job_name=None, initial_infeed_sleep_secs=None, input_partition_dims=None, eval_training_input_configuration=2, experimental_host_call_every_n_steps=1), '_cluster': None}\n",
            "I1012 15:05:11.791605 140273920317312 estimator.py:212] Using config: {'_model_dir': '/content/output', '_tf_random_seed': None, '_save_summary_steps': 100, '_save_checkpoints_steps': 1000, '_save_checkpoints_secs': None, '_session_config': allow_soft_placement: true\n",
            "graph_options {\n",
            "  rewrite_options {\n",
            "    meta_optimizer_iterations: ONE\n",
            "  }\n",
            "}\n",
            ", '_keep_checkpoint_max': 5, '_keep_checkpoint_every_n_hours': 10000, '_log_step_count_steps': None, '_train_distribute': None, '_device_fn': None, '_protocol': None, '_eval_distribute': None, '_experimental_distribute': None, '_experimental_max_worker_delay_secs': None, '_session_creation_timeout_secs': 7200, '_service': None, '_cluster_spec': <tensorflow.python.training.server_lib.ClusterSpec object at 0x7f93daca3ac8>, '_task_type': 'worker', '_task_id': 0, '_global_id_in_cluster': 0, '_master': '', '_evaluation_master': '', '_is_chief': True, '_num_ps_replicas': 0, '_num_worker_replicas': 1, '_tpu_config': TPUConfig(iterations_per_loop=1000, num_shards=8, num_cores_per_replica=None, per_host_input_for_training=3, tpu_job_name=None, initial_infeed_sleep_secs=None, input_partition_dims=None, eval_training_input_configuration=2, experimental_host_call_every_n_steps=1), '_cluster': None}\n",
            "INFO:tensorflow:_TPUContext: eval_on_tpu True\n",
            "I1012 15:05:11.791960 140273920317312 tpu_context.py:220] _TPUContext: eval_on_tpu True\n",
            "WARNING:tensorflow:eval_on_tpu ignored because use_tpu is False.\n",
            "W1012 15:05:11.792494 140273920317312 tpu_context.py:222] eval_on_tpu ignored because use_tpu is False.\n",
            "WARNING:tensorflow:From run_squad.py:1065: The name tf.python_io.TFRecordWriter is deprecated. Please use tf.io.TFRecordWriter instead.\n",
            "\n",
            "W1012 15:05:11.792727 140273920317312 module_wrapper.py:139] From run_squad.py:1065: The name tf.python_io.TFRecordWriter is deprecated. Please use tf.io.TFRecordWriter instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:431: The name tf.logging.info is deprecated. Please use tf.compat.v1.logging.info instead.\n",
            "\n",
            "W1012 15:05:11.796375 140273920317312 module_wrapper.py:139] From run_squad.py:431: The name tf.logging.info is deprecated. Please use tf.compat.v1.logging.info instead.\n",
            "\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.796567 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000000\n",
            "I1012 15:05:11.796675 140273920317312 run_squad.py:432] unique_id: 1000000000\n",
            "INFO:tensorflow:example_index: 0\n",
            "I1012 15:05:11.796757 140273920317312 run_squad.py:433] example_index: 0\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.796829 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what is the name of the act that was a success in creating boundaries for the crown and the e ##ic for being subjective ? [SEP] pitt ' s act was deemed a failure because it quickly became apparent that the boundaries between government control and the company ' s powers were ne ##bu ##lous and highly subjective . the government felt obliged to respond to humanitarian calls for better treatment of local peoples in british - occupied territories . edmund burke , a former east india company shareholder and diplomat , was moved to address the situation and introduced a new regulating bill in 1783 . the bill was defeated amid lobbying by company loyalists and accusations of ne ##pot ##ism in the bill ' s recommendations for the appointment of councillors . [SEP]\n",
            "I1012 15:05:11.796960 140273920317312 run_squad.py:436] tokens: [CLS] what is the name of the act that was a success in creating boundaries for the crown and the e ##ic for being subjective ? [SEP] pitt ' s act was deemed a failure because it quickly became apparent that the boundaries between government control and the company ' s powers were ne ##bu ##lous and highly subjective . the government felt obliged to respond to humanitarian calls for better treatment of local peoples in british - occupied territories . edmund burke , a former east india company shareholder and diplomat , was moved to address the situation and introduced a new regulating bill in 1783 . the bill was defeated amid lobbying by company loyalists and accusations of ne ##pot ##ism in the bill ' s recommendations for the appointment of councillors . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 27:0 28:0 29:0 30:1 31:2 32:3 33:4 34:5 35:6 36:7 37:8 38:9 39:10 40:11 41:12 42:13 43:14 44:15 45:16 46:17 47:18 48:19 49:19 50:19 51:20 52:21 53:22 54:22 55:22 56:23 57:24 58:25 59:25 60:26 61:27 62:28 63:29 64:30 65:31 66:32 67:33 68:34 69:35 70:36 71:37 72:38 73:39 74:40 75:41 76:42 77:42 78:42 79:43 80:43 81:44 82:45 83:45 84:46 85:47 86:48 87:49 88:50 89:51 90:52 91:53 92:53 93:54 94:55 95:56 96:57 97:58 98:59 99:60 100:61 101:62 102:63 103:64 104:65 105:66 106:67 107:67 108:68 109:69 110:70 111:71 112:72 113:73 114:74 115:75 116:76 117:77 118:78 119:79 120:80 121:80 122:80 123:81 124:82 125:83 126:83 127:83 128:84 129:85 130:86 131:87 132:88 133:89 134:89\n",
            "I1012 15:05:11.797111 140273920317312 run_squad.py:438] token_to_orig_map: 27:0 28:0 29:0 30:1 31:2 32:3 33:4 34:5 35:6 36:7 37:8 38:9 39:10 40:11 41:12 42:13 43:14 44:15 45:16 46:17 47:18 48:19 49:19 50:19 51:20 52:21 53:22 54:22 55:22 56:23 57:24 58:25 59:25 60:26 61:27 62:28 63:29 64:30 65:31 66:32 67:33 68:34 69:35 70:36 71:37 72:38 73:39 74:40 75:41 76:42 77:42 78:42 79:43 80:43 81:44 82:45 83:45 84:46 85:47 86:48 87:49 88:50 89:51 90:52 91:53 92:53 93:54 94:55 95:56 96:57 97:58 98:59 99:60 100:61 101:62 102:63 103:64 104:65 105:66 106:67 107:67 108:68 109:69 110:70 111:71 112:72 113:73 114:74 115:75 116:76 117:77 118:78 119:79 120:80 121:80 122:80 123:81 124:82 125:83 126:83 127:83 128:84 129:85 130:86 131:87 132:88 133:89 134:89\n",
            "INFO:tensorflow:token_is_max_context: 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True\n",
            "I1012 15:05:11.797259 140273920317312 run_squad.py:440] token_is_max_context: 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2003 1996 2171 1997 1996 2552 2008 2001 1037 3112 1999 4526 7372 2005 1996 4410 1998 1996 1041 2594 2005 2108 20714 1029 102 15091 1005 1055 2552 2001 8357 1037 4945 2138 2009 2855 2150 6835 2008 1996 7372 2090 2231 2491 1998 1996 2194 1005 1055 4204 2020 11265 8569 15534 1998 3811 20714 1012 1996 2231 2371 14723 2000 6869 2000 11470 4455 2005 2488 3949 1997 2334 7243 1999 2329 1011 4548 6500 1012 9493 9894 1010 1037 2280 2264 2634 2194 18668 1998 11125 1010 2001 2333 2000 4769 1996 3663 1998 3107 1037 2047 21575 3021 1999 15331 1012 1996 3021 2001 3249 13463 19670 2011 2194 26590 1998 13519 1997 11265 11008 2964 1999 1996 3021 1005 1055 11433 2005 1996 6098 1997 13189 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.797446 140273920317312 run_squad.py:442] input_ids: 101 2054 2003 1996 2171 1997 1996 2552 2008 2001 1037 3112 1999 4526 7372 2005 1996 4410 1998 1996 1041 2594 2005 2108 20714 1029 102 15091 1005 1055 2552 2001 8357 1037 4945 2138 2009 2855 2150 6835 2008 1996 7372 2090 2231 2491 1998 1996 2194 1005 1055 4204 2020 11265 8569 15534 1998 3811 20714 1012 1996 2231 2371 14723 2000 6869 2000 11470 4455 2005 2488 3949 1997 2334 7243 1999 2329 1011 4548 6500 1012 9493 9894 1010 1037 2280 2264 2634 2194 18668 1998 11125 1010 2001 2333 2000 4769 1996 3663 1998 3107 1037 2047 21575 3021 1999 15331 1012 1996 3021 2001 3249 13463 19670 2011 2194 26590 1998 13519 1997 11265 11008 2964 1999 1996 3021 1005 1055 11433 2005 1996 6098 1997 13189 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.797624 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.797800 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:11.797878 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.802800 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000001\n",
            "I1012 15:05:11.803015 140273920317312 run_squad.py:432] unique_id: 1000000001\n",
            "INFO:tensorflow:example_index: 1\n",
            "I1012 15:05:11.803118 140273920317312 run_squad.py:433] example_index: 1\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.803193 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what do winners of the continental competition get to do ? [SEP] after the world cup , the most important international football competitions are the continental championships , which are organised by each continental confederation and contested between national teams . these are the european championship ( uefa ) , the copa america ( con ##me ##bol ) , african cup of nations ( caf ) , the asian cup ( afc ) , the concacaf gold cup ( concacaf ) and the of ##c nations cup ( of ##c ) . the fifa confederation ##s cup is contested by the winners of all six continental championships , the current fifa world cup champions and the country which is hosting the confederation ##s cup . this is generally regarded as a warm - up tournament for the upcoming fifa world cup and does not carry the same prestige as the world cup itself . the most prestigious competitions in club football are the respective continental championships , which are generally contested between national champions , for example the uefa champions league in europe and the copa libertadores in south america . the winners of each continental competition contest the fifa club world cup . [SEP]\n",
            "I1012 15:05:11.803341 140273920317312 run_squad.py:436] tokens: [CLS] what do winners of the continental competition get to do ? [SEP] after the world cup , the most important international football competitions are the continental championships , which are organised by each continental confederation and contested between national teams . these are the european championship ( uefa ) , the copa america ( con ##me ##bol ) , african cup of nations ( caf ) , the asian cup ( afc ) , the concacaf gold cup ( concacaf ) and the of ##c nations cup ( of ##c ) . the fifa confederation ##s cup is contested by the winners of all six continental championships , the current fifa world cup champions and the country which is hosting the confederation ##s cup . this is generally regarded as a warm - up tournament for the upcoming fifa world cup and does not carry the same prestige as the world cup itself . the most prestigious competitions in club football are the respective continental championships , which are generally contested between national champions , for example the uefa champions league in europe and the copa libertadores in south america . the winners of each continental competition contest the fifa club world cup . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 13:0 14:1 15:2 16:3 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:13 28:13 29:14 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:25 42:26 43:27 44:28 45:29 46:30 47:31 48:31 49:31 50:31 51:32 52:33 53:34 54:35 55:35 56:35 57:35 58:35 59:35 60:36 61:37 62:38 63:39 64:40 65:40 66:40 67:40 68:41 69:42 70:43 71:44 72:44 73:44 74:44 75:45 76:46 77:47 78:48 79:49 80:49 81:49 82:50 83:51 84:52 85:52 86:53 87:54 88:55 89:55 90:55 91:55 92:55 93:56 94:57 95:58 96:58 97:59 98:60 99:61 100:62 101:63 102:64 103:65 104:66 105:67 106:68 107:69 108:69 109:70 110:71 111:72 112:73 113:74 114:75 115:76 116:77 117:78 118:79 119:80 120:81 121:82 122:83 123:83 124:84 125:84 126:85 127:86 128:87 129:88 130:89 131:90 132:91 133:91 134:91 135:92 136:93 137:94 138:95 139:96 140:97 141:98 142:99 143:100 144:101 145:102 146:103 147:104 148:105 149:106 150:107 151:108 152:109 153:110 154:110 155:111 156:112 157:113 158:114 159:115 160:116 161:117 162:118 163:119 164:120 165:121 166:122 167:122 168:123 169:124 170:125 171:126 172:127 173:128 174:129 175:129 176:130 177:131 178:132 179:133 180:134 181:135 182:136 183:137 184:138 185:139 186:140 187:141 188:142 189:143 190:144 191:144 192:145 193:146 194:147 195:148 196:149 197:150 198:151 199:152 200:153 201:154 202:155 203:156 204:156\n",
            "I1012 15:05:11.803505 140273920317312 run_squad.py:438] token_to_orig_map: 13:0 14:1 15:2 16:3 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:13 28:13 29:14 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:25 42:26 43:27 44:28 45:29 46:30 47:31 48:31 49:31 50:31 51:32 52:33 53:34 54:35 55:35 56:35 57:35 58:35 59:35 60:36 61:37 62:38 63:39 64:40 65:40 66:40 67:40 68:41 69:42 70:43 71:44 72:44 73:44 74:44 75:45 76:46 77:47 78:48 79:49 80:49 81:49 82:50 83:51 84:52 85:52 86:53 87:54 88:55 89:55 90:55 91:55 92:55 93:56 94:57 95:58 96:58 97:59 98:60 99:61 100:62 101:63 102:64 103:65 104:66 105:67 106:68 107:69 108:69 109:70 110:71 111:72 112:73 113:74 114:75 115:76 116:77 117:78 118:79 119:80 120:81 121:82 122:83 123:83 124:84 125:84 126:85 127:86 128:87 129:88 130:89 131:90 132:91 133:91 134:91 135:92 136:93 137:94 138:95 139:96 140:97 141:98 142:99 143:100 144:101 145:102 146:103 147:104 148:105 149:106 150:107 151:108 152:109 153:110 154:110 155:111 156:112 157:113 158:114 159:115 160:116 161:117 162:118 163:119 164:120 165:121 166:122 167:122 168:123 169:124 170:125 171:126 172:127 173:128 174:129 175:129 176:130 177:131 178:132 179:133 180:134 181:135 182:136 183:137 184:138 185:139 186:140 187:141 188:142 189:143 190:144 191:144 192:145 193:146 194:147 195:148 196:149 197:150 198:151 199:152 200:153 201:154 202:155 203:156 204:156\n",
            "INFO:tensorflow:token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True\n",
            "I1012 15:05:11.838445 140273920317312 run_squad.py:440] token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2079 4791 1997 1996 6803 2971 2131 2000 2079 1029 102 2044 1996 2088 2452 1010 1996 2087 2590 2248 2374 6479 2024 1996 6803 3219 1010 2029 2024 7362 2011 2169 6803 11078 1998 7259 2090 2120 2780 1012 2122 2024 1996 2647 2528 1006 6663 1007 1010 1996 10613 2637 1006 9530 4168 14956 1007 1010 3060 2452 1997 3741 1006 24689 1007 1010 1996 4004 2452 1006 10511 1007 1010 1996 22169 2751 2452 1006 22169 1007 1998 1996 1997 2278 3741 2452 1006 1997 2278 1007 1012 1996 5713 11078 2015 2452 2003 7259 2011 1996 4791 1997 2035 2416 6803 3219 1010 1996 2783 5713 2088 2452 3966 1998 1996 2406 2029 2003 9936 1996 11078 2015 2452 1012 2023 2003 3227 5240 2004 1037 4010 1011 2039 2977 2005 1996 9046 5713 2088 2452 1998 2515 2025 4287 1996 2168 14653 2004 1996 2088 2452 2993 1012 1996 2087 8919 6479 1999 2252 2374 2024 1996 7972 6803 3219 1010 2029 2024 3227 7259 2090 2120 3966 1010 2005 2742 1996 6663 3966 2223 1999 2885 1998 1996 10613 27968 1999 2148 2637 1012 1996 4791 1997 2169 6803 2971 5049 1996 5713 2252 2088 2452 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.839442 140273920317312 run_squad.py:442] input_ids: 101 2054 2079 4791 1997 1996 6803 2971 2131 2000 2079 1029 102 2044 1996 2088 2452 1010 1996 2087 2590 2248 2374 6479 2024 1996 6803 3219 1010 2029 2024 7362 2011 2169 6803 11078 1998 7259 2090 2120 2780 1012 2122 2024 1996 2647 2528 1006 6663 1007 1010 1996 10613 2637 1006 9530 4168 14956 1007 1010 3060 2452 1997 3741 1006 24689 1007 1010 1996 4004 2452 1006 10511 1007 1010 1996 22169 2751 2452 1006 22169 1007 1998 1996 1997 2278 3741 2452 1006 1997 2278 1007 1012 1996 5713 11078 2015 2452 2003 7259 2011 1996 4791 1997 2035 2416 6803 3219 1010 1996 2783 5713 2088 2452 3966 1998 1996 2406 2029 2003 9936 1996 11078 2015 2452 1012 2023 2003 3227 5240 2004 1037 4010 1011 2039 2977 2005 1996 9046 5713 2088 2452 1998 2515 2025 4287 1996 2168 14653 2004 1996 2088 2452 2993 1012 1996 2087 8919 6479 1999 2252 2374 2024 1996 7972 6803 3219 1010 2029 2024 3227 7259 2090 2120 3966 1010 2005 2742 1996 6663 3966 2223 1999 2885 1998 1996 10613 27968 1999 2148 2637 1012 1996 4791 1997 2169 6803 2971 5049 1996 5713 2252 2088 2452 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.839805 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.840126 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 198\n",
            "I1012 15:05:11.840283 140273920317312 run_squad.py:451] start_position: 198\n",
            "INFO:tensorflow:end_position: 203\n",
            "I1012 15:05:11.840388 140273920317312 run_squad.py:452] end_position: 203\n",
            "INFO:tensorflow:answer: contest the fifa club world cup\n",
            "I1012 15:05:11.840486 140273920317312 run_squad.py:454] answer: contest the fifa club world cup\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.844240 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000002\n",
            "I1012 15:05:11.844435 140273920317312 run_squad.py:432] unique_id: 1000000002\n",
            "INFO:tensorflow:example_index: 2\n",
            "I1012 15:05:11.844498 140273920317312 run_squad.py:433] example_index: 2\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.844551 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what did frederick zu ##gi ##be study in detail for this book ? [SEP] in his book the cr ##uc ##if ##ix ##ion of jesus , physician and forensic path ##ologist frederick zu ##gi ##be studied the likely circumstances of the death of jesus in great detail . zu ##gi ##be carried out a number of experiments over several years to test his theories while he was a medical examiner . these studies included experiments in which volunteers with specific weights were hanging at specific angles and the amount of pull on each hand was measured , in cases where the feet were also secured or not . in these cases the amount of pull and the corresponding pain was found to be significant . [SEP]\n",
            "I1012 15:05:11.844637 140273920317312 run_squad.py:436] tokens: [CLS] what did frederick zu ##gi ##be study in detail for this book ? [SEP] in his book the cr ##uc ##if ##ix ##ion of jesus , physician and forensic path ##ologist frederick zu ##gi ##be studied the likely circumstances of the death of jesus in great detail . zu ##gi ##be carried out a number of experiments over several years to test his theories while he was a medical examiner . these studies included experiments in which volunteers with specific weights were hanging at specific angles and the amount of pull on each hand was measured , in cases where the feet were also secured or not . in these cases the amount of pull and the corresponding pain was found to be significant . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 15:0 16:1 17:2 18:3 19:4 20:4 21:4 22:4 23:4 24:5 25:6 26:6 27:7 28:8 29:9 30:10 31:10 32:11 33:12 34:12 35:12 36:13 37:14 38:15 39:16 40:17 41:18 42:19 43:20 44:21 45:22 46:23 47:24 48:24 49:25 50:25 51:25 52:26 53:27 54:28 55:29 56:30 57:31 58:32 59:33 60:34 61:35 62:36 63:37 64:38 65:39 66:40 67:41 68:42 69:43 70:44 71:44 72:45 73:46 74:47 75:48 76:49 77:50 78:51 79:52 80:53 81:54 82:55 83:56 84:57 85:58 86:59 87:60 88:61 89:62 90:63 91:64 92:65 93:66 94:67 95:68 96:69 97:69 98:70 99:71 100:72 101:73 102:74 103:75 104:76 105:77 106:78 107:79 108:79 109:80 110:81 111:82 112:83 113:84 114:85 115:86 116:87 117:88 118:89 119:90 120:91 121:92 122:93 123:94 124:95 125:95\n",
            "I1012 15:05:11.844742 140273920317312 run_squad.py:438] token_to_orig_map: 15:0 16:1 17:2 18:3 19:4 20:4 21:4 22:4 23:4 24:5 25:6 26:6 27:7 28:8 29:9 30:10 31:10 32:11 33:12 34:12 35:12 36:13 37:14 38:15 39:16 40:17 41:18 42:19 43:20 44:21 45:22 46:23 47:24 48:24 49:25 50:25 51:25 52:26 53:27 54:28 55:29 56:30 57:31 58:32 59:33 60:34 61:35 62:36 63:37 64:38 65:39 66:40 67:41 68:42 69:43 70:44 71:44 72:45 73:46 74:47 75:48 76:49 77:50 78:51 79:52 80:53 81:54 82:55 83:56 84:57 85:58 86:59 87:60 88:61 89:62 90:63 91:64 92:65 93:66 94:67 95:68 96:69 97:69 98:70 99:71 100:72 101:73 102:74 103:75 104:76 105:77 106:78 107:79 108:79 109:80 110:81 111:82 112:83 113:84 114:85 115:86 116:87 117:88 118:89 119:90 120:91 121:92 122:93 123:94 124:95 125:95\n",
            "INFO:tensorflow:token_is_max_context: 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True\n",
            "I1012 15:05:11.844828 140273920317312 run_squad.py:440] token_is_max_context: 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2106 5406 16950 5856 4783 2817 1999 6987 2005 2023 2338 1029 102 1999 2010 2338 1996 13675 14194 10128 7646 3258 1997 4441 1010 7522 1998 15359 4130 8662 5406 16950 5856 4783 3273 1996 3497 6214 1997 1996 2331 1997 4441 1999 2307 6987 1012 16950 5856 4783 3344 2041 1037 2193 1997 7885 2058 2195 2086 2000 3231 2010 8106 2096 2002 2001 1037 2966 19684 1012 2122 2913 2443 7885 1999 2029 7314 2007 3563 15871 2020 5689 2012 3563 12113 1998 1996 3815 1997 4139 2006 2169 2192 2001 7594 1010 1999 3572 2073 1996 2519 2020 2036 7119 2030 2025 1012 1999 2122 3572 1996 3815 1997 4139 1998 1996 7978 3255 2001 2179 2000 2022 3278 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.844968 140273920317312 run_squad.py:442] input_ids: 101 2054 2106 5406 16950 5856 4783 2817 1999 6987 2005 2023 2338 1029 102 1999 2010 2338 1996 13675 14194 10128 7646 3258 1997 4441 1010 7522 1998 15359 4130 8662 5406 16950 5856 4783 3273 1996 3497 6214 1997 1996 2331 1997 4441 1999 2307 6987 1012 16950 5856 4783 3344 2041 1037 2193 1997 7885 2058 2195 2086 2000 3231 2010 8106 2096 2002 2001 1037 2966 19684 1012 2122 2913 2443 7885 1999 2029 7314 2007 3563 15871 2020 5689 2012 3563 12113 1998 1996 3815 1997 4139 2006 2169 2192 2001 7594 1010 1999 3572 2073 1996 2519 2020 2036 7119 2030 2025 1012 1999 2122 3572 1996 3815 1997 4139 1998 1996 7978 3255 2001 2179 2000 2022 3278 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.845091 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.845227 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 37\n",
            "I1012 15:05:11.845284 140273920317312 run_squad.py:451] start_position: 37\n",
            "INFO:tensorflow:end_position: 44\n",
            "I1012 15:05:11.845332 140273920317312 run_squad.py:452] end_position: 44\n",
            "INFO:tensorflow:answer: the likely circumstances of the death of jesus\n",
            "I1012 15:05:11.845378 140273920317312 run_squad.py:454] answer: the likely circumstances of the death of jesus\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.848650 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000003\n",
            "I1012 15:05:11.848831 140273920317312 run_squad.py:432] unique_id: 1000000003\n",
            "INFO:tensorflow:example_index: 3\n",
            "I1012 15:05:11.848892 140273920317312 run_squad.py:433] example_index: 3\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.848945 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] how many millions of tourists does greece ban each year ? [SEP] greece attracts more than 16 million tourists each year , thus contributing 18 . 2 % to the nation ' s gdp in 2008 according to an o ##ec ##d report . the same survey showed that the average tourist expenditure while in greece was $ 1 , 07 ##3 , ranking greece 10th in the world . the number of jobs directly or indirectly related to the tourism sector were 840 , 000 in 2008 and represented 19 % of the country ' s total labor force . in 2009 , greece welcomed over 19 . 3 million tourists , a major increase from the 17 . 7 million tourists the country welcomed in 2008 . [SEP]\n",
            "I1012 15:05:11.849031 140273920317312 run_squad.py:436] tokens: [CLS] how many millions of tourists does greece ban each year ? [SEP] greece attracts more than 16 million tourists each year , thus contributing 18 . 2 % to the nation ' s gdp in 2008 according to an o ##ec ##d report . the same survey showed that the average tourist expenditure while in greece was $ 1 , 07 ##3 , ranking greece 10th in the world . the number of jobs directly or indirectly related to the tourism sector were 840 , 000 in 2008 and represented 19 % of the country ' s total labor force . in 2009 , greece welcomed over 19 . 3 million tourists , a major increase from the 17 . 7 million tourists the country welcomed in 2008 . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:8 23:9 24:10 25:11 26:11 27:11 28:11 29:12 30:13 31:14 32:14 33:14 34:15 35:16 36:17 37:18 38:19 39:20 40:21 41:21 42:21 43:22 44:22 45:23 46:24 47:25 48:26 49:27 50:28 51:29 52:30 53:31 54:32 55:33 56:34 57:35 58:36 59:36 60:36 61:36 62:36 63:36 64:37 65:38 66:39 67:40 68:41 69:42 70:42 71:43 72:44 73:45 74:46 75:47 76:48 77:49 78:50 79:51 80:52 81:53 82:54 83:55 84:56 85:56 86:56 87:57 88:58 89:59 90:60 91:61 92:61 93:62 94:63 95:64 96:64 97:64 98:65 99:66 100:67 101:67 102:68 103:69 104:69 105:70 106:71 107:72 108:73 109:73 110:73 111:74 112:75 113:75 114:76 115:77 116:78 117:79 118:80 119:81 120:81 121:81 122:82 123:83 124:84 125:85 126:86 127:87 128:88 129:88\n",
            "I1012 15:05:11.849143 140273920317312 run_squad.py:438] token_to_orig_map: 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:8 23:9 24:10 25:11 26:11 27:11 28:11 29:12 30:13 31:14 32:14 33:14 34:15 35:16 36:17 37:18 38:19 39:20 40:21 41:21 42:21 43:22 44:22 45:23 46:24 47:25 48:26 49:27 50:28 51:29 52:30 53:31 54:32 55:33 56:34 57:35 58:36 59:36 60:36 61:36 62:36 63:36 64:37 65:38 66:39 67:40 68:41 69:42 70:42 71:43 72:44 73:45 74:46 75:47 76:48 77:49 78:50 79:51 80:52 81:53 82:54 83:55 84:56 85:56 86:56 87:57 88:58 89:59 90:60 91:61 92:61 93:62 94:63 95:64 96:64 97:64 98:65 99:66 100:67 101:67 102:68 103:69 104:69 105:70 106:71 107:72 108:73 109:73 110:73 111:74 112:75 113:75 114:76 115:77 116:78 117:79 118:80 119:81 120:81 121:81 122:82 123:83 124:84 125:85 126:86 127:87 128:88 129:88\n",
            "INFO:tensorflow:token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True\n",
            "I1012 15:05:11.849237 140273920317312 run_squad.py:440] token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True\n",
            "INFO:tensorflow:input_ids: 101 2129 2116 8817 1997 9045 2515 5483 7221 2169 2095 1029 102 5483 17771 2062 2084 2385 2454 9045 2169 2095 1010 2947 8020 2324 1012 1016 1003 2000 1996 3842 1005 1055 14230 1999 2263 2429 2000 2019 1051 8586 2094 3189 1012 1996 2168 5002 3662 2008 1996 2779 7538 20700 2096 1999 5483 2001 1002 1015 1010 5718 2509 1010 5464 5483 6049 1999 1996 2088 1012 1996 2193 1997 5841 3495 2030 17351 3141 2000 1996 6813 4753 2020 28122 1010 2199 1999 2263 1998 3421 2539 1003 1997 1996 2406 1005 1055 2561 4450 2486 1012 1999 2268 1010 5483 10979 2058 2539 1012 1017 2454 9045 1010 1037 2350 3623 2013 1996 2459 1012 1021 2454 9045 1996 2406 10979 1999 2263 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.941915 140273920317312 run_squad.py:442] input_ids: 101 2129 2116 8817 1997 9045 2515 5483 7221 2169 2095 1029 102 5483 17771 2062 2084 2385 2454 9045 2169 2095 1010 2947 8020 2324 1012 1016 1003 2000 1996 3842 1005 1055 14230 1999 2263 2429 2000 2019 1051 8586 2094 3189 1012 1996 2168 5002 3662 2008 1996 2779 7538 20700 2096 1999 5483 2001 1002 1015 1010 5718 2509 1010 5464 5483 6049 1999 1996 2088 1012 1996 2193 1997 5841 3495 2030 17351 3141 2000 1996 6813 4753 2020 28122 1010 2199 1999 2263 1998 3421 2539 1003 1997 1996 2406 1005 1055 2561 4450 2486 1012 1999 2268 1010 5483 10979 2058 2539 1012 1017 2454 9045 1010 1037 2350 3623 2013 1996 2459 1012 1021 2454 9045 1996 2406 10979 1999 2263 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.942391 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.942665 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:11.942801 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.947375 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000004\n",
            "I1012 15:05:11.947561 140273920317312 run_squad.py:432] unique_id: 1000000004\n",
            "INFO:tensorflow:example_index: 4\n",
            "I1012 15:05:11.947623 140273920317312 run_squad.py:433] example_index: 4\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.947675 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what is the main role of the cabinet of government ministers ? [SEP] when the party is represented by members in the lower house of parliament , the party leader simultaneously serves as the leader of the parliamentary group of that full party representation ; depending on a minimum number of seats held , westminster - based parties typically allow for leaders to form front ##ben ##ch teams of senior fellow members of the parliamentary group to serve as critics of aspects of government policy . when a party becomes the largest party not part of the government , the party ' s parliamentary group forms the official opposition , with official opposition front ##ben ##ch team members often forming the official opposition shadow cabinet . when a party achieve ##s enough seats in an election to form a majority , the party ' s front ##ben ##ch becomes the cabinet of government ministers . [SEP]\n",
            "I1012 15:05:11.947769 140273920317312 run_squad.py:436] tokens: [CLS] what is the main role of the cabinet of government ministers ? [SEP] when the party is represented by members in the lower house of parliament , the party leader simultaneously serves as the leader of the parliamentary group of that full party representation ; depending on a minimum number of seats held , westminster - based parties typically allow for leaders to form front ##ben ##ch teams of senior fellow members of the parliamentary group to serve as critics of aspects of government policy . when a party becomes the largest party not part of the government , the party ' s parliamentary group forms the official opposition , with official opposition front ##ben ##ch team members often forming the official opposition shadow cabinet . when a party achieve ##s enough seats in an election to form a majority , the party ' s front ##ben ##ch becomes the cabinet of government ministers . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 14:0 15:1 16:2 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:12 28:13 29:14 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:27 43:28 44:29 45:29 46:30 47:31 48:32 49:33 50:34 51:35 52:36 53:37 54:37 55:38 56:38 57:38 58:39 59:40 60:41 61:42 62:43 63:44 64:45 65:46 66:46 67:46 68:47 69:48 70:49 71:50 72:51 73:52 74:53 75:54 76:55 77:56 78:57 79:58 80:59 81:60 82:61 83:62 84:63 85:64 86:64 87:65 88:66 89:67 90:68 91:69 92:70 93:71 94:72 95:73 96:74 97:75 98:76 99:76 100:77 101:78 102:78 103:78 104:79 105:80 106:81 107:82 108:83 109:84 110:84 111:85 112:86 113:87 114:88 115:88 116:88 117:89 118:90 119:91 120:92 121:93 122:94 123:95 124:96 125:97 126:97 127:98 128:99 129:100 130:101 131:101 132:102 133:103 134:104 135:105 136:106 137:107 138:108 139:109 140:110 141:110 142:111 143:112 144:112 145:112 146:113 147:113 148:113 149:114 150:115 151:116 152:117 153:118 154:119 155:119\n",
            "I1012 15:05:11.947870 140273920317312 run_squad.py:438] token_to_orig_map: 14:0 15:1 16:2 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:12 28:13 29:14 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:27 43:28 44:29 45:29 46:30 47:31 48:32 49:33 50:34 51:35 52:36 53:37 54:37 55:38 56:38 57:38 58:39 59:40 60:41 61:42 62:43 63:44 64:45 65:46 66:46 67:46 68:47 69:48 70:49 71:50 72:51 73:52 74:53 75:54 76:55 77:56 78:57 79:58 80:59 81:60 82:61 83:62 84:63 85:64 86:64 87:65 88:66 89:67 90:68 91:69 92:70 93:71 94:72 95:73 96:74 97:75 98:76 99:76 100:77 101:78 102:78 103:78 104:79 105:80 106:81 107:82 108:83 109:84 110:84 111:85 112:86 113:87 114:88 115:88 116:88 117:89 118:90 119:91 120:92 121:93 122:94 123:95 124:96 125:97 126:97 127:98 128:99 129:100 130:101 131:101 132:102 133:103 134:104 135:105 136:106 137:107 138:108 139:109 140:110 141:110 142:111 143:112 144:112 145:112 146:113 147:113 148:113 149:114 150:115 151:116 152:117 153:118 154:119 155:119\n",
            "INFO:tensorflow:token_is_max_context: 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True\n",
            "I1012 15:05:11.947965 140273920317312 run_squad.py:440] token_is_max_context: 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2003 1996 2364 2535 1997 1996 5239 1997 2231 7767 1029 102 2043 1996 2283 2003 3421 2011 2372 1999 1996 2896 2160 1997 3323 1010 1996 2283 3003 7453 4240 2004 1996 3003 1997 1996 5768 2177 1997 2008 2440 2283 6630 1025 5834 2006 1037 6263 2193 1997 4272 2218 1010 9434 1011 2241 4243 4050 3499 2005 4177 2000 2433 2392 10609 2818 2780 1997 3026 3507 2372 1997 1996 5768 2177 2000 3710 2004 4401 1997 5919 1997 2231 3343 1012 2043 1037 2283 4150 1996 2922 2283 2025 2112 1997 1996 2231 1010 1996 2283 1005 1055 5768 2177 3596 1996 2880 4559 1010 2007 2880 4559 2392 10609 2818 2136 2372 2411 5716 1996 2880 4559 5192 5239 1012 2043 1037 2283 6162 2015 2438 4272 1999 2019 2602 2000 2433 1037 3484 1010 1996 2283 1005 1055 2392 10609 2818 4150 1996 5239 1997 2231 7767 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.948137 140273920317312 run_squad.py:442] input_ids: 101 2054 2003 1996 2364 2535 1997 1996 5239 1997 2231 7767 1029 102 2043 1996 2283 2003 3421 2011 2372 1999 1996 2896 2160 1997 3323 1010 1996 2283 3003 7453 4240 2004 1996 3003 1997 1996 5768 2177 1997 2008 2440 2283 6630 1025 5834 2006 1037 6263 2193 1997 4272 2218 1010 9434 1011 2241 4243 4050 3499 2005 4177 2000 2433 2392 10609 2818 2780 1997 3026 3507 2372 1997 1996 5768 2177 2000 3710 2004 4401 1997 5919 1997 2231 3343 1012 2043 1037 2283 4150 1996 2922 2283 2025 2112 1997 1996 2231 1010 1996 2283 1005 1055 5768 2177 3596 1996 2880 4559 1010 2007 2880 4559 2392 10609 2818 2136 2372 2411 5716 1996 2880 4559 5192 5239 1012 2043 1037 2283 6162 2015 2438 4272 1999 2019 2602 2000 2433 1037 3484 1010 1996 2283 1005 1055 2392 10609 2818 4150 1996 5239 1997 2231 7767 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.948269 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:11.948390 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:11.948443 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:11.953360 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000005\n",
            "I1012 15:05:11.953553 140273920317312 run_squad.py:432] unique_id: 1000000005\n",
            "INFO:tensorflow:example_index: 5\n",
            "I1012 15:05:11.953613 140273920317312 run_squad.py:433] example_index: 5\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:11.953665 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what does the fe ##pc stand for ? [SEP] f ##dr ' s new deal programs often contained equal opportunity clauses stating \" no discrimination shall be made on account of race , color or creed \" , : 11 but the true forerunner to affirmative action was the interior secretary of the time , harold l . ic ##kes . ic ##kes prohibited discrimination in hiring for public works administration funded projects and oversaw not only the institution of a quota system , where contractors were required to employ a fixed percentage of black workers , by robert c . weaver and clark foreman , : 12 but also the equal pay of women proposed by harry hopkins . : 14 ##f ##dr ' s largest contribution to affirmative action , however , lay in his executive order 880 ##2 which prohibited discrimination in the defense industry or government . : 22 the executive order promoted the idea that if taxpayer funds were accepted through a government contract , then all taxpayers should have an equal opportunity to work through the contractor . : 23 – 4 to enforce this idea , roosevelt created the fair employment practices committee ( fe ##pc ) with the power to investigate hiring practices by government contractors . : 22 [SEP]\n",
            "I1012 15:05:11.953775 140273920317312 run_squad.py:436] tokens: [CLS] what does the fe ##pc stand for ? [SEP] f ##dr ' s new deal programs often contained equal opportunity clauses stating \" no discrimination shall be made on account of race , color or creed \" , : 11 but the true forerunner to affirmative action was the interior secretary of the time , harold l . ic ##kes . ic ##kes prohibited discrimination in hiring for public works administration funded projects and oversaw not only the institution of a quota system , where contractors were required to employ a fixed percentage of black workers , by robert c . weaver and clark foreman , : 12 but also the equal pay of women proposed by harry hopkins . : 14 ##f ##dr ' s largest contribution to affirmative action , however , lay in his executive order 880 ##2 which prohibited discrimination in the defense industry or government . : 22 the executive order promoted the idea that if taxpayer funds were accepted through a government contract , then all taxpayers should have an equal opportunity to work through the contractor . : 23 – 4 to enforce this idea , roosevelt created the fair employment practices committee ( fe ##pc ) with the power to investigate hiring practices by government contractors . : 22 [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 10:0 11:0 12:0 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:9 23:10 24:10 25:11 26:12 27:13 28:14 29:15 30:16 31:17 32:18 33:18 34:19 35:20 36:21 37:21 38:21 39:21 40:21 41:22 42:23 43:24 44:25 45:26 46:27 47:28 48:29 49:30 50:31 51:32 52:33 53:34 54:35 55:35 56:36 57:37 58:37 59:38 60:38 61:38 62:39 63:39 64:40 65:41 66:42 67:43 68:44 69:45 70:46 71:47 72:48 73:49 74:50 75:51 76:52 77:53 78:54 79:55 80:56 81:57 82:58 83:59 84:59 85:60 86:61 87:62 88:63 89:64 90:65 91:66 92:67 93:68 94:69 95:70 96:71 97:71 98:72 99:73 100:74 101:74 102:75 103:76 104:77 105:78 106:78 107:78 108:78 109:79 110:80 111:81 112:82 113:83 114:84 115:85 116:86 117:87 118:88 119:89 120:89 121:89 122:89 123:89 124:89 125:89 126:89 127:90 128:91 129:92 130:93 131:94 132:94 133:95 134:95 135:96 136:97 137:98 138:99 139:100 140:101 141:101 142:102 143:103 144:104 145:105 146:106 147:107 148:108 149:109 150:110 151:110 152:110 153:110 154:111 155:112 156:113 157:114 158:115 159:116 160:117 161:118 162:119 163:120 164:121 165:122 166:123 167:124 168:125 169:126 170:126 171:127 172:128 173:129 174:130 175:131 176:132 177:133 178:134 179:135 180:136 181:137 182:138 183:139 184:139 185:139 186:139 187:139 188:139 189:140 190:141 191:142 192:143 193:143 194:144 195:145 196:146 197:147 198:148 199:149 200:150 201:151 202:151 203:151 204:151 205:152 206:153 207:154 208:155 209:156 210:157 211:158 212:159 213:160 214:161 215:161 216:161 217:161\n",
            "I1012 15:05:11.953910 140273920317312 run_squad.py:438] token_to_orig_map: 10:0 11:0 12:0 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:9 23:10 24:10 25:11 26:12 27:13 28:14 29:15 30:16 31:17 32:18 33:18 34:19 35:20 36:21 37:21 38:21 39:21 40:21 41:22 42:23 43:24 44:25 45:26 46:27 47:28 48:29 49:30 50:31 51:32 52:33 53:34 54:35 55:35 56:36 57:37 58:37 59:38 60:38 61:38 62:39 63:39 64:40 65:41 66:42 67:43 68:44 69:45 70:46 71:47 72:48 73:49 74:50 75:51 76:52 77:53 78:54 79:55 80:56 81:57 82:58 83:59 84:59 85:60 86:61 87:62 88:63 89:64 90:65 91:66 92:67 93:68 94:69 95:70 96:71 97:71 98:72 99:73 100:74 101:74 102:75 103:76 104:77 105:78 106:78 107:78 108:78 109:79 110:80 111:81 112:82 113:83 114:84 115:85 116:86 117:87 118:88 119:89 120:89 121:89 122:89 123:89 124:89 125:89 126:89 127:90 128:91 129:92 130:93 131:94 132:94 133:95 134:95 135:96 136:97 137:98 138:99 139:100 140:101 141:101 142:102 143:103 144:104 145:105 146:106 147:107 148:108 149:109 150:110 151:110 152:110 153:110 154:111 155:112 156:113 157:114 158:115 159:116 160:117 161:118 162:119 163:120 164:121 165:122 166:123 167:124 168:125 169:126 170:126 171:127 172:128 173:129 174:130 175:131 176:132 177:133 178:134 179:135 180:136 181:137 182:138 183:139 184:139 185:139 186:139 187:139 188:139 189:140 190:141 191:142 192:143 193:143 194:144 195:145 196:146 197:147 198:148 199:149 200:150 201:151 202:151 203:151 204:151 205:152 206:153 207:154 208:155 209:156 210:157 211:158 212:159 213:160 214:161 215:161 216:161 217:161\n",
            "INFO:tensorflow:token_is_max_context: 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True 216:True 217:True\n",
            "I1012 15:05:12.050902 140273920317312 run_squad.py:440] token_is_max_context: 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True 216:True 217:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2515 1996 10768 15042 3233 2005 1029 102 1042 13626 1005 1055 2047 3066 3454 2411 4838 5020 4495 24059 5517 1000 2053 9147 4618 2022 2081 2006 4070 1997 2679 1010 3609 2030 16438 1000 1010 1024 2340 2021 1996 2995 23993 2000 27352 2895 2001 1996 4592 3187 1997 1996 2051 1010 7157 1048 1012 24582 9681 1012 24582 9681 10890 9147 1999 14763 2005 2270 2573 3447 6787 3934 1998 14105 2025 2069 1996 5145 1997 1037 20563 2291 1010 2073 16728 2020 3223 2000 12666 1037 4964 7017 1997 2304 3667 1010 2011 2728 1039 1012 14077 1998 5215 18031 1010 1024 2260 2021 2036 1996 5020 3477 1997 2308 3818 2011 4302 10239 1012 1024 2403 2546 13626 1005 1055 2922 6691 2000 27352 2895 1010 2174 1010 3913 1999 2010 3237 2344 26839 2475 2029 10890 9147 1999 1996 3639 3068 2030 2231 1012 1024 2570 1996 3237 2344 3755 1996 2801 2008 2065 26980 5029 2020 3970 2083 1037 2231 3206 1010 2059 2035 26457 2323 2031 2019 5020 4495 2000 2147 2083 1996 13666 1012 1024 2603 1516 1018 2000 16306 2023 2801 1010 8573 2580 1996 4189 6107 6078 2837 1006 10768 15042 1007 2007 1996 2373 2000 8556 14763 6078 2011 2231 16728 1012 1024 2570 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.051311 140273920317312 run_squad.py:442] input_ids: 101 2054 2515 1996 10768 15042 3233 2005 1029 102 1042 13626 1005 1055 2047 3066 3454 2411 4838 5020 4495 24059 5517 1000 2053 9147 4618 2022 2081 2006 4070 1997 2679 1010 3609 2030 16438 1000 1010 1024 2340 2021 1996 2995 23993 2000 27352 2895 2001 1996 4592 3187 1997 1996 2051 1010 7157 1048 1012 24582 9681 1012 24582 9681 10890 9147 1999 14763 2005 2270 2573 3447 6787 3934 1998 14105 2025 2069 1996 5145 1997 1037 20563 2291 1010 2073 16728 2020 3223 2000 12666 1037 4964 7017 1997 2304 3667 1010 2011 2728 1039 1012 14077 1998 5215 18031 1010 1024 2260 2021 2036 1996 5020 3477 1997 2308 3818 2011 4302 10239 1012 1024 2403 2546 13626 1005 1055 2922 6691 2000 27352 2895 1010 2174 1010 3913 1999 2010 3237 2344 26839 2475 2029 10890 9147 1999 1996 3639 3068 2030 2231 1012 1024 2570 1996 3237 2344 3755 1996 2801 2008 2065 26980 5029 2020 3970 2083 1037 2231 3206 1010 2059 2035 26457 2323 2031 2019 5020 4495 2000 2147 2083 1996 13666 1012 1024 2603 1516 1018 2000 16306 2023 2801 1010 8573 2580 1996 4189 6107 6078 2837 1006 10768 15042 1007 2007 1996 2373 2000 8556 14763 6078 2011 2231 16728 1012 1024 2570 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.052009 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.053452 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 197\n",
            "I1012 15:05:12.053611 140273920317312 run_squad.py:451] start_position: 197\n",
            "INFO:tensorflow:end_position: 200\n",
            "I1012 15:05:12.053716 140273920317312 run_squad.py:452] end_position: 200\n",
            "INFO:tensorflow:answer: fair employment practices committee\n",
            "I1012 15:05:12.053800 140273920317312 run_squad.py:454] answer: fair employment practices committee\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.057355 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000006\n",
            "I1012 15:05:12.057563 140273920317312 run_squad.py:432] unique_id: 1000000006\n",
            "INFO:tensorflow:example_index: 6\n",
            "I1012 15:05:12.057690 140273920317312 run_squad.py:433] example_index: 6\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.057785 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] the structures that still remain are open to whom ? [SEP] because it was designated as the national capital , many structures were built around that time . even today , some of them still remain which are open to tourists . [SEP]\n",
            "I1012 15:05:12.057899 140273920317312 run_squad.py:436] tokens: [CLS] the structures that still remain are open to whom ? [SEP] because it was designated as the national capital , many structures were built around that time . even today , some of them still remain which are open to tourists . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 12:0 13:1 14:2 15:3 16:4 17:5 18:6 19:7 20:7 21:8 22:9 23:10 24:11 25:12 26:13 27:14 28:14 29:15 30:16 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:26\n",
            "I1012 15:05:12.058028 140273920317312 run_squad.py:438] token_to_orig_map: 12:0 13:1 14:2 15:3 16:4 17:5 18:6 19:7 20:7 21:8 22:9 23:10 24:11 25:12 26:13 27:14 28:14 29:15 30:16 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:26\n",
            "INFO:tensorflow:token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True\n",
            "I1012 15:05:12.058168 140273920317312 run_squad.py:440] token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True\n",
            "INFO:tensorflow:input_ids: 101 1996 5090 2008 2145 3961 2024 2330 2000 3183 1029 102 2138 2009 2001 4351 2004 1996 2120 3007 1010 2116 5090 2020 2328 2105 2008 2051 1012 2130 2651 1010 2070 1997 2068 2145 3961 2029 2024 2330 2000 9045 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.058418 140273920317312 run_squad.py:442] input_ids: 101 1996 5090 2008 2145 3961 2024 2330 2000 3183 1029 102 2138 2009 2001 4351 2004 1996 2120 3007 1010 2116 5090 2020 2328 2105 2008 2051 1012 2130 2651 1010 2070 1997 2068 2145 3961 2029 2024 2330 2000 9045 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.058690 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.058954 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 41\n",
            "I1012 15:05:12.059087 140273920317312 run_squad.py:451] start_position: 41\n",
            "INFO:tensorflow:end_position: 41\n",
            "I1012 15:05:12.059221 140273920317312 run_squad.py:452] end_position: 41\n",
            "INFO:tensorflow:answer: tourists\n",
            "I1012 15:05:12.059319 140273920317312 run_squad.py:454] answer: tourists\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.064311 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000007\n",
            "I1012 15:05:12.064494 140273920317312 run_squad.py:432] unique_id: 1000000007\n",
            "INFO:tensorflow:example_index: 7\n",
            "I1012 15:05:12.064557 140273920317312 run_squad.py:433] example_index: 7\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.064617 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] when was the mann act passed ? [SEP] the bureau ' s first official task was visiting and making surveys of the houses of prostitution in preparation for enforcing the \" white slave traffic act , \" or mann act , passed on june 25 , 1910 . in 1932 , it was renamed the united states bureau of investigation . the following year it was linked to the bureau of prohibition and rec ##hri ##sten ##ed the division of investigation ( doi ) before finally becoming an independent service within the department of justice in 1935 . in the same year , its name was officially changed from the division of investigation to the present - day federal bureau of investigation , or fbi . [SEP]\n",
            "I1012 15:05:12.064705 140273920317312 run_squad.py:436] tokens: [CLS] when was the mann act passed ? [SEP] the bureau ' s first official task was visiting and making surveys of the houses of prostitution in preparation for enforcing the \" white slave traffic act , \" or mann act , passed on june 25 , 1910 . in 1932 , it was renamed the united states bureau of investigation . the following year it was linked to the bureau of prohibition and rec ##hri ##sten ##ed the division of investigation ( doi ) before finally becoming an independent service within the department of justice in 1935 . in the same year , its name was officially changed from the division of investigation to the present - day federal bureau of investigation , or fbi . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 9:0 10:1 11:1 12:1 13:2 14:3 15:4 16:5 17:6 18:7 19:8 20:9 21:10 22:11 23:12 24:13 25:14 26:15 27:16 28:17 29:18 30:19 31:20 32:20 33:21 34:22 35:23 36:23 37:23 38:24 39:25 40:26 41:26 42:27 43:28 44:29 45:30 46:30 47:31 48:31 49:32 50:33 51:33 52:34 53:35 54:36 55:37 56:38 57:39 58:40 59:41 60:42 61:42 62:43 63:44 64:45 65:46 66:47 67:48 68:49 69:50 70:51 71:52 72:53 73:54 74:55 75:55 76:55 77:55 78:56 79:57 80:58 81:59 82:60 83:60 84:60 85:61 86:62 87:63 88:64 89:65 90:66 91:67 92:68 93:69 94:70 95:71 96:72 97:73 98:73 99:74 100:75 101:76 102:77 103:77 104:78 105:79 106:80 107:81 108:82 109:83 110:84 111:85 112:86 113:87 114:88 115:89 116:90 117:90 118:90 119:91 120:92 121:93 122:94 123:94 124:95 125:96 126:96\n",
            "I1012 15:05:12.064805 140273920317312 run_squad.py:438] token_to_orig_map: 9:0 10:1 11:1 12:1 13:2 14:3 15:4 16:5 17:6 18:7 19:8 20:9 21:10 22:11 23:12 24:13 25:14 26:15 27:16 28:17 29:18 30:19 31:20 32:20 33:21 34:22 35:23 36:23 37:23 38:24 39:25 40:26 41:26 42:27 43:28 44:29 45:30 46:30 47:31 48:31 49:32 50:33 51:33 52:34 53:35 54:36 55:37 56:38 57:39 58:40 59:41 60:42 61:42 62:43 63:44 64:45 65:46 66:47 67:48 68:49 69:50 70:51 71:52 72:53 73:54 74:55 75:55 76:55 77:55 78:56 79:57 80:58 81:59 82:60 83:60 84:60 85:61 86:62 87:63 88:64 89:65 90:66 91:67 92:68 93:69 94:70 95:71 96:72 97:73 98:73 99:74 100:75 101:76 102:77 103:77 104:78 105:79 106:80 107:81 108:82 109:83 110:84 111:85 112:86 113:87 114:88 115:89 116:90 117:90 118:90 119:91 120:92 121:93 122:94 123:94 124:95 125:96 126:96\n",
            "INFO:tensorflow:token_is_max_context: 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True\n",
            "I1012 15:05:12.064894 140273920317312 run_squad.py:440] token_is_max_context: 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True\n",
            "INFO:tensorflow:input_ids: 101 2043 2001 1996 10856 2552 2979 1029 102 1996 4879 1005 1055 2034 2880 4708 2001 5873 1998 2437 12265 1997 1996 3506 1997 15016 1999 7547 2005 27455 1996 1000 2317 6658 4026 2552 1010 1000 2030 10856 2552 1010 2979 2006 2238 2423 1010 4976 1012 1999 4673 1010 2009 2001 4096 1996 2142 2163 4879 1997 4812 1012 1996 2206 2095 2009 2001 5799 2000 1996 4879 1997 13574 1998 28667 26378 16173 2098 1996 2407 1997 4812 1006 9193 1007 2077 2633 3352 2019 2981 2326 2306 1996 2533 1997 3425 1999 4437 1012 1999 1996 2168 2095 1010 2049 2171 2001 3985 2904 2013 1996 2407 1997 4812 2000 1996 2556 1011 2154 2976 4879 1997 4812 1010 2030 8495 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.065037 140273920317312 run_squad.py:442] input_ids: 101 2043 2001 1996 10856 2552 2979 1029 102 1996 4879 1005 1055 2034 2880 4708 2001 5873 1998 2437 12265 1997 1996 3506 1997 15016 1999 7547 2005 27455 1996 1000 2317 6658 4026 2552 1010 1000 2030 10856 2552 1010 2979 2006 2238 2423 1010 4976 1012 1999 4673 1010 2009 2001 4096 1996 2142 2163 4879 1997 4812 1012 1996 2206 2095 2009 2001 5799 2000 1996 4879 1997 13574 1998 28667 26378 16173 2098 1996 2407 1997 4812 1006 9193 1007 2077 2633 3352 2019 2981 2326 2306 1996 2533 1997 3425 1999 4437 1012 1999 1996 2168 2095 1010 2049 2171 2001 3985 2904 2013 1996 2407 1997 4812 2000 1996 2556 1011 2154 2976 4879 1997 4812 1010 2030 8495 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.065172 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.065295 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 44\n",
            "I1012 15:05:12.065352 140273920317312 run_squad.py:451] start_position: 44\n",
            "INFO:tensorflow:end_position: 47\n",
            "I1012 15:05:12.065400 140273920317312 run_squad.py:452] end_position: 47\n",
            "INFO:tensorflow:answer: june 25 , 1910\n",
            "I1012 15:05:12.065448 140273920317312 run_squad.py:454] answer: june 25 , 1910\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.068165 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000008\n",
            "I1012 15:05:12.068338 140273920317312 run_squad.py:432] unique_id: 1000000008\n",
            "INFO:tensorflow:example_index: 8\n",
            "I1012 15:05:12.068398 140273920317312 run_squad.py:433] example_index: 8\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.068448 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what is the result of / e / being the same in central , western and bel ##ear ##ic ? [SEP] central , western , and bal ##ear ##ic differ in the lexi ##cal incidence of stressed / e / and / ɛ / . usually , words with / ɛ / in central catalan correspond to / ə / in bal ##ear ##ic and / e / in western catalan . words with / e / in bal ##ear ##ic almost always have / e / in central and western catalan as well . [ vague ] as a result , central catalan has a much higher incidence of / e / . [SEP]\n",
            "I1012 15:05:12.068530 140273920317312 run_squad.py:436] tokens: [CLS] what is the result of / e / being the same in central , western and bel ##ear ##ic ? [SEP] central , western , and bal ##ear ##ic differ in the lexi ##cal incidence of stressed / e / and / ɛ / . usually , words with / ɛ / in central catalan correspond to / ə / in bal ##ear ##ic and / e / in western catalan . words with / e / in bal ##ear ##ic almost always have / e / in central and western catalan as well . [ vague ] as a result , central catalan has a much higher incidence of / e / . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 22:0 23:0 24:1 25:1 26:2 27:3 28:3 29:3 30:4 31:5 32:6 33:7 34:7 35:8 36:9 37:10 38:11 39:11 40:11 41:12 42:13 43:13 44:13 45:13 46:14 47:14 48:15 49:16 50:17 51:17 52:17 53:18 54:19 55:20 56:21 57:22 58:23 59:23 60:23 61:24 62:25 63:25 64:25 65:26 66:27 67:27 68:27 69:28 70:29 71:30 72:30 73:31 74:32 75:33 76:33 77:33 78:34 79:35 80:35 81:35 82:36 83:37 84:38 85:39 86:39 87:39 88:40 89:41 90:42 91:43 92:44 93:45 94:46 95:46 96:46 97:46 98:46 99:47 100:48 101:49 102:49 103:50 104:51 105:52 106:53 107:54 108:55 109:56 110:57 111:58 112:58 113:58 114:58\n",
            "I1012 15:05:12.068628 140273920317312 run_squad.py:438] token_to_orig_map: 22:0 23:0 24:1 25:1 26:2 27:3 28:3 29:3 30:4 31:5 32:6 33:7 34:7 35:8 36:9 37:10 38:11 39:11 40:11 41:12 42:13 43:13 44:13 45:13 46:14 47:14 48:15 49:16 50:17 51:17 52:17 53:18 54:19 55:20 56:21 57:22 58:23 59:23 60:23 61:24 62:25 63:25 64:25 65:26 66:27 67:27 68:27 69:28 70:29 71:30 72:30 73:31 74:32 75:33 76:33 77:33 78:34 79:35 80:35 81:35 82:36 83:37 84:38 85:39 86:39 87:39 88:40 89:41 90:42 91:43 92:44 93:45 94:46 95:46 96:46 97:46 98:46 99:47 100:48 101:49 102:49 103:50 104:51 105:52 106:53 107:54 108:55 109:56 110:57 111:58 112:58 113:58 114:58\n",
            "INFO:tensorflow:token_is_max_context: 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True\n",
            "I1012 15:05:12.068710 140273920317312 run_squad.py:440] token_is_max_context: 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2003 1996 2765 1997 1013 1041 1013 2108 1996 2168 1999 2430 1010 2530 1998 19337 14644 2594 1029 102 2430 1010 2530 1010 1998 28352 14644 2594 11234 1999 1996 16105 9289 18949 1997 13233 1013 1041 1013 1998 1013 1115 1013 1012 2788 1010 2616 2007 1013 1115 1013 1999 2430 13973 17254 2000 1013 1114 1013 1999 28352 14644 2594 1998 1013 1041 1013 1999 2530 13973 1012 2616 2007 1013 1041 1013 1999 28352 14644 2594 2471 2467 2031 1013 1041 1013 1999 2430 1998 2530 13973 2004 2092 1012 1031 13727 1033 2004 1037 2765 1010 2430 13973 2038 1037 2172 3020 18949 1997 1013 1041 1013 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.163855 140273920317312 run_squad.py:442] input_ids: 101 2054 2003 1996 2765 1997 1013 1041 1013 2108 1996 2168 1999 2430 1010 2530 1998 19337 14644 2594 1029 102 2430 1010 2530 1010 1998 28352 14644 2594 11234 1999 1996 16105 9289 18949 1997 13233 1013 1041 1013 1998 1013 1115 1013 1012 2788 1010 2616 2007 1013 1115 1013 1999 2430 13973 17254 2000 1013 1114 1013 1999 28352 14644 2594 1998 1013 1041 1013 1999 2530 13973 1012 2616 2007 1013 1041 1013 1999 28352 14644 2594 2471 2467 2031 1013 1041 1013 1999 2430 1998 2530 13973 2004 2092 1012 1031 13727 1033 2004 1037 2765 1010 2430 13973 2038 1037 2172 3020 18949 1997 1013 1041 1013 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.164362 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.164649 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 108\n",
            "I1012 15:05:12.164793 140273920317312 run_squad.py:451] start_position: 108\n",
            "INFO:tensorflow:end_position: 109\n",
            "I1012 15:05:12.164898 140273920317312 run_squad.py:452] end_position: 109\n",
            "INFO:tensorflow:answer: higher incidence\n",
            "I1012 15:05:12.165008 140273920317312 run_squad.py:454] answer: higher incidence\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.169338 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000009\n",
            "I1012 15:05:12.169534 140273920317312 run_squad.py:432] unique_id: 1000000009\n",
            "INFO:tensorflow:example_index: 9\n",
            "I1012 15:05:12.169600 140273920317312 run_squad.py:433] example_index: 9\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.169654 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what did the old letter ⟨ [UNK] ⟩ become ? [SEP] older letters of the russian alphabet include ⟨ [UNK] ⟩ , which merged to ⟨ е ⟩ ( / je / or / ʲ ##e / ) ; ⟨ і ⟩ and ⟨ [UNK] ⟩ , which both merged to ⟨ и ⟩ ( / i / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ ф ⟩ ( / f / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ у ⟩ ( / u / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ ю ⟩ ( / ju / or / ʲ ##u / ) ; and ⟨ [UNK] / ⟨ [UNK] ⟩ ⟩ , which later were graphical ##ly res ##ha ##ped into ⟨ я ⟩ and merged phonetic ##ally to / ja / or / ʲ ##a / . while these older letters have been abandoned at one time or another , they may be used in this and related articles . the yer ##s ⟨ ъ ⟩ and ⟨ ь ⟩ originally indicated the pronunciation of ultra - short or reduced / u / , / i / . [SEP]\n",
            "I1012 15:05:12.169772 140273920317312 run_squad.py:436] tokens: [CLS] what did the old letter ⟨ [UNK] ⟩ become ? [SEP] older letters of the russian alphabet include ⟨ [UNK] ⟩ , which merged to ⟨ е ⟩ ( / je / or / ʲ ##e / ) ; ⟨ і ⟩ and ⟨ [UNK] ⟩ , which both merged to ⟨ и ⟩ ( / i / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ ф ⟩ ( / f / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ у ⟩ ( / u / ) ; ⟨ [UNK] ⟩ , which merged to ⟨ ю ⟩ ( / ju / or / ʲ ##u / ) ; and ⟨ [UNK] / ⟨ [UNK] ⟩ ⟩ , which later were graphical ##ly res ##ha ##ped into ⟨ я ⟩ and merged phonetic ##ally to / ja / or / ʲ ##a / . while these older letters have been abandoned at one time or another , they may be used in this and related articles . the yer ##s ⟨ ъ ⟩ and ⟨ ь ⟩ originally indicated the pronunciation of ultra - short or reduced / u / , / i / . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 12:0 13:1 14:2 15:3 16:4 17:5 18:6 19:7 20:7 21:7 22:7 23:8 24:9 25:10 26:11 27:11 28:11 29:12 30:12 31:12 32:12 33:13 34:14 35:14 36:14 37:14 38:14 39:14 40:15 41:15 42:15 43:16 44:17 45:17 46:17 47:17 48:18 49:19 50:20 51:21 52:22 53:22 54:22 55:23 56:23 57:23 58:23 59:23 60:23 61:24 62:24 63:24 64:24 65:25 66:26 67:27 68:28 69:28 70:28 71:29 72:29 73:29 74:29 75:29 76:29 77:30 78:30 79:30 80:30 81:31 82:32 83:33 84:34 85:34 86:34 87:35 88:35 89:35 90:35 91:35 92:35 93:36 94:36 95:36 96:36 97:37 98:38 99:39 100:40 101:40 102:40 103:41 104:41 105:41 106:41 107:42 108:43 109:43 110:43 111:43 112:43 113:43 114:44 115:45 116:45 117:45 118:45 119:45 120:45 121:45 122:45 123:46 124:47 125:48 126:49 127:49 128:50 129:50 130:50 131:51 132:52 133:52 134:52 135:53 136:54 137:55 138:55 139:56 140:57 141:57 142:57 143:58 144:59 145:59 146:59 147:59 148:59 149:60 150:61 151:62 152:63 153:64 154:65 155:66 156:67 157:68 158:69 159:70 160:71 161:71 162:72 163:73 164:74 165:75 166:76 167:77 168:78 169:79 170:80 171:80 172:81 173:82 174:82 175:83 176:83 177:83 178:84 179:85 180:85 181:85 182:86 183:87 184:88 185:89 186:90 187:91 188:91 189:91 190:92 191:93 192:94 193:94 194:94 195:94 196:95 197:95 198:95 199:95\n",
            "I1012 15:05:12.169896 140273920317312 run_squad.py:438] token_to_orig_map: 12:0 13:1 14:2 15:3 16:4 17:5 18:6 19:7 20:7 21:7 22:7 23:8 24:9 25:10 26:11 27:11 28:11 29:12 30:12 31:12 32:12 33:13 34:14 35:14 36:14 37:14 38:14 39:14 40:15 41:15 42:15 43:16 44:17 45:17 46:17 47:17 48:18 49:19 50:20 51:21 52:22 53:22 54:22 55:23 56:23 57:23 58:23 59:23 60:23 61:24 62:24 63:24 64:24 65:25 66:26 67:27 68:28 69:28 70:28 71:29 72:29 73:29 74:29 75:29 76:29 77:30 78:30 79:30 80:30 81:31 82:32 83:33 84:34 85:34 86:34 87:35 88:35 89:35 90:35 91:35 92:35 93:36 94:36 95:36 96:36 97:37 98:38 99:39 100:40 101:40 102:40 103:41 104:41 105:41 106:41 107:42 108:43 109:43 110:43 111:43 112:43 113:43 114:44 115:45 116:45 117:45 118:45 119:45 120:45 121:45 122:45 123:46 124:47 125:48 126:49 127:49 128:50 129:50 130:50 131:51 132:52 133:52 134:52 135:53 136:54 137:55 138:55 139:56 140:57 141:57 142:57 143:58 144:59 145:59 146:59 147:59 148:59 149:60 150:61 151:62 152:63 153:64 154:65 155:66 156:67 157:68 158:69 159:70 160:71 161:71 162:72 163:73 164:74 165:75 166:76 167:77 168:78 169:79 170:80 171:80 172:81 173:82 174:82 175:83 176:83 177:83 178:84 179:85 180:85 181:85 182:86 183:87 184:88 185:89 186:90 187:91 188:91 189:91 190:92 191:93 192:94 193:94 194:94 195:94 196:95 197:95 198:95 199:95\n",
            "INFO:tensorflow:token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True\n",
            "I1012 15:05:12.170008 140273920317312 run_squad.py:440] token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2106 1996 2214 3661 1629 100 1630 2468 1029 102 3080 4144 1997 1996 2845 12440 2421 1629 100 1630 1010 2029 5314 2000 1629 1185 1630 1006 1013 15333 1013 2030 1013 1141 2063 1013 1007 1025 1629 1213 1630 1998 1629 100 1630 1010 2029 2119 5314 2000 1629 1188 1630 1006 1013 1045 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1199 1630 1006 1013 1042 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1198 1630 1006 1013 1057 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1209 1630 1006 1013 18414 1013 2030 1013 1141 2226 1013 1007 1025 1998 1629 100 1013 1629 100 1630 1630 1010 2029 2101 2020 20477 2135 24501 3270 5669 2046 1629 1210 1630 1998 5314 26664 3973 2000 1013 14855 1013 2030 1013 1141 2050 1013 1012 2096 2122 3080 4144 2031 2042 4704 2012 2028 2051 2030 2178 1010 2027 2089 2022 2109 1999 2023 1998 3141 4790 1012 1996 20416 2015 1629 1205 1630 1998 1629 1207 1630 2761 5393 1996 15498 1997 11087 1011 2460 2030 4359 1013 1057 1013 1010 1013 1045 1013 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.170168 140273920317312 run_squad.py:442] input_ids: 101 2054 2106 1996 2214 3661 1629 100 1630 2468 1029 102 3080 4144 1997 1996 2845 12440 2421 1629 100 1630 1010 2029 5314 2000 1629 1185 1630 1006 1013 15333 1013 2030 1013 1141 2063 1013 1007 1025 1629 1213 1630 1998 1629 100 1630 1010 2029 2119 5314 2000 1629 1188 1630 1006 1013 1045 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1199 1630 1006 1013 1042 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1198 1630 1006 1013 1057 1013 1007 1025 1629 100 1630 1010 2029 5314 2000 1629 1209 1630 1006 1013 18414 1013 2030 1013 1141 2226 1013 1007 1025 1998 1629 100 1013 1629 100 1630 1630 1010 2029 2101 2020 20477 2135 24501 3270 5669 2046 1629 1210 1630 1998 5314 26664 3973 2000 1013 14855 1013 2030 1013 1141 2050 1013 1012 2096 2122 3080 4144 2031 2042 4704 2012 2028 2051 2030 2178 1010 2027 2089 2022 2109 1999 2023 1998 3141 4790 1012 1996 20416 2015 1629 1205 1630 1998 1629 1207 1630 2761 5393 1996 15498 1997 11087 1011 2460 2030 4359 1013 1057 1013 1010 1013 1045 1013 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.170299 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.170420 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 26\n",
            "I1012 15:05:12.170477 140273920317312 run_squad.py:451] start_position: 26\n",
            "INFO:tensorflow:end_position: 28\n",
            "I1012 15:05:12.170526 140273920317312 run_squad.py:452] end_position: 28\n",
            "INFO:tensorflow:answer: ⟨ е ⟩\n",
            "I1012 15:05:12.170573 140273920317312 run_squad.py:454] answer: ⟨ е ⟩\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.175814 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000010\n",
            "I1012 15:05:12.176030 140273920317312 run_squad.py:432] unique_id: 1000000010\n",
            "INFO:tensorflow:example_index: 10\n",
            "I1012 15:05:12.176107 140273920317312 run_squad.py:433] example_index: 10\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.176164 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what was the problem with the palace ' s chimneys ? [SEP] buckingham palace finally became the principal royal residence in 1837 , on the accession of queen victoria , who was the first monarch to reside there ; her predecessor william iv had died before its completion . while the state rooms were a riot of gil ##t and colour , the nec ##ess ##ities of the new palace were somewhat less luxurious . for one thing , it was reported the chimneys smoked so much that the fires had to be allowed to die down , and consequently the court shivered in icy mag ##ni ##fi ##cence . ventilation was so bad that the interior smelled , and when a decision was taken to install gas lamps , there was a serious worry about the build - up of gas on the lower floors . it was also said that staff were lax and lazy and the palace was dirty . following the queen ' s marriage in 1840 , her husband , prince albert , concerned himself with a reorganisation of the household offices and staff , and with the design faults of the palace . the problems were all rec ##ti ##fied by the close of 1840 . however , the builders were to return within the decade . [SEP]\n",
            "I1012 15:05:12.176275 140273920317312 run_squad.py:436] tokens: [CLS] what was the problem with the palace ' s chimneys ? [SEP] buckingham palace finally became the principal royal residence in 1837 , on the accession of queen victoria , who was the first monarch to reside there ; her predecessor william iv had died before its completion . while the state rooms were a riot of gil ##t and colour , the nec ##ess ##ities of the new palace were somewhat less luxurious . for one thing , it was reported the chimneys smoked so much that the fires had to be allowed to die down , and consequently the court shivered in icy mag ##ni ##fi ##cence . ventilation was so bad that the interior smelled , and when a decision was taken to install gas lamps , there was a serious worry about the build - up of gas on the lower floors . it was also said that staff were lax and lazy and the palace was dirty . following the queen ' s marriage in 1840 , her husband , prince albert , concerned himself with a reorganisation of the household offices and staff , and with the design faults of the palace . the problems were all rec ##ti ##fied by the close of 1840 . however , the builders were to return within the decade . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:9 23:9 24:10 25:11 26:12 27:13 28:14 29:15 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:23 40:24 41:25 42:26 43:27 44:28 45:29 46:30 47:31 48:32 49:32 50:33 51:34 52:35 53:36 54:37 55:38 56:39 57:40 58:41 59:41 60:42 61:43 62:43 63:44 64:45 65:45 66:45 67:46 68:47 69:48 70:49 71:50 72:51 73:52 74:53 75:53 76:54 77:55 78:56 79:56 80:57 81:58 82:59 83:60 84:61 85:62 86:63 87:64 88:65 89:66 90:67 91:68 92:69 93:70 94:71 95:72 96:73 97:74 98:74 99:75 100:76 101:77 102:78 103:79 104:80 105:81 106:82 107:82 108:82 109:82 110:82 111:83 112:84 113:85 114:86 115:87 116:88 117:89 118:90 119:90 120:91 121:92 122:93 123:94 124:95 125:96 126:97 127:98 128:99 129:100 130:100 131:101 132:102 133:103 134:104 135:105 136:106 137:107 138:108 139:108 140:108 141:109 142:110 143:111 144:112 145:113 146:114 147:114 148:115 149:116 150:117 151:118 152:119 153:120 154:121 155:122 156:123 157:124 158:125 159:126 160:127 161:128 162:129 163:129 164:130 165:131 166:132 167:132 168:132 169:133 170:134 171:135 172:135 173:136 174:137 175:137 176:138 177:139 178:139 179:140 180:141 181:142 182:143 183:144 184:145 185:146 186:147 187:148 188:149 189:150 190:150 191:151 192:152 193:153 194:154 195:155 196:156 197:157 198:158 199:158 200:159 201:160 202:161 203:162 204:163 205:163 206:163 207:164 208:165 209:166 210:167 211:168 212:168 213:169 214:169 215:170 216:171 217:172 218:173 219:174 220:175 221:176 222:177 223:177\n",
            "I1012 15:05:12.266993 140273920317312 run_squad.py:438] token_to_orig_map: 13:0 14:1 15:2 16:3 17:4 18:5 19:6 20:7 21:8 22:9 23:9 24:10 25:11 26:12 27:13 28:14 29:15 30:15 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:23 40:24 41:25 42:26 43:27 44:28 45:29 46:30 47:31 48:32 49:32 50:33 51:34 52:35 53:36 54:37 55:38 56:39 57:40 58:41 59:41 60:42 61:43 62:43 63:44 64:45 65:45 66:45 67:46 68:47 69:48 70:49 71:50 72:51 73:52 74:53 75:53 76:54 77:55 78:56 79:56 80:57 81:58 82:59 83:60 84:61 85:62 86:63 87:64 88:65 89:66 90:67 91:68 92:69 93:70 94:71 95:72 96:73 97:74 98:74 99:75 100:76 101:77 102:78 103:79 104:80 105:81 106:82 107:82 108:82 109:82 110:82 111:83 112:84 113:85 114:86 115:87 116:88 117:89 118:90 119:90 120:91 121:92 122:93 123:94 124:95 125:96 126:97 127:98 128:99 129:100 130:100 131:101 132:102 133:103 134:104 135:105 136:106 137:107 138:108 139:108 140:108 141:109 142:110 143:111 144:112 145:113 146:114 147:114 148:115 149:116 150:117 151:118 152:119 153:120 154:121 155:122 156:123 157:124 158:125 159:126 160:127 161:128 162:129 163:129 164:130 165:131 166:132 167:132 168:132 169:133 170:134 171:135 172:135 173:136 174:137 175:137 176:138 177:139 178:139 179:140 180:141 181:142 182:143 183:144 184:145 185:146 186:147 187:148 188:149 189:150 190:150 191:151 192:152 193:153 194:154 195:155 196:156 197:157 198:158 199:158 200:159 201:160 202:161 203:162 204:163 205:163 206:163 207:164 208:165 209:166 210:167 211:168 212:168 213:169 214:169 215:170 216:171 217:172 218:173 219:174 220:175 221:176 222:177 223:177\n",
            "INFO:tensorflow:token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True 216:True 217:True 218:True 219:True 220:True 221:True 222:True 223:True\n",
            "I1012 15:05:12.267416 140273920317312 run_squad.py:440] token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True 216:True 217:True 218:True 219:True 220:True 221:True 222:True 223:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2001 1996 3291 2007 1996 4186 1005 1055 28885 1029 102 17836 4186 2633 2150 1996 4054 2548 5039 1999 9713 1010 2006 1996 16993 1997 3035 3848 1010 2040 2001 1996 2034 11590 2000 13960 2045 1025 2014 8646 2520 4921 2018 2351 2077 2049 6503 1012 2096 1996 2110 4734 2020 1037 11421 1997 13097 2102 1998 6120 1010 1996 26785 7971 6447 1997 1996 2047 4186 2020 5399 2625 20783 1012 2005 2028 2518 1010 2009 2001 2988 1996 28885 20482 2061 2172 2008 1996 8769 2018 2000 2022 3039 2000 3280 2091 1010 1998 8821 1996 2457 13927 1999 13580 23848 3490 8873 29320 1012 19536 2001 2061 2919 2008 1996 4592 9557 1010 1998 2043 1037 3247 2001 2579 2000 16500 3806 14186 1010 2045 2001 1037 3809 4737 2055 1996 3857 1011 2039 1997 3806 2006 1996 2896 8158 1012 2009 2001 2036 2056 2008 3095 2020 27327 1998 13971 1998 1996 4186 2001 6530 1012 2206 1996 3035 1005 1055 3510 1999 8905 1010 2014 3129 1010 3159 4789 1010 4986 2370 2007 1037 24934 1997 1996 4398 4822 1998 3095 1010 1998 2007 1996 2640 19399 1997 1996 4186 1012 1996 3471 2020 2035 28667 3775 10451 2011 1996 2485 1997 8905 1012 2174 1010 1996 16472 2020 2000 2709 2306 1996 5476 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.268200 140273920317312 run_squad.py:442] input_ids: 101 2054 2001 1996 3291 2007 1996 4186 1005 1055 28885 1029 102 17836 4186 2633 2150 1996 4054 2548 5039 1999 9713 1010 2006 1996 16993 1997 3035 3848 1010 2040 2001 1996 2034 11590 2000 13960 2045 1025 2014 8646 2520 4921 2018 2351 2077 2049 6503 1012 2096 1996 2110 4734 2020 1037 11421 1997 13097 2102 1998 6120 1010 1996 26785 7971 6447 1997 1996 2047 4186 2020 5399 2625 20783 1012 2005 2028 2518 1010 2009 2001 2988 1996 28885 20482 2061 2172 2008 1996 8769 2018 2000 2022 3039 2000 3280 2091 1010 1998 8821 1996 2457 13927 1999 13580 23848 3490 8873 29320 1012 19536 2001 2061 2919 2008 1996 4592 9557 1010 1998 2043 1037 3247 2001 2579 2000 16500 3806 14186 1010 2045 2001 1037 3809 4737 2055 1996 3857 1011 2039 1997 3806 2006 1996 2896 8158 1012 2009 2001 2036 2056 2008 3095 2020 27327 1998 13971 1998 1996 4186 2001 6530 1012 2206 1996 3035 1005 1055 3510 1999 8905 1010 2014 3129 1010 3159 4789 1010 4986 2370 2007 1037 24934 1997 1996 4398 4822 1998 3095 1010 1998 2007 1996 2640 19399 1997 1996 4186 1012 1996 3471 2020 2035 28667 3775 10451 2011 1996 2485 1997 8905 1012 2174 1010 1996 16472 2020 2000 2709 2306 1996 5476 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.268532 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.268812 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 83\n",
            "I1012 15:05:12.268958 140273920317312 run_squad.py:451] start_position: 83\n",
            "INFO:tensorflow:end_position: 85\n",
            "I1012 15:05:12.269072 140273920317312 run_squad.py:452] end_position: 85\n",
            "INFO:tensorflow:answer: the chimneys smoked\n",
            "I1012 15:05:12.269203 140273920317312 run_squad.py:454] answer: the chimneys smoked\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.274414 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000011\n",
            "I1012 15:05:12.274614 140273920317312 run_squad.py:432] unique_id: 1000000011\n",
            "INFO:tensorflow:example_index: 11\n",
            "I1012 15:05:12.274678 140273920317312 run_squad.py:433] example_index: 11\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.274730 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] who has noted that binding precedent did not exist when the constitution was written ? [SEP] as federal judge alex ko ##zin ##ski has pointed out , binding precedent as we know it today simply did not exist at the time the constitution was framed . judicial decisions were not consistently , accurately , and faithful ##ly reported on both sides of the atlantic ( reporters often simply re ##wr ##ote or failed to publish decisions which they disliked ) , and the united kingdom lacked a coherent court hierarchy prior to the end of the 19th century . furthermore , english judges in the eighteenth century sub ##scribe ##d to now - obsolete natural law theories of law , by which law was believed to have an existence independent of what individual judges said . judges saw themselves as merely declaring the law which had always theoretically existed , and not as making the law . therefore , a judge could reject another judge ' s opinion as simply an incorrect statement of the law , in the way that scientists regularly reject each other ' s conclusions as incorrect statements of the laws of science . [SEP]\n",
            "I1012 15:05:12.274834 140273920317312 run_squad.py:436] tokens: [CLS] who has noted that binding precedent did not exist when the constitution was written ? [SEP] as federal judge alex ko ##zin ##ski has pointed out , binding precedent as we know it today simply did not exist at the time the constitution was framed . judicial decisions were not consistently , accurately , and faithful ##ly reported on both sides of the atlantic ( reporters often simply re ##wr ##ote or failed to publish decisions which they disliked ) , and the united kingdom lacked a coherent court hierarchy prior to the end of the 19th century . furthermore , english judges in the eighteenth century sub ##scribe ##d to now - obsolete natural law theories of law , by which law was believed to have an existence independent of what individual judges said . judges saw themselves as merely declaring the law which had always theoretically existed , and not as making the law . therefore , a judge could reject another judge ' s opinion as simply an incorrect statement of the law , in the way that scientists regularly reject each other ' s conclusions as incorrect statements of the laws of science . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 17:0 18:1 19:2 20:3 21:4 22:4 23:4 24:5 25:6 26:7 27:7 28:8 29:9 30:10 31:11 32:12 33:13 34:14 35:15 36:16 37:17 38:18 39:19 40:20 41:21 42:22 43:23 44:24 45:25 46:25 47:26 48:27 49:28 50:29 51:30 52:30 53:31 54:31 55:32 56:33 57:33 58:34 59:35 60:36 61:37 62:38 63:39 64:40 65:41 66:41 67:42 68:43 69:44 70:44 71:44 72:45 73:46 74:47 75:48 76:49 77:50 78:51 79:52 80:52 81:52 82:53 83:54 84:55 85:56 86:57 87:58 88:59 89:60 90:61 91:62 92:63 93:64 94:65 95:66 96:67 97:68 98:69 99:69 100:70 101:70 102:71 103:72 104:73 105:74 106:75 107:76 108:77 109:77 110:77 111:78 112:79 113:79 114:79 115:80 116:81 117:82 118:83 119:84 120:84 121:85 122:86 123:87 124:88 125:89 126:90 127:91 128:92 129:93 130:94 131:95 132:96 133:97 134:98 135:99 136:99 137:100 138:101 139:102 140:103 141:104 142:105 143:106 144:107 145:108 146:109 147:110 148:111 149:112 150:112 151:113 152:114 153:115 154:116 155:117 156:118 157:118 158:119 159:119 160:120 161:121 162:122 163:123 164:124 165:125 166:125 167:125 168:126 169:127 170:128 171:129 172:130 173:131 174:132 175:133 176:134 177:134 178:135 179:136 180:137 181:138 182:139 183:140 184:141 185:142 186:143 187:143 188:143 189:144 190:145 191:146 192:147 193:148 194:149 195:150 196:151 197:152 198:152\n",
            "I1012 15:05:12.274954 140273920317312 run_squad.py:438] token_to_orig_map: 17:0 18:1 19:2 20:3 21:4 22:4 23:4 24:5 25:6 26:7 27:7 28:8 29:9 30:10 31:11 32:12 33:13 34:14 35:15 36:16 37:17 38:18 39:19 40:20 41:21 42:22 43:23 44:24 45:25 46:25 47:26 48:27 49:28 50:29 51:30 52:30 53:31 54:31 55:32 56:33 57:33 58:34 59:35 60:36 61:37 62:38 63:39 64:40 65:41 66:41 67:42 68:43 69:44 70:44 71:44 72:45 73:46 74:47 75:48 76:49 77:50 78:51 79:52 80:52 81:52 82:53 83:54 84:55 85:56 86:57 87:58 88:59 89:60 90:61 91:62 92:63 93:64 94:65 95:66 96:67 97:68 98:69 99:69 100:70 101:70 102:71 103:72 104:73 105:74 106:75 107:76 108:77 109:77 110:77 111:78 112:79 113:79 114:79 115:80 116:81 117:82 118:83 119:84 120:84 121:85 122:86 123:87 124:88 125:89 126:90 127:91 128:92 129:93 130:94 131:95 132:96 133:97 134:98 135:99 136:99 137:100 138:101 139:102 140:103 141:104 142:105 143:106 144:107 145:108 146:109 147:110 148:111 149:112 150:112 151:113 152:114 153:115 154:116 155:117 156:118 157:118 158:119 159:119 160:120 161:121 162:122 163:123 164:124 165:125 166:125 167:125 168:126 169:127 170:128 171:129 172:130 173:131 174:132 175:133 176:134 177:134 178:135 179:136 180:137 181:138 182:139 183:140 184:141 185:142 186:143 187:143 188:143 189:144 190:145 191:146 192:147 193:148 194:149 195:150 196:151 197:152 198:152\n",
            "INFO:tensorflow:token_is_max_context: 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True\n",
            "I1012 15:05:12.275061 140273920317312 run_squad.py:440] token_is_max_context: 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True\n",
            "INFO:tensorflow:input_ids: 101 2040 2038 3264 2008 8031 20056 2106 2025 4839 2043 1996 4552 2001 2517 1029 102 2004 2976 3648 4074 12849 17168 5488 2038 4197 2041 1010 8031 20056 2004 2057 2113 2009 2651 3432 2106 2025 4839 2012 1996 2051 1996 4552 2001 10366 1012 8268 6567 2020 2025 10862 1010 14125 1010 1998 11633 2135 2988 2006 2119 3903 1997 1996 4448 1006 12060 2411 3432 2128 13088 12184 2030 3478 2000 10172 6567 2029 2027 18966 1007 1010 1998 1996 2142 2983 10858 1037 18920 2457 12571 3188 2000 1996 2203 1997 1996 3708 2301 1012 7297 1010 2394 6794 1999 1996 12965 2301 4942 29234 2094 2000 2085 1011 15832 3019 2375 8106 1997 2375 1010 2011 2029 2375 2001 3373 2000 2031 2019 4598 2981 1997 2054 3265 6794 2056 1012 6794 2387 3209 2004 6414 13752 1996 2375 2029 2018 2467 22634 5839 1010 1998 2025 2004 2437 1996 2375 1012 3568 1010 1037 3648 2071 15454 2178 3648 1005 1055 5448 2004 3432 2019 16542 4861 1997 1996 2375 1010 1999 1996 2126 2008 6529 5570 15454 2169 2060 1005 1055 15306 2004 16542 8635 1997 1996 4277 1997 2671 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.275235 140273920317312 run_squad.py:442] input_ids: 101 2040 2038 3264 2008 8031 20056 2106 2025 4839 2043 1996 4552 2001 2517 1029 102 2004 2976 3648 4074 12849 17168 5488 2038 4197 2041 1010 8031 20056 2004 2057 2113 2009 2651 3432 2106 2025 4839 2012 1996 2051 1996 4552 2001 10366 1012 8268 6567 2020 2025 10862 1010 14125 1010 1998 11633 2135 2988 2006 2119 3903 1997 1996 4448 1006 12060 2411 3432 2128 13088 12184 2030 3478 2000 10172 6567 2029 2027 18966 1007 1010 1998 1996 2142 2983 10858 1037 18920 2457 12571 3188 2000 1996 2203 1997 1996 3708 2301 1012 7297 1010 2394 6794 1999 1996 12965 2301 4942 29234 2094 2000 2085 1011 15832 3019 2375 8106 1997 2375 1010 2011 2029 2375 2001 3373 2000 2031 2019 4598 2981 1997 2054 3265 6794 2056 1012 6794 2387 3209 2004 6414 13752 1996 2375 2029 2018 2467 22634 5839 1010 1998 2025 2004 2437 1996 2375 1012 3568 1010 1037 3648 2071 15454 2178 3648 1005 1055 5448 2004 3432 2019 16542 4861 1997 1996 2375 1010 1999 1996 2126 2008 6529 5570 15454 2169 2060 1005 1055 15306 2004 16542 8635 1997 1996 4277 1997 2671 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.275370 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.275491 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 18\n",
            "I1012 15:05:12.275549 140273920317312 run_squad.py:451] start_position: 18\n",
            "INFO:tensorflow:end_position: 23\n",
            "I1012 15:05:12.275597 140273920317312 run_squad.py:452] end_position: 23\n",
            "INFO:tensorflow:answer: federal judge alex ko ##zin ##ski\n",
            "I1012 15:05:12.275644 140273920317312 run_squad.py:454] answer: federal judge alex ko ##zin ##ski\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.278917 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000012\n",
            "I1012 15:05:12.279131 140273920317312 run_squad.py:432] unique_id: 1000000012\n",
            "INFO:tensorflow:example_index: 12\n",
            "I1012 15:05:12.279195 140273920317312 run_squad.py:433] example_index: 12\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.279246 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what short ##coming was noticeable , from the start , for wesley clark ? [SEP] in september 2003 , retired four - star general wesley clark announced his intention to run in the presidential primary election for the democratic party nomination . his campaign focused on themes of leadership and patriot ##ism ; early campaign ads relied heavily on biography . his late start left him with relatively few detailed policy proposals . this weakness was apparent in his first few debates , although he soon presented a range of position papers , including a major tax - relief plan . nevertheless , the democrats did not flock to support his campaign . [SEP]\n",
            "I1012 15:05:12.279337 140273920317312 run_squad.py:436] tokens: [CLS] what short ##coming was noticeable , from the start , for wesley clark ? [SEP] in september 2003 , retired four - star general wesley clark announced his intention to run in the presidential primary election for the democratic party nomination . his campaign focused on themes of leadership and patriot ##ism ; early campaign ads relied heavily on biography . his late start left him with relatively few detailed policy proposals . this weakness was apparent in his first few debates , although he soon presented a range of position papers , including a major tax - relief plan . nevertheless , the democrats did not flock to support his campaign . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 16:0 17:1 18:2 19:2 20:3 21:4 22:4 23:4 24:5 25:6 26:7 27:8 28:9 29:10 30:11 31:12 32:13 33:14 34:15 35:16 36:17 37:18 38:19 39:20 40:21 41:22 42:22 43:23 44:24 45:25 46:26 47:27 48:28 49:29 50:30 51:31 52:31 53:31 54:32 55:33 56:34 57:35 58:36 59:37 60:38 61:38 62:39 63:40 64:41 65:42 66:43 67:44 68:45 69:46 70:47 71:48 72:49 73:49 74:50 75:51 76:52 77:53 78:54 79:55 80:56 81:57 82:58 83:58 84:59 85:60 86:61 87:62 88:63 89:64 90:65 91:66 92:67 93:67 94:68 95:69 96:70 97:71 98:71 99:71 100:72 101:72 102:73 103:73 104:74 105:75 106:76 107:77 108:78 109:79 110:80 111:81 112:82 113:82\n",
            "I1012 15:05:12.279431 140273920317312 run_squad.py:438] token_to_orig_map: 16:0 17:1 18:2 19:2 20:3 21:4 22:4 23:4 24:5 25:6 26:7 27:8 28:9 29:10 30:11 31:12 32:13 33:14 34:15 35:16 36:17 37:18 38:19 39:20 40:21 41:22 42:22 43:23 44:24 45:25 46:26 47:27 48:28 49:29 50:30 51:31 52:31 53:31 54:32 55:33 56:34 57:35 58:36 59:37 60:38 61:38 62:39 63:40 64:41 65:42 66:43 67:44 68:45 69:46 70:47 71:48 72:49 73:49 74:50 75:51 76:52 77:53 78:54 79:55 80:56 81:57 82:58 83:58 84:59 85:60 86:61 87:62 88:63 89:64 90:65 91:66 92:67 93:67 94:68 95:69 96:70 97:71 98:71 99:71 100:72 101:72 102:73 103:73 104:74 105:75 106:76 107:77 108:78 109:79 110:80 111:81 112:82 113:82\n",
            "INFO:tensorflow:token_is_max_context: 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True\n",
            "I1012 15:05:12.370772 140273920317312 run_squad.py:440] token_is_max_context: 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2460 18935 2001 17725 1010 2013 1996 2707 1010 2005 11482 5215 1029 102 1999 2244 2494 1010 3394 2176 1011 2732 2236 11482 5215 2623 2010 6808 2000 2448 1999 1996 4883 3078 2602 2005 1996 3537 2283 6488 1012 2010 3049 4208 2006 6991 1997 4105 1998 16419 2964 1025 2220 3049 14997 13538 4600 2006 8308 1012 2010 2397 2707 2187 2032 2007 4659 2261 6851 3343 10340 1012 2023 11251 2001 6835 1999 2010 2034 2261 14379 1010 2348 2002 2574 3591 1037 2846 1997 2597 4981 1010 2164 1037 2350 4171 1011 4335 2933 1012 6600 1010 1996 8037 2106 2025 19311 2000 2490 2010 3049 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.371353 140273920317312 run_squad.py:442] input_ids: 101 2054 2460 18935 2001 17725 1010 2013 1996 2707 1010 2005 11482 5215 1029 102 1999 2244 2494 1010 3394 2176 1011 2732 2236 11482 5215 2623 2010 6808 2000 2448 1999 1996 4883 3078 2602 2005 1996 3537 2283 6488 1012 2010 3049 4208 2006 6991 1997 4105 1998 16419 2964 1025 2220 3049 14997 13538 4600 2006 8308 1012 2010 2397 2707 2187 2032 2007 4659 2261 6851 3343 10340 1012 2023 11251 2001 6835 1999 2010 2034 2261 14379 1010 2348 2002 2574 3591 1037 2846 1997 2597 4981 1010 2164 1037 2350 4171 1011 4335 2933 1012 6600 1010 1996 8037 2106 2025 19311 2000 2490 2010 3049 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.371708 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.371989 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 69\n",
            "I1012 15:05:12.372155 140273920317312 run_squad.py:451] start_position: 69\n",
            "INFO:tensorflow:end_position: 72\n",
            "I1012 15:05:12.372269 140273920317312 run_squad.py:452] end_position: 72\n",
            "INFO:tensorflow:answer: few detailed policy proposals\n",
            "I1012 15:05:12.372374 140273920317312 run_squad.py:454] answer: few detailed policy proposals\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.376217 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000013\n",
            "I1012 15:05:12.376411 140273920317312 run_squad.py:432] unique_id: 1000000013\n",
            "INFO:tensorflow:example_index: 13\n",
            "I1012 15:05:12.376497 140273920317312 run_squad.py:433] example_index: 13\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.376575 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] the digest ##ive chambers of the ct ##eno ##ph ##ora and the cn ##ida ##ria serve as what ? [SEP] among the other ph ##yla , the ct ##eno ##ph ##ora and the cn ##ida ##ria , which includes sea an ##emon ##es , coral ##s , and jelly ##fish , are radial ##ly symmetric and have digest ##ive chambers with a single opening , which serves as both the mouth and the an ##us . both have distinct tissues , but they are not organized into organs . there are only two main ge ##rm layers , the ec ##to ##der ##m and end ##oder ##m , with only scattered cells between them . as such , these animals are sometimes called dip ##lo ##bla ##stic . the tiny pl ##aco ##zo ##ans are similar , but they do not have a permanent digest ##ive chamber . [SEP]\n",
            "I1012 15:05:12.376718 140273920317312 run_squad.py:436] tokens: [CLS] the digest ##ive chambers of the ct ##eno ##ph ##ora and the cn ##ida ##ria serve as what ? [SEP] among the other ph ##yla , the ct ##eno ##ph ##ora and the cn ##ida ##ria , which includes sea an ##emon ##es , coral ##s , and jelly ##fish , are radial ##ly symmetric and have digest ##ive chambers with a single opening , which serves as both the mouth and the an ##us . both have distinct tissues , but they are not organized into organs . there are only two main ge ##rm layers , the ec ##to ##der ##m and end ##oder ##m , with only scattered cells between them . as such , these animals are sometimes called dip ##lo ##bla ##stic . the tiny pl ##aco ##zo ##ans are similar , but they do not have a permanent digest ##ive chamber . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 21:0 22:1 23:2 24:3 25:3 26:3 27:4 28:5 29:5 30:5 31:5 32:6 33:7 34:8 35:8 36:8 37:8 38:9 39:10 40:11 41:12 42:12 43:12 44:12 45:13 46:13 47:13 48:14 49:15 50:15 51:15 52:16 53:17 54:17 55:18 56:19 57:20 58:21 59:21 60:22 61:23 62:24 63:25 64:26 65:26 66:27 67:28 68:29 69:30 70:31 71:32 72:33 73:34 74:35 75:35 76:35 77:36 78:37 79:38 80:39 81:39 82:40 83:41 84:42 85:43 86:44 87:45 88:46 89:46 90:47 91:48 92:49 93:50 94:51 95:52 96:52 97:53 98:53 99:54 100:55 101:55 102:55 103:55 104:56 105:57 106:57 107:57 108:57 109:58 110:59 111:60 112:61 113:62 114:63 115:63 116:64 117:65 118:65 119:66 120:67 121:68 122:69 123:70 124:71 125:71 126:71 127:71 128:71 129:72 130:73 131:74 132:74 133:74 134:74 135:75 136:76 137:76 138:77 139:78 140:79 141:80 142:81 143:82 144:83 145:84 146:84 147:85 148:85\n",
            "I1012 15:05:12.376864 140273920317312 run_squad.py:438] token_to_orig_map: 21:0 22:1 23:2 24:3 25:3 26:3 27:4 28:5 29:5 30:5 31:5 32:6 33:7 34:8 35:8 36:8 37:8 38:9 39:10 40:11 41:12 42:12 43:12 44:12 45:13 46:13 47:13 48:14 49:15 50:15 51:15 52:16 53:17 54:17 55:18 56:19 57:20 58:21 59:21 60:22 61:23 62:24 63:25 64:26 65:26 66:27 67:28 68:29 69:30 70:31 71:32 72:33 73:34 74:35 75:35 76:35 77:36 78:37 79:38 80:39 81:39 82:40 83:41 84:42 85:43 86:44 87:45 88:46 89:46 90:47 91:48 92:49 93:50 94:51 95:52 96:52 97:53 98:53 99:54 100:55 101:55 102:55 103:55 104:56 105:57 106:57 107:57 108:57 109:58 110:59 111:60 112:61 113:62 114:63 115:63 116:64 117:65 118:65 119:66 120:67 121:68 122:69 123:70 124:71 125:71 126:71 127:71 128:71 129:72 130:73 131:74 132:74 133:74 134:74 135:75 136:76 137:76 138:77 139:78 140:79 141:80 142:81 143:82 144:83 145:84 146:84 147:85 148:85\n",
            "INFO:tensorflow:token_is_max_context: 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True\n",
            "I1012 15:05:12.377002 140273920317312 run_squad.py:440] token_is_max_context: 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True\n",
            "INFO:tensorflow:input_ids: 101 1996 17886 3512 8477 1997 1996 14931 16515 8458 6525 1998 1996 27166 8524 4360 3710 2004 2054 1029 102 2426 1996 2060 6887 23943 1010 1996 14931 16515 8458 6525 1998 1996 27166 8524 4360 1010 2029 2950 2712 2019 26941 2229 1010 11034 2015 1010 1998 20919 7529 1010 2024 15255 2135 19490 1998 2031 17886 3512 8477 2007 1037 2309 3098 1010 2029 4240 2004 2119 1996 2677 1998 1996 2019 2271 1012 2119 2031 5664 14095 1010 2021 2027 2024 2025 4114 2046 11595 1012 2045 2024 2069 2048 2364 16216 10867 9014 1010 1996 14925 3406 4063 2213 1998 2203 27381 2213 1010 2007 2069 7932 4442 2090 2068 1012 2004 2107 1010 2122 4176 2024 2823 2170 16510 4135 28522 10074 1012 1996 4714 20228 22684 6844 6962 2024 2714 1010 2021 2027 2079 2025 2031 1037 4568 17886 3512 4574 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.377204 140273920317312 run_squad.py:442] input_ids: 101 1996 17886 3512 8477 1997 1996 14931 16515 8458 6525 1998 1996 27166 8524 4360 3710 2004 2054 1029 102 2426 1996 2060 6887 23943 1010 1996 14931 16515 8458 6525 1998 1996 27166 8524 4360 1010 2029 2950 2712 2019 26941 2229 1010 11034 2015 1010 1998 20919 7529 1010 2024 15255 2135 19490 1998 2031 17886 3512 8477 2007 1037 2309 3098 1010 2029 4240 2004 2119 1996 2677 1998 1996 2019 2271 1012 2119 2031 5664 14095 1010 2021 2027 2024 2025 4114 2046 11595 1012 2045 2024 2069 2048 2364 16216 10867 9014 1010 1996 14925 3406 4063 2213 1998 2203 27381 2213 1010 2007 2069 7932 4442 2090 2068 1012 2004 2107 1010 2122 4176 2024 2823 2170 16510 4135 28522 10074 1012 1996 4714 20228 22684 6844 6962 2024 2714 1010 2021 2027 2079 2025 2031 1037 4568 17886 3512 4574 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.377380 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.377549 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 69\n",
            "I1012 15:05:12.377637 140273920317312 run_squad.py:451] start_position: 69\n",
            "INFO:tensorflow:end_position: 75\n",
            "I1012 15:05:12.377709 140273920317312 run_squad.py:452] end_position: 75\n",
            "INFO:tensorflow:answer: both the mouth and the an ##us\n",
            "I1012 15:05:12.377778 140273920317312 run_squad.py:454] answer: both the mouth and the an ##us\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.379907 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000014\n",
            "I1012 15:05:12.380082 140273920317312 run_squad.py:432] unique_id: 1000000014\n",
            "INFO:tensorflow:example_index: 14\n",
            "I1012 15:05:12.380185 140273920317312 run_squad.py:433] example_index: 14\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.380263 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] when did buddhism leave zhejiang ? [SEP] in mid - 2015 the government of zhejiang recognised folk religion as \" civil religion \" beginning the registration of more than twenty thousand folk religious associations . buddhism has an important presence since its arrival in zhejiang 1 , 800 years ago . [SEP]\n",
            "I1012 15:05:12.380365 140273920317312 run_squad.py:436] tokens: [CLS] when did buddhism leave zhejiang ? [SEP] in mid - 2015 the government of zhejiang recognised folk religion as \" civil religion \" beginning the registration of more than twenty thousand folk religious associations . buddhism has an important presence since its arrival in zhejiang 1 , 800 years ago . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 8:0 9:1 10:1 11:1 12:2 13:3 14:4 15:5 16:6 17:7 18:8 19:9 20:10 21:10 22:11 23:11 24:12 25:13 26:14 27:15 28:16 29:17 30:18 31:19 32:20 33:21 34:22 35:22 36:23 37:24 38:25 39:26 40:27 41:28 42:29 43:30 44:31 45:32 46:33 47:33 48:33 49:34 50:35 51:35\n",
            "I1012 15:05:12.380476 140273920317312 run_squad.py:438] token_to_orig_map: 8:0 9:1 10:1 11:1 12:2 13:3 14:4 15:5 16:6 17:7 18:8 19:9 20:10 21:10 22:11 23:11 24:12 25:13 26:14 27:15 28:16 29:17 30:18 31:19 32:20 33:21 34:22 35:22 36:23 37:24 38:25 39:26 40:27 41:28 42:29 43:30 44:31 45:32 46:33 47:33 48:33 49:34 50:35 51:35\n",
            "INFO:tensorflow:token_is_max_context: 8:True 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True\n",
            "I1012 15:05:12.380578 140273920317312 run_squad.py:440] token_is_max_context: 8:True 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True\n",
            "INFO:tensorflow:input_ids: 101 2043 2106 11388 2681 26805 1029 102 1999 3054 1011 2325 1996 2231 1997 26805 7843 5154 4676 2004 1000 2942 4676 1000 2927 1996 8819 1997 2062 2084 3174 4595 5154 3412 8924 1012 11388 2038 2019 2590 3739 2144 2049 5508 1999 26805 1015 1010 5385 2086 3283 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.380770 140273920317312 run_squad.py:442] input_ids: 101 2043 2106 11388 2681 26805 1029 102 1999 3054 1011 2325 1996 2231 1997 26805 7843 5154 4676 2004 1000 2942 4676 1000 2927 1996 8819 1997 2062 2084 3174 4595 5154 3412 8924 1012 11388 2038 2019 2590 3739 2144 2049 5508 1999 26805 1015 1010 5385 2086 3283 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.380942 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.475061 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:12.475260 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.485572 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000015\n",
            "I1012 15:05:12.485798 140273920317312 run_squad.py:432] unique_id: 1000000015\n",
            "INFO:tensorflow:example_index: 15\n",
            "I1012 15:05:12.485867 140273920317312 run_squad.py:433] example_index: 15\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.485920 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] who embraced his family according to the new testament ? [SEP] the ha ##gio ##graphy of mary and the holy family can be contrasted with other material in the gospels . these references include an incident which can be interpreted as jesus rejecting his family in the new testament : \" and his mother and his brothers arrived , and standing outside , they sent in a message asking for him . . . and looking at those who sat in a circle around him , jesus said , ' these are my mother and my brothers . whoever does the will of god is my brother , and sister , and mother ' . \" [ 3 : 31 - 35 ] other verses suggest a conflict between jesus and his family , including an attempt to have jesus restrained because \" he is out of his mind \" , and the famous quote : \" a prophet is not without honor except in his own town , among his relatives and in his own home . \" a leading biblical scholar commented : \" there are clear signs not only that jesus ' s family rejected his message during his public ministry but that he in turn spur ##ned them publicly \" . [SEP]\n",
            "I1012 15:05:12.486033 140273920317312 run_squad.py:436] tokens: [CLS] who embraced his family according to the new testament ? [SEP] the ha ##gio ##graphy of mary and the holy family can be contrasted with other material in the gospels . these references include an incident which can be interpreted as jesus rejecting his family in the new testament : \" and his mother and his brothers arrived , and standing outside , they sent in a message asking for him . . . and looking at those who sat in a circle around him , jesus said , ' these are my mother and my brothers . whoever does the will of god is my brother , and sister , and mother ' . \" [ 3 : 31 - 35 ] other verses suggest a conflict between jesus and his family , including an attempt to have jesus restrained because \" he is out of his mind \" , and the famous quote : \" a prophet is not without honor except in his own town , among his relatives and in his own home . \" a leading biblical scholar commented : \" there are clear signs not only that jesus ' s family rejected his message during his public ministry but that he in turn spur ##ned them publicly \" . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 12:0 13:1 14:1 15:1 16:2 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:13 28:14 29:15 30:16 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:27 43:28 44:29 45:30 46:31 47:32 48:33 49:34 50:34 51:35 52:35 53:36 54:37 55:38 56:39 57:40 58:41 59:41 60:42 61:43 62:44 63:44 64:45 65:46 66:47 67:48 68:49 69:50 70:51 71:52 72:53 73:53 74:53 75:54 76:55 77:56 78:57 79:58 80:59 81:60 82:61 83:62 84:63 85:64 86:64 87:65 88:66 89:66 90:67 91:67 92:68 93:69 94:70 95:71 96:72 97:73 98:73 99:74 100:75 101:76 102:77 103:78 104:79 105:80 106:81 107:82 108:82 109:83 110:84 111:84 112:85 113:86 114:86 115:86 116:86 117:86 118:86 119:86 120:86 121:86 122:86 123:86 124:87 125:88 126:89 127:90 128:91 129:92 130:93 131:94 132:95 133:96 134:96 135:97 136:98 137:99 138:100 139:101 140:102 141:103 142:104 143:105 144:105 145:106 146:107 147:108 148:109 149:110 150:110 151:110 152:111 153:112 154:113 155:114 156:114 157:115 158:115 159:116 160:117 161:118 162:119 163:120 164:121 165:122 166:123 167:124 168:125 169:125 170:126 171:127 172:128 173:129 174:130 175:131 176:132 177:133 178:133 179:133 180:134 181:135 182:136 183:137 184:138 185:138 186:139 187:139 188:140 189:141 190:142 191:143 192:144 193:145 194:146 195:146 196:146 197:147 198:148 199:149 200:150 201:151 202:152 203:153 204:154 205:155 206:156 207:157 208:158 209:159 210:160 211:160 212:161 213:162 214:162 215:162\n",
            "I1012 15:05:12.486207 140273920317312 run_squad.py:438] token_to_orig_map: 12:0 13:1 14:1 15:1 16:2 17:3 18:4 19:5 20:6 21:7 22:8 23:9 24:10 25:11 26:12 27:13 28:14 29:15 30:16 31:16 32:17 33:18 34:19 35:20 36:21 37:22 38:23 39:24 40:25 41:26 42:27 43:28 44:29 45:30 46:31 47:32 48:33 49:34 50:34 51:35 52:35 53:36 54:37 55:38 56:39 57:40 58:41 59:41 60:42 61:43 62:44 63:44 64:45 65:46 66:47 67:48 68:49 69:50 70:51 71:52 72:53 73:53 74:53 75:54 76:55 77:56 78:57 79:58 80:59 81:60 82:61 83:62 84:63 85:64 86:64 87:65 88:66 89:66 90:67 91:67 92:68 93:69 94:70 95:71 96:72 97:73 98:73 99:74 100:75 101:76 102:77 103:78 104:79 105:80 106:81 107:82 108:82 109:83 110:84 111:84 112:85 113:86 114:86 115:86 116:86 117:86 118:86 119:86 120:86 121:86 122:86 123:86 124:87 125:88 126:89 127:90 128:91 129:92 130:93 131:94 132:95 133:96 134:96 135:97 136:98 137:99 138:100 139:101 140:102 141:103 142:104 143:105 144:105 145:106 146:107 147:108 148:109 149:110 150:110 151:110 152:111 153:112 154:113 155:114 156:114 157:115 158:115 159:116 160:117 161:118 162:119 163:120 164:121 165:122 166:123 167:124 168:125 169:125 170:126 171:127 172:128 173:129 174:130 175:131 176:132 177:133 178:133 179:133 180:134 181:135 182:136 183:137 184:138 185:138 186:139 187:139 188:140 189:141 190:142 191:143 192:144 193:145 194:146 195:146 196:146 197:147 198:148 199:149 200:150 201:151 202:152 203:153 204:154 205:155 206:156 207:157 208:158 209:159 210:160 211:160 212:161 213:162 214:162 215:162\n",
            "INFO:tensorflow:token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True\n",
            "I1012 15:05:12.486344 140273920317312 run_squad.py:440] token_is_max_context: 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True 197:True 198:True 199:True 200:True 201:True 202:True 203:True 204:True 205:True 206:True 207:True 208:True 209:True 210:True 211:True 212:True 213:True 214:True 215:True\n",
            "INFO:tensorflow:input_ids: 101 2040 14218 2010 2155 2429 2000 1996 2047 9025 1029 102 1996 5292 11411 12565 1997 2984 1998 1996 4151 2155 2064 2022 22085 2007 2060 3430 1999 1996 24131 1012 2122 7604 2421 2019 5043 2029 2064 2022 10009 2004 4441 21936 2010 2155 1999 1996 2047 9025 1024 1000 1998 2010 2388 1998 2010 3428 3369 1010 1998 3061 2648 1010 2027 2741 1999 1037 4471 4851 2005 2032 1012 1012 1012 1998 2559 2012 2216 2040 2938 1999 1037 4418 2105 2032 1010 4441 2056 1010 1005 2122 2024 2026 2388 1998 2026 3428 1012 9444 2515 1996 2097 1997 2643 2003 2026 2567 1010 1998 2905 1010 1998 2388 1005 1012 1000 1031 1017 1024 2861 1011 3486 1033 2060 11086 6592 1037 4736 2090 4441 1998 2010 2155 1010 2164 2019 3535 2000 2031 4441 19868 2138 1000 2002 2003 2041 1997 2010 2568 1000 1010 1998 1996 3297 14686 1024 1000 1037 12168 2003 2025 2302 3932 3272 1999 2010 2219 2237 1010 2426 2010 9064 1998 1999 2010 2219 2188 1012 1000 1037 2877 10213 6288 7034 1024 1000 2045 2024 3154 5751 2025 2069 2008 4441 1005 1055 2155 5837 2010 4471 2076 2010 2270 3757 2021 2008 2002 1999 2735 12996 7228 2068 7271 1000 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.486507 140273920317312 run_squad.py:442] input_ids: 101 2040 14218 2010 2155 2429 2000 1996 2047 9025 1029 102 1996 5292 11411 12565 1997 2984 1998 1996 4151 2155 2064 2022 22085 2007 2060 3430 1999 1996 24131 1012 2122 7604 2421 2019 5043 2029 2064 2022 10009 2004 4441 21936 2010 2155 1999 1996 2047 9025 1024 1000 1998 2010 2388 1998 2010 3428 3369 1010 1998 3061 2648 1010 2027 2741 1999 1037 4471 4851 2005 2032 1012 1012 1012 1998 2559 2012 2216 2040 2938 1999 1037 4418 2105 2032 1010 4441 2056 1010 1005 2122 2024 2026 2388 1998 2026 3428 1012 9444 2515 1996 2097 1997 2643 2003 2026 2567 1010 1998 2905 1010 1998 2388 1005 1012 1000 1031 1017 1024 2861 1011 3486 1033 2060 11086 6592 1037 4736 2090 4441 1998 2010 2155 1010 2164 2019 3535 2000 2031 4441 19868 2138 1000 2002 2003 2041 1997 2010 2568 1000 1010 1998 1996 3297 14686 1024 1000 1037 12168 2003 2025 2302 3932 3272 1999 2010 2219 2237 1010 2426 2010 9064 1998 1999 2010 2219 2188 1012 1000 1037 2877 10213 6288 7034 1024 1000 2045 2024 3154 5751 2025 2069 2008 4441 1005 1055 2155 5837 2010 4471 2076 2010 2270 3757 2021 2008 2002 1999 2735 12996 7228 2068 7271 1000 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.486635 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.486758 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:12.486815 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.490735 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000016\n",
            "I1012 15:05:12.490931 140273920317312 run_squad.py:432] unique_id: 1000000016\n",
            "INFO:tensorflow:example_index: 16\n",
            "I1012 15:05:12.490992 140273920317312 run_squad.py:433] example_index: 16\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.491044 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] where does a bill go once the president signs it into effect ? [SEP] after the president signs a bill into law ( or congress en ##act ##s it over his veto ) , it is delivered to the office of the federal register ( of ##r ) of the national archives and records administration ( nara ) where it is assigned a law number , and prepared for publication as a slip law . public laws , but not private laws , are also given legal statutory citation by the of ##r . at the end of each session of congress , the slip laws are compiled into bound volumes called the united states statutes at large , and they are known as session laws . the statutes at large present a chronological arrangement of the laws in the exact order that they have been enacted . [SEP]\n",
            "I1012 15:05:12.491157 140273920317312 run_squad.py:436] tokens: [CLS] where does a bill go once the president signs it into effect ? [SEP] after the president signs a bill into law ( or congress en ##act ##s it over his veto ) , it is delivered to the office of the federal register ( of ##r ) of the national archives and records administration ( nara ) where it is assigned a law number , and prepared for publication as a slip law . public laws , but not private laws , are also given legal statutory citation by the of ##r . at the end of each session of congress , the slip laws are compiled into bound volumes called the united states statutes at large , and they are known as session laws . the statutes at large present a chronological arrangement of the laws in the exact order that they have been enacted . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 15:0 16:1 17:2 18:3 19:4 20:5 21:6 22:7 23:8 24:8 25:9 26:10 27:10 28:10 29:11 30:12 31:13 32:14 33:14 34:14 35:15 36:16 37:17 38:18 39:19 40:20 41:21 42:22 43:23 44:24 45:25 46:25 47:25 48:25 49:26 50:27 51:28 52:29 53:30 54:31 55:32 56:33 57:33 58:33 59:34 60:35 61:36 62:37 63:38 64:39 65:40 66:40 67:41 68:42 69:43 70:44 71:45 72:46 73:47 74:48 75:48 76:49 77:50 78:50 79:51 80:52 81:53 82:54 83:54 84:55 85:56 86:57 87:58 88:59 89:60 90:61 91:62 92:63 93:63 94:63 95:64 96:65 97:66 98:67 99:68 100:69 101:70 102:71 103:71 104:72 105:73 106:74 107:75 108:76 109:77 110:78 111:79 112:80 113:81 114:82 115:83 116:84 117:85 118:86 119:86 120:87 121:88 122:89 123:90 124:91 125:92 126:93 127:93 128:94 129:95 130:96 131:97 132:98 133:99 134:100 135:101 136:102 137:103 138:104 139:105 140:106 141:107 142:108 143:109 144:110 145:111 146:112 147:113 148:113\n",
            "I1012 15:05:12.585700 140273920317312 run_squad.py:438] token_to_orig_map: 15:0 16:1 17:2 18:3 19:4 20:5 21:6 22:7 23:8 24:8 25:9 26:10 27:10 28:10 29:11 30:12 31:13 32:14 33:14 34:14 35:15 36:16 37:17 38:18 39:19 40:20 41:21 42:22 43:23 44:24 45:25 46:25 47:25 48:25 49:26 50:27 51:28 52:29 53:30 54:31 55:32 56:33 57:33 58:33 59:34 60:35 61:36 62:37 63:38 64:39 65:40 66:40 67:41 68:42 69:43 70:44 71:45 72:46 73:47 74:48 75:48 76:49 77:50 78:50 79:51 80:52 81:53 82:54 83:54 84:55 85:56 86:57 87:58 88:59 89:60 90:61 91:62 92:63 93:63 94:63 95:64 96:65 97:66 98:67 99:68 100:69 101:70 102:71 103:71 104:72 105:73 106:74 107:75 108:76 109:77 110:78 111:79 112:80 113:81 114:82 115:83 116:84 117:85 118:86 119:86 120:87 121:88 122:89 123:90 124:91 125:92 126:93 127:93 128:94 129:95 130:96 131:97 132:98 133:99 134:100 135:101 136:102 137:103 138:104 139:105 140:106 141:107 142:108 143:109 144:110 145:111 146:112 147:113 148:113\n",
            "INFO:tensorflow:token_is_max_context: 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True\n",
            "I1012 15:05:12.586174 140273920317312 run_squad.py:440] token_is_max_context: 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True\n",
            "INFO:tensorflow:input_ids: 101 2073 2515 1037 3021 2175 2320 1996 2343 5751 2009 2046 3466 1029 102 2044 1996 2343 5751 1037 3021 2046 2375 1006 2030 3519 4372 18908 2015 2009 2058 2010 22102 1007 1010 2009 2003 5359 2000 1996 2436 1997 1996 2976 4236 1006 1997 2099 1007 1997 1996 2120 8264 1998 2636 3447 1006 27544 1007 2073 2009 2003 4137 1037 2375 2193 1010 1998 4810 2005 4772 2004 1037 7540 2375 1012 2270 4277 1010 2021 2025 2797 4277 1010 2024 2036 2445 3423 15201 11091 2011 1996 1997 2099 1012 2012 1996 2203 1997 2169 5219 1997 3519 1010 1996 7540 4277 2024 9227 2046 5391 6702 2170 1996 2142 2163 18574 2012 2312 1010 1998 2027 2024 2124 2004 5219 4277 1012 1996 18574 2012 2312 2556 1037 23472 6512 1997 1996 4277 1999 1996 6635 2344 2008 2027 2031 2042 11955 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.586749 140273920317312 run_squad.py:442] input_ids: 101 2073 2515 1037 3021 2175 2320 1996 2343 5751 2009 2046 3466 1029 102 2044 1996 2343 5751 1037 3021 2046 2375 1006 2030 3519 4372 18908 2015 2009 2058 2010 22102 1007 1010 2009 2003 5359 2000 1996 2436 1997 1996 2976 4236 1006 1997 2099 1007 1997 1996 2120 8264 1998 2636 3447 1006 27544 1007 2073 2009 2003 4137 1037 2375 2193 1010 1998 4810 2005 4772 2004 1037 7540 2375 1012 2270 4277 1010 2021 2025 2797 4277 1010 2024 2036 2445 3423 15201 11091 2011 1996 1997 2099 1012 2012 1996 2203 1997 2169 5219 1997 3519 1010 1996 7540 4277 2024 9227 2046 5391 6702 2170 1996 2142 2163 18574 2012 2312 1010 1998 2027 2024 2124 2004 5219 4277 1012 1996 18574 2012 2312 2556 1037 23472 6512 1997 1996 4277 1999 1996 6635 2344 2008 2027 2031 2042 11955 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.587373 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.587831 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 37\n",
            "I1012 15:05:12.588119 140273920317312 run_squad.py:451] start_position: 37\n",
            "INFO:tensorflow:end_position: 58\n",
            "I1012 15:05:12.588244 140273920317312 run_squad.py:452] end_position: 58\n",
            "INFO:tensorflow:answer: delivered to the office of the federal register ( of ##r ) of the national archives and records administration ( nara )\n",
            "I1012 15:05:12.588361 140273920317312 run_squad.py:454] answer: delivered to the office of the federal register ( of ##r ) of the national archives and records administration ( nara )\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.593402 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000017\n",
            "I1012 15:05:12.593644 140273920317312 run_squad.py:432] unique_id: 1000000017\n",
            "INFO:tensorflow:example_index: 17\n",
            "I1012 15:05:12.593746 140273920317312 run_squad.py:433] example_index: 17\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.593827 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what other beginnings of origin ##ation do some of the last names of the greeks share ? [SEP] greek surname ##s were widely in use by the 9th century su ##pp ##lan ##ting the ancient tradition of using the father ’ s name , however greek surname ##s are most commonly patron ##ym ##ics . commonly , greek male surname ##s end in - s , which is the common ending for greek masculine proper nouns in the no ##mina ##tive case . exceptionally , some end in - ou , indicating the gen ##itive case of this proper noun for patron ##ym ##ic reasons . although surname ##s in mainland greece are static today , dynamic and changing patron ##ym ##ic usage survives in middle names where the gen ##itive of father ' s first name is commonly the middle name ( this usage having been passed on to the russians ) . in cyprus , by contrast , surname ##s follow the ancient tradition of being given according to the father ’ s name . finally , in addition to greek - derived surname ##s many have latin , turkish and italian origin . [SEP]\n",
            "I1012 15:05:12.593985 140273920317312 run_squad.py:436] tokens: [CLS] what other beginnings of origin ##ation do some of the last names of the greeks share ? [SEP] greek surname ##s were widely in use by the 9th century su ##pp ##lan ##ting the ancient tradition of using the father ’ s name , however greek surname ##s are most commonly patron ##ym ##ics . commonly , greek male surname ##s end in - s , which is the common ending for greek masculine proper nouns in the no ##mina ##tive case . exceptionally , some end in - ou , indicating the gen ##itive case of this proper noun for patron ##ym ##ic reasons . although surname ##s in mainland greece are static today , dynamic and changing patron ##ym ##ic usage survives in middle names where the gen ##itive of father ' s first name is commonly the middle name ( this usage having been passed on to the russians ) . in cyprus , by contrast , surname ##s follow the ancient tradition of being given according to the father ’ s name . finally , in addition to greek - derived surname ##s many have latin , turkish and italian origin . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 19:0 20:1 21:1 22:2 23:3 24:4 25:5 26:6 27:7 28:8 29:9 30:10 31:10 32:10 33:10 34:11 35:12 36:13 37:14 38:15 39:16 40:17 41:17 42:17 43:18 44:18 45:19 46:20 47:21 48:21 49:22 50:23 51:24 52:25 53:25 54:25 55:25 56:26 57:26 58:27 59:28 60:29 61:29 62:30 63:31 64:32 65:32 66:32 67:33 68:34 69:35 70:36 71:37 72:38 73:39 74:40 75:41 76:42 77:43 78:44 79:45 80:45 81:45 82:46 83:46 84:47 85:47 86:48 87:49 88:50 89:51 90:51 91:51 92:52 93:53 94:54 95:54 96:55 97:56 98:57 99:58 100:59 101:60 102:61 103:61 104:61 105:62 106:62 107:63 108:64 109:64 110:65 111:66 112:67 113:68 114:69 115:70 116:70 117:71 118:72 119:73 120:74 121:74 122:74 123:75 124:76 125:77 126:78 127:79 128:80 129:81 130:82 131:82 132:83 133:84 134:84 135:84 136:85 137:86 138:87 139:88 140:89 141:90 142:91 143:92 144:92 145:93 146:94 147:95 148:96 149:97 150:98 151:99 152:100 153:100 154:100 155:101 156:102 157:102 158:103 159:104 160:104 161:105 162:105 163:106 164:107 165:108 166:109 167:110 168:111 169:112 170:113 171:114 172:115 173:116 174:116 175:116 176:117 177:117 178:118 179:118 180:119 181:120 182:121 183:122 184:122 185:122 186:123 187:123 188:124 189:125 190:126 191:126 192:127 193:128 194:129 195:130 196:130\n",
            "I1012 15:05:12.594163 140273920317312 run_squad.py:438] token_to_orig_map: 19:0 20:1 21:1 22:2 23:3 24:4 25:5 26:6 27:7 28:8 29:9 30:10 31:10 32:10 33:10 34:11 35:12 36:13 37:14 38:15 39:16 40:17 41:17 42:17 43:18 44:18 45:19 46:20 47:21 48:21 49:22 50:23 51:24 52:25 53:25 54:25 55:25 56:26 57:26 58:27 59:28 60:29 61:29 62:30 63:31 64:32 65:32 66:32 67:33 68:34 69:35 70:36 71:37 72:38 73:39 74:40 75:41 76:42 77:43 78:44 79:45 80:45 81:45 82:46 83:46 84:47 85:47 86:48 87:49 88:50 89:51 90:51 91:51 92:52 93:53 94:54 95:54 96:55 97:56 98:57 99:58 100:59 101:60 102:61 103:61 104:61 105:62 106:62 107:63 108:64 109:64 110:65 111:66 112:67 113:68 114:69 115:70 116:70 117:71 118:72 119:73 120:74 121:74 122:74 123:75 124:76 125:77 126:78 127:79 128:80 129:81 130:82 131:82 132:83 133:84 134:84 135:84 136:85 137:86 138:87 139:88 140:89 141:90 142:91 143:92 144:92 145:93 146:94 147:95 148:96 149:97 150:98 151:99 152:100 153:100 154:100 155:101 156:102 157:102 158:103 159:104 160:104 161:105 162:105 163:106 164:107 165:108 166:109 167:110 168:111 169:112 170:113 171:114 172:115 173:116 174:116 175:116 176:117 177:117 178:118 179:118 180:119 181:120 182:121 183:122 184:122 185:122 186:123 187:123 188:124 189:125 190:126 191:126 192:127 193:128 194:129 195:130 196:130\n",
            "INFO:tensorflow:token_is_max_context: 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True\n",
            "I1012 15:05:12.594324 140273920317312 run_squad.py:440] token_is_max_context: 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True 117:True 118:True 119:True 120:True 121:True 122:True 123:True 124:True 125:True 126:True 127:True 128:True 129:True 130:True 131:True 132:True 133:True 134:True 135:True 136:True 137:True 138:True 139:True 140:True 141:True 142:True 143:True 144:True 145:True 146:True 147:True 148:True 149:True 150:True 151:True 152:True 153:True 154:True 155:True 156:True 157:True 158:True 159:True 160:True 161:True 162:True 163:True 164:True 165:True 166:True 167:True 168:True 169:True 170:True 171:True 172:True 173:True 174:True 175:True 176:True 177:True 178:True 179:True 180:True 181:True 182:True 183:True 184:True 185:True 186:True 187:True 188:True 189:True 190:True 191:True 192:True 193:True 194:True 195:True 196:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2060 16508 1997 4761 3370 2079 2070 1997 1996 2197 3415 1997 1996 13176 3745 1029 102 3306 11988 2015 2020 4235 1999 2224 2011 1996 6280 2301 10514 9397 5802 3436 1996 3418 4535 1997 2478 1996 2269 1521 1055 2171 1010 2174 3306 11988 2015 2024 2087 4141 9161 24335 6558 1012 4141 1010 3306 3287 11988 2015 2203 1999 1011 1055 1010 2029 2003 1996 2691 4566 2005 3306 14818 5372 19211 1999 1996 2053 22311 6024 2553 1012 17077 1010 2070 2203 1999 1011 15068 1010 8131 1996 8991 13043 2553 1997 2023 5372 15156 2005 9161 24335 2594 4436 1012 2348 11988 2015 1999 8240 5483 2024 10763 2651 1010 8790 1998 5278 9161 24335 2594 8192 13655 1999 2690 3415 2073 1996 8991 13043 1997 2269 1005 1055 2034 2171 2003 4141 1996 2690 2171 1006 2023 8192 2383 2042 2979 2006 2000 1996 12513 1007 1012 1999 9719 1010 2011 5688 1010 11988 2015 3582 1996 3418 4535 1997 2108 2445 2429 2000 1996 2269 1521 1055 2171 1012 2633 1010 1999 2804 2000 3306 1011 5173 11988 2015 2116 2031 3763 1010 5037 1998 3059 4761 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.594523 140273920317312 run_squad.py:442] input_ids: 101 2054 2060 16508 1997 4761 3370 2079 2070 1997 1996 2197 3415 1997 1996 13176 3745 1029 102 3306 11988 2015 2020 4235 1999 2224 2011 1996 6280 2301 10514 9397 5802 3436 1996 3418 4535 1997 2478 1996 2269 1521 1055 2171 1010 2174 3306 11988 2015 2024 2087 4141 9161 24335 6558 1012 4141 1010 3306 3287 11988 2015 2203 1999 1011 1055 1010 2029 2003 1996 2691 4566 2005 3306 14818 5372 19211 1999 1996 2053 22311 6024 2553 1012 17077 1010 2070 2203 1999 1011 15068 1010 8131 1996 8991 13043 2553 1997 2023 5372 15156 2005 9161 24335 2594 4436 1012 2348 11988 2015 1999 8240 5483 2024 10763 2651 1010 8790 1998 5278 9161 24335 2594 8192 13655 1999 2690 3415 2073 1996 8991 13043 1997 2269 1005 1055 2034 2171 2003 4141 1996 2690 2171 1006 2023 8192 2383 2042 2979 2006 2000 1996 12513 1007 1012 1999 9719 1010 2011 5688 1010 11988 2015 3582 1996 3418 4535 1997 2108 2445 2429 2000 1996 2269 1521 1055 2171 1012 2633 1010 1999 2804 2000 3306 1011 5173 11988 2015 2116 2031 3763 1010 5037 1998 3059 4761 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.594700 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.594868 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 188\n",
            "I1012 15:05:12.594948 140273920317312 run_squad.py:451] start_position: 188\n",
            "INFO:tensorflow:end_position: 196\n",
            "I1012 15:05:12.595018 140273920317312 run_squad.py:452] end_position: 196\n",
            "INFO:tensorflow:answer: many have latin , turkish and italian origin .\n",
            "I1012 15:05:12.595088 140273920317312 run_squad.py:454] answer: many have latin , turkish and italian origin .\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.597223 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000018\n",
            "I1012 15:05:12.597396 140273920317312 run_squad.py:432] unique_id: 1000000018\n",
            "INFO:tensorflow:example_index: 18\n",
            "I1012 15:05:12.597479 140273920317312 run_squad.py:433] example_index: 18\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.597554 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what is the function of a \" beer engine \" ? [SEP] a \" beer engine \" is a device for pumping beer , originally manually operated and typically used to di ##sp ##ense beer from a cas ##k or container in a pub ' s basement or cellar . [SEP]\n",
            "I1012 15:05:12.597662 140273920317312 run_squad.py:436] tokens: [CLS] what is the function of a \" beer engine \" ? [SEP] a \" beer engine \" is a device for pumping beer , originally manually operated and typically used to di ##sp ##ense beer from a cas ##k or container in a pub ' s basement or cellar . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 13:0 14:1 15:1 16:2 17:2 18:3 19:4 20:5 21:6 22:7 23:8 24:8 25:9 26:10 27:11 28:12 29:13 30:14 31:15 32:16 33:16 34:16 35:17 36:18 37:19 38:20 39:20 40:21 41:22 42:23 43:24 44:25 45:25 46:25 47:26 48:27 49:28 50:28\n",
            "I1012 15:05:12.597766 140273920317312 run_squad.py:438] token_to_orig_map: 13:0 14:1 15:1 16:2 17:2 18:3 19:4 20:5 21:6 22:7 23:8 24:8 25:9 26:10 27:11 28:12 29:13 30:14 31:15 32:16 33:16 34:16 35:17 36:18 37:19 38:20 39:20 40:21 41:22 42:23 43:24 44:25 45:25 46:25 47:26 48:27 49:28 50:28\n",
            "INFO:tensorflow:token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True\n",
            "I1012 15:05:12.597864 140273920317312 run_squad.py:440] token_is_max_context: 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True\n",
            "INFO:tensorflow:input_ids: 101 2054 2003 1996 3853 1997 1037 1000 5404 3194 1000 1029 102 1037 1000 5404 3194 1000 2003 1037 5080 2005 14107 5404 1010 2761 21118 3498 1998 4050 2109 2000 4487 13102 16700 5404 2013 1037 25222 2243 2030 11661 1999 1037 9047 1005 1055 8102 2030 15423 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.598051 140273920317312 run_squad.py:442] input_ids: 101 2054 2003 1996 3853 1997 1037 1000 5404 3194 1000 1029 102 1037 1000 5404 3194 1000 2003 1037 5080 2005 14107 5404 1010 2761 21118 3498 1998 4050 2109 2000 4487 13102 16700 5404 2013 1037 25222 2243 2030 11661 1999 1037 9047 1005 1055 8102 2030 15423 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.691001 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.691512 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:start_position: 31\n",
            "I1012 15:05:12.691800 140273920317312 run_squad.py:451] start_position: 31\n",
            "INFO:tensorflow:end_position: 49\n",
            "I1012 15:05:12.692030 140273920317312 run_squad.py:452] end_position: 49\n",
            "INFO:tensorflow:answer: to di ##sp ##ense beer from a cas ##k or container in a pub ' s basement or cellar\n",
            "I1012 15:05:12.692169 140273920317312 run_squad.py:454] answer: to di ##sp ##ense beer from a cas ##k or container in a pub ' s basement or cellar\n",
            "INFO:tensorflow:*** Example ***\n",
            "I1012 15:05:12.695983 140273920317312 run_squad.py:431] *** Example ***\n",
            "INFO:tensorflow:unique_id: 1000000019\n",
            "I1012 15:05:12.696208 140273920317312 run_squad.py:432] unique_id: 1000000019\n",
            "INFO:tensorflow:example_index: 19\n",
            "I1012 15:05:12.696297 140273920317312 run_squad.py:433] example_index: 19\n",
            "INFO:tensorflow:doc_span_index: 0\n",
            "I1012 15:05:12.696374 140273920317312 run_squad.py:434] doc_span_index: 0\n",
            "INFO:tensorflow:tokens: [CLS] what coats uranium metal in liquid ? [SEP] uranium metal reacts with almost all non - metal elements ( with an exception of the noble gases ) and their compounds , with react ##ivity increasing with temperature . hydro ##ch ##lor ##ic and ni ##tric acids dissolve uranium , but non - ox ##idi ##zing acids other than hydro ##ch ##lor ##ic acid attack the element very slowly . when finely divided , it can react with cold water ; in air , uranium metal becomes coated with a dark layer of uranium oxide . uranium in ore ##s is extracted chemical ##ly and converted into uranium dioxide or other chemical forms usable in industry . [SEP]\n",
            "I1012 15:05:12.696501 140273920317312 run_squad.py:436] tokens: [CLS] what coats uranium metal in liquid ? [SEP] uranium metal reacts with almost all non - metal elements ( with an exception of the noble gases ) and their compounds , with react ##ivity increasing with temperature . hydro ##ch ##lor ##ic and ni ##tric acids dissolve uranium , but non - ox ##idi ##zing acids other than hydro ##ch ##lor ##ic acid attack the element very slowly . when finely divided , it can react with cold water ; in air , uranium metal becomes coated with a dark layer of uranium oxide . uranium in ore ##s is extracted chemical ##ly and converted into uranium dioxide or other chemical forms usable in industry . [SEP]\n",
            "INFO:tensorflow:token_to_orig_map: 9:0 10:1 11:2 12:3 13:4 14:5 15:6 16:6 17:6 18:7 19:8 20:8 21:9 22:10 23:11 24:12 25:13 26:14 27:14 28:15 29:16 30:17 31:17 32:18 33:19 34:19 35:20 36:21 37:22 38:22 39:23 40:23 41:23 42:23 43:24 44:25 45:25 46:26 47:27 48:28 49:28 50:29 51:30 52:30 53:30 54:30 55:30 56:31 57:32 58:33 59:34 60:34 61:34 62:34 63:35 64:36 65:37 66:38 67:39 68:40 69:40 70:41 71:42 72:43 73:43 74:44 75:45 76:46 77:47 78:48 79:49 80:49 81:50 82:51 83:51 84:52 85:53 86:54 87:55 88:56 89:57 90:58 91:59 92:60 93:61 94:62 95:62 96:63 97:64 98:65 99:65 100:66 101:67 102:68 103:68 104:69 105:70 106:71 107:72 108:73 109:74 110:75 111:76 112:77 113:78 114:79 115:80 116:80\n",
            "I1012 15:05:12.696639 140273920317312 run_squad.py:438] token_to_orig_map: 9:0 10:1 11:2 12:3 13:4 14:5 15:6 16:6 17:6 18:7 19:8 20:8 21:9 22:10 23:11 24:12 25:13 26:14 27:14 28:15 29:16 30:17 31:17 32:18 33:19 34:19 35:20 36:21 37:22 38:22 39:23 40:23 41:23 42:23 43:24 44:25 45:25 46:26 47:27 48:28 49:28 50:29 51:30 52:30 53:30 54:30 55:30 56:31 57:32 58:33 59:34 60:34 61:34 62:34 63:35 64:36 65:37 66:38 67:39 68:40 69:40 70:41 71:42 72:43 73:43 74:44 75:45 76:46 77:47 78:48 79:49 80:49 81:50 82:51 83:51 84:52 85:53 86:54 87:55 88:56 89:57 90:58 91:59 92:60 93:61 94:62 95:62 96:63 97:64 98:65 99:65 100:66 101:67 102:68 103:68 104:69 105:70 106:71 107:72 108:73 109:74 110:75 111:76 112:77 113:78 114:79 115:80 116:80\n",
            "INFO:tensorflow:token_is_max_context: 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True\n",
            "I1012 15:05:12.696784 140273920317312 run_squad.py:440] token_is_max_context: 9:True 10:True 11:True 12:True 13:True 14:True 15:True 16:True 17:True 18:True 19:True 20:True 21:True 22:True 23:True 24:True 25:True 26:True 27:True 28:True 29:True 30:True 31:True 32:True 33:True 34:True 35:True 36:True 37:True 38:True 39:True 40:True 41:True 42:True 43:True 44:True 45:True 46:True 47:True 48:True 49:True 50:True 51:True 52:True 53:True 54:True 55:True 56:True 57:True 58:True 59:True 60:True 61:True 62:True 63:True 64:True 65:True 66:True 67:True 68:True 69:True 70:True 71:True 72:True 73:True 74:True 75:True 76:True 77:True 78:True 79:True 80:True 81:True 82:True 83:True 84:True 85:True 86:True 87:True 88:True 89:True 90:True 91:True 92:True 93:True 94:True 95:True 96:True 97:True 98:True 99:True 100:True 101:True 102:True 103:True 104:True 105:True 106:True 107:True 108:True 109:True 110:True 111:True 112:True 113:True 114:True 115:True 116:True\n",
            "INFO:tensorflow:input_ids: 101 2054 15695 14247 3384 1999 6381 1029 102 14247 3384 27325 2007 2471 2035 2512 1011 3384 3787 1006 2007 2019 6453 1997 1996 7015 15865 1007 1998 2037 10099 1010 2007 10509 7730 4852 2007 4860 1012 18479 2818 10626 2594 1998 9152 12412 12737 21969 14247 1010 2021 2512 1011 23060 28173 6774 12737 2060 2084 18479 2818 10626 2594 5648 2886 1996 5783 2200 3254 1012 2043 22126 4055 1010 2009 2064 10509 2007 3147 2300 1025 1999 2250 1010 14247 3384 4150 15026 2007 1037 2601 6741 1997 14247 15772 1012 14247 1999 10848 2015 2003 15901 5072 2135 1998 4991 2046 14247 14384 2030 2060 5072 3596 24013 1999 3068 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.696977 140273920317312 run_squad.py:442] input_ids: 101 2054 15695 14247 3384 1999 6381 1029 102 14247 3384 27325 2007 2471 2035 2512 1011 3384 3787 1006 2007 2019 6453 1997 1996 7015 15865 1007 1998 2037 10099 1010 2007 10509 7730 4852 2007 4860 1012 18479 2818 10626 2594 1998 9152 12412 12737 21969 14247 1010 2021 2512 1011 23060 28173 6774 12737 2060 2084 18479 2818 10626 2594 5648 2886 1996 5783 2200 3254 1012 2043 22126 4055 1010 2009 2064 10509 2007 3147 2300 1025 1999 2250 1010 14247 3384 4150 15026 2007 1037 2601 6741 1997 14247 15772 1012 14247 1999 10848 2015 2003 15901 5072 2135 1998 4991 2046 14247 14384 2030 2060 5072 3596 24013 1999 3068 1012 102 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.697161 140273920317312 run_squad.py:444] input_mask: 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:segment_ids: 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "I1012 15:05:12.697333 140273920317312 run_squad.py:446] segment_ids: 0 0 0 0 0 0 0 0 0 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 1 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0 0\n",
            "INFO:tensorflow:impossible example\n",
            "I1012 15:05:12.697411 140273920317312 run_squad.py:448] impossible example\n",
            "INFO:tensorflow:***** Running training *****\n",
            "I1012 15:13:37.366663 140273920317312 run_squad.py:1203] ***** Running training *****\n",
            "INFO:tensorflow:  Num orig examples = 130319\n",
            "I1012 15:13:37.367003 140273920317312 run_squad.py:1204]   Num orig examples = 130319\n",
            "INFO:tensorflow:  Num split examples = 131944\n",
            "I1012 15:13:37.367122 140273920317312 run_squad.py:1205]   Num split examples = 131944\n",
            "INFO:tensorflow:  Batch size = 24\n",
            "I1012 15:13:37.367232 140273920317312 run_squad.py:1206]   Batch size = 24\n",
            "INFO:tensorflow:  Num steps = 10859\n",
            "I1012 15:13:37.367298 140273920317312 run_squad.py:1207]   Num steps = 10859\n",
            "WARNING:tensorflow:From run_squad.py:691: The name tf.FixedLenFeature is deprecated. Please use tf.io.FixedLenFeature instead.\n",
            "\n",
            "W1012 15:13:37.604519 140273920317312 module_wrapper.py:139] From run_squad.py:691: The name tf.FixedLenFeature is deprecated. Please use tf.io.FixedLenFeature instead.\n",
            "\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "If using Keras pass *_constraint arguments to layers.\n",
            "W1012 15:13:37.627132 140273920317312 deprecation.py:506] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/resource_variable_ops.py:1630: calling BaseResourceVariable.__init__ (from tensorflow.python.ops.resource_variable_ops) with constraint is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "If using Keras pass *_constraint arguments to layers.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.\n",
            "W1012 15:13:37.627692 140273920317312 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/training/training_util.py:236: Variable.initialized_value (from tensorflow.python.ops.variables) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use Variable.read_value. Variables in 2.X are initialized automatically both in eager and graph (inside tf.defun) contexts.\n",
            "WARNING:tensorflow:From run_squad.py:730: map_and_batch (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.experimental.map_and_batch(...)`.\n",
            "W1012 15:13:37.677609 140273920317312 deprecation.py:323] From run_squad.py:730: map_and_batch (from tensorflow.contrib.data.python.ops.batching) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.experimental.map_and_batch(...)`.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/data/python/ops/batching.py:276: map_and_batch (from tensorflow.python.data.experimental.ops.batching) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map(map_func, num_parallel_calls)` followed by `tf.data.Dataset.batch(batch_size, drop_remainder)`. Static tf.data optimizations will take care of using the fused implementation.\n",
            "W1012 15:13:37.677874 140273920317312 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/contrib/data/python/ops/batching.py:276: map_and_batch (from tensorflow.python.data.experimental.ops.batching) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.data.Dataset.map(map_func, num_parallel_calls)` followed by `tf.data.Dataset.batch(batch_size, drop_remainder)`. Static tf.data optimizations will take care of using the fused implementation.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.parse_single_example is deprecated. Please use tf.io.parse_single_example instead.\n",
            "\n",
            "W1012 15:13:37.750007 140273920317312 module_wrapper.py:139] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/autograph/converters/directives.py:119: The name tf.parse_single_example is deprecated. Please use tf.io.parse_single_example instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:710: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "W1012 15:13:37.877443 140273920317312 deprecation.py:323] From run_squad.py:710: to_int32 (from tensorflow.python.ops.math_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use `tf.cast` instead.\n",
            "INFO:tensorflow:Calling model_fn.\n",
            "I1012 15:13:37.897834 140273920317312 estimator.py:1148] Calling model_fn.\n",
            "INFO:tensorflow:Running train on CPU\n",
            "I1012 15:13:37.898225 140273920317312 tpu_estimator.py:3124] Running train on CPU\n",
            "INFO:tensorflow:*** Features ***\n",
            "I1012 15:13:37.898594 140273920317312 run_squad.py:598] *** Features ***\n",
            "INFO:tensorflow:  name = end_positions, shape = (24,)\n",
            "I1012 15:13:37.898730 140273920317312 run_squad.py:600]   name = end_positions, shape = (24,)\n",
            "INFO:tensorflow:  name = input_ids, shape = (24, 384)\n",
            "I1012 15:13:37.898820 140273920317312 run_squad.py:600]   name = input_ids, shape = (24, 384)\n",
            "INFO:tensorflow:  name = input_mask, shape = (24, 384)\n",
            "I1012 15:13:37.898922 140273920317312 run_squad.py:600]   name = input_mask, shape = (24, 384)\n",
            "INFO:tensorflow:  name = segment_ids, shape = (24, 384)\n",
            "I1012 15:13:37.899000 140273920317312 run_squad.py:600]   name = segment_ids, shape = (24, 384)\n",
            "INFO:tensorflow:  name = start_positions, shape = (24,)\n",
            "I1012 15:13:37.899071 140273920317312 run_squad.py:600]   name = start_positions, shape = (24,)\n",
            "INFO:tensorflow:  name = unique_ids, shape = (24,)\n",
            "I1012 15:13:37.899157 140273920317312 run_squad.py:600]   name = unique_ids, shape = (24,)\n",
            "WARNING:tensorflow:From /content/modeling.py:171: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
            "\n",
            "W1012 15:13:37.899379 140273920317312 module_wrapper.py:139] From /content/modeling.py:171: The name tf.variable_scope is deprecated. Please use tf.compat.v1.variable_scope instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/modeling.py:409: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
            "\n",
            "W1012 15:13:37.901259 140273920317312 module_wrapper.py:139] From /content/modeling.py:409: The name tf.get_variable is deprecated. Please use tf.compat.v1.get_variable instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/modeling.py:490: The name tf.assert_less_equal is deprecated. Please use tf.compat.v1.assert_less_equal instead.\n",
            "\n",
            "W1012 15:13:37.922797 140273920317312 module_wrapper.py:139] From /content/modeling.py:490: The name tf.assert_less_equal is deprecated. Please use tf.compat.v1.assert_less_equal instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/modeling.py:358: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
            "W1012 15:13:37.970703 140273920317312 deprecation.py:506] From /content/modeling.py:358: calling dropout (from tensorflow.python.ops.nn_ops) with keep_prob is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `rate` instead of `keep_prob`. Rate should be set to `rate = 1 - keep_prob`.\n",
            "WARNING:tensorflow:From /content/modeling.py:671: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use keras.layers.Dense instead.\n",
            "W1012 15:13:37.984908 140273920317312 deprecation.py:323] From /content/modeling.py:671: dense (from tensorflow.python.layers.core) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use keras.layers.Dense instead.\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/core.py:187: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `layer.__call__` method instead.\n",
            "W1012 15:13:37.986412 140273920317312 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/layers/core.py:187: Layer.apply (from tensorflow.python.keras.engine.base_layer) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Please use `layer.__call__` method instead.\n",
            "WARNING:tensorflow:From run_squad.py:617: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.\n",
            "\n",
            "W1012 15:13:41.778558 140273920317312 module_wrapper.py:139] From run_squad.py:617: The name tf.trainable_variables is deprecated. Please use tf.compat.v1.trainable_variables instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:632: The name tf.train.init_from_checkpoint is deprecated. Please use tf.compat.v1.train.init_from_checkpoint instead.\n",
            "\n",
            "W1012 15:13:41.783121 140273920317312 module_wrapper.py:139] From run_squad.py:632: The name tf.train.init_from_checkpoint is deprecated. Please use tf.compat.v1.train.init_from_checkpoint instead.\n",
            "\n",
            "INFO:tensorflow:**** Trainable Variables ****\n",
            "I1012 15:13:42.997735 140273920317312 run_squad.py:634] **** Trainable Variables ****\n",
            "INFO:tensorflow:  name = bert/embeddings/word_embeddings:0, shape = (30522, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.997967 140273920317312 run_squad.py:640]   name = bert/embeddings/word_embeddings:0, shape = (30522, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/embeddings/token_type_embeddings:0, shape = (2, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998083 140273920317312 run_squad.py:640]   name = bert/embeddings/token_type_embeddings:0, shape = (2, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/embeddings/position_embeddings:0, shape = (512, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998227 140273920317312 run_squad.py:640]   name = bert/embeddings/position_embeddings:0, shape = (512, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/embeddings/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998310 140273920317312 run_squad.py:640]   name = bert/embeddings/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/embeddings/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998385 140273920317312 run_squad.py:640]   name = bert/embeddings/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998453 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998524 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998589 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998657 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998721 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998787 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998861 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998928 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.998991 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999052 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999126 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999195 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999257 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999321 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999389 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_0/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999452 140273920317312 run_squad.py:640]   name = bert/encoder/layer_0/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999514 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999579 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999639 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999705 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999767 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999832 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999895 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:42.999959 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000021 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000083 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000158 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000225 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000285 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000351 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000422 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_1/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000483 140273920317312 run_squad.py:640]   name = bert/encoder/layer_1/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000544 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000611 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000672 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000739 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000802 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000867 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.000928 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001014 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001128 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001215 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001280 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001349 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001425 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001492 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001555 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_2/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001616 140273920317312 run_squad.py:640]   name = bert/encoder/layer_2/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001677 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001744 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001807 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001874 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.001938 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002005 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002068 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002155 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002218 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002280 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002341 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002435 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.002501 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.084906 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.085223 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_3/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.085431 140273920317312 run_squad.py:640]   name = bert/encoder/layer_3/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.085586 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.085741 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.085891 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086048 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086196 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086348 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086480 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086622 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086750 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.086888 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087021 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087203 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087337 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087479 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087609 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_4/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087738 140273920317312 run_squad.py:640]   name = bert/encoder/layer_4/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.087870 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088013 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088174 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088325 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088461 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088597 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.088727 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089046 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089264 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089416 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089559 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089722 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.089870 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090040 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090210 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_5/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090353 140273920317312 run_squad.py:640]   name = bert/encoder/layer_5/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090493 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090641 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090780 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.090926 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091073 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091244 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091375 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091519 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091657 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091789 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.091913 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092066 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092218 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092360 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092489 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_6/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092617 140273920317312 run_squad.py:640]   name = bert/encoder/layer_6/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092745 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.092881 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093023 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093180 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093316 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093457 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093588 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093733 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093859 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.093995 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094141 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094281 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094412 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094549 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094679 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_7/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094807 140273920317312 run_squad.py:640]   name = bert/encoder/layer_7/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.094932 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095087 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095238 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095378 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095507 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095645 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095776 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.095913 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096051 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096206 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096334 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096477 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096609 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096746 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.096874 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_8/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097009 140273920317312 run_squad.py:640]   name = bert/encoder/layer_8/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097153 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097293 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097421 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097560 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097686 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097803 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.097920 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098065 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098209 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098335 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098461 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098596 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098722 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.098865 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099001 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_9/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099146 140273920317312 run_squad.py:640]   name = bert/encoder/layer_9/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099272 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099405 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099532 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099665 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099795 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.099927 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100068 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100223 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100349 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100477 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100602 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100738 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.100868 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101011 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101158 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_10/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101285 140273920317312 run_squad.py:640]   name = bert/encoder/layer_10/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101411 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101551 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101678 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101814 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.101943 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102090 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102243 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102379 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102509 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102635 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102760 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.102898 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103034 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103194 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103325 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_11/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103449 140273920317312 run_squad.py:640]   name = bert/encoder/layer_11/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103576 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103712 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103839 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.103984 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104129 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104272 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104398 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104531 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104660 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104784 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.104908 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105055 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105197 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105333 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105460 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_12/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105606 140273920317312 run_squad.py:640]   name = bert/encoder/layer_12/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105733 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.105869 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106007 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106160 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106289 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106424 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106550 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106689 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106813 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.106938 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107073 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107230 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107359 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107492 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107617 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_13/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107741 140273920317312 run_squad.py:640]   name = bert/encoder/layer_13/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.107863 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108012 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108158 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108296 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108423 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108559 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108685 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108830 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.108967 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109082 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109222 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109357 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109481 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109617 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109740 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_14/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.109864 140273920317312 run_squad.py:640]   name = bert/encoder/layer_14/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110000 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110157 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110287 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110421 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110548 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110684 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110811 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.110949 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111087 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111232 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111358 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111493 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111621 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111758 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.111886 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_15/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112023 140273920317312 run_squad.py:640]   name = bert/encoder/layer_15/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112165 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112303 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112432 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112567 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112693 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112828 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.112960 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113117 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113251 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113377 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113502 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113638 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113767 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.113898 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114033 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_16/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114176 140273920317312 run_squad.py:640]   name = bert/encoder/layer_16/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114300 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114436 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114562 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114697 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114825 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.114968 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115111 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115252 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115380 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115506 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115628 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115760 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.115888 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116032 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116180 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_17/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116307 140273920317312 run_squad.py:640]   name = bert/encoder/layer_17/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116430 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116567 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116691 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116826 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.116961 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117113 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117246 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117379 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117507 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117632 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117756 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.117893 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118030 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118185 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118312 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_18/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118434 140273920317312 run_squad.py:640]   name = bert/encoder/layer_18/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118559 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118695 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118830 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.118980 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119122 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119263 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119390 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119524 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119652 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119772 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.119895 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120042 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120188 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120327 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120450 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_19/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120573 140273920317312 run_squad.py:640]   name = bert/encoder/layer_19/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120699 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120833 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.120967 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121124 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121259 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121398 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121524 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121663 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121791 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.121916 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122054 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122209 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122338 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122476 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122605 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_20/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122732 140273920317312 run_squad.py:640]   name = bert/encoder/layer_20/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122853 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.122999 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123145 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123283 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123412 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123546 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123672 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123811 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.123937 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124075 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124229 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124366 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124493 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124628 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124753 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_21/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.124880 140273920317312 run_squad.py:640]   name = bert/encoder/layer_21/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125014 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125169 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125296 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125427 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125573 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125709 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.125838 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126009 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126163 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126293 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126419 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126561 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126686 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126819 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.126948 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_22/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127085 140273920317312 run_squad.py:640]   name = bert/encoder/layer_22/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127231 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/query/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127369 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/query/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127494 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/key/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127631 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/key/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127754 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/value/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.127889 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/self/value/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128026 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/output/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128184 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128317 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128441 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/attention/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128566 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/intermediate/dense/kernel:0, shape = (1024, 4096), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128703 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/intermediate/dense/bias:0, shape = (4096,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128838 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/output/dense/kernel:0, shape = (4096, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.128985 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/output/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.129128 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/output/LayerNorm/beta:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/encoder/layer_23/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.129258 140273920317312 run_squad.py:640]   name = bert/encoder/layer_23/output/LayerNorm/gamma:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/pooler/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.129384 140273920317312 run_squad.py:640]   name = bert/pooler/dense/kernel:0, shape = (1024, 1024), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = bert/pooler/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "I1012 15:13:43.129522 140273920317312 run_squad.py:640]   name = bert/pooler/dense/bias:0, shape = (1024,), *INIT_FROM_CKPT*\n",
            "INFO:tensorflow:  name = cls/squad/output_weights:0, shape = (2, 1024)\n",
            "I1012 15:13:43.129706 140273920317312 run_squad.py:640]   name = cls/squad/output_weights:0, shape = (2, 1024)\n",
            "INFO:tensorflow:  name = cls/squad/output_bias:0, shape = (2,)\n",
            "I1012 15:13:43.129885 140273920317312 run_squad.py:640]   name = cls/squad/output_bias:0, shape = (2,)\n",
            "WARNING:tensorflow:From /content/optimization.py:27: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.\n",
            "\n",
            "W1012 15:13:43.143157 140273920317312 module_wrapper.py:139] From /content/optimization.py:27: The name tf.train.get_or_create_global_step is deprecated. Please use tf.compat.v1.train.get_or_create_global_step instead.\n",
            "\n",
            "WARNING:tensorflow:From /content/optimization.py:32: The name tf.train.polynomial_decay is deprecated. Please use tf.compat.v1.train.polynomial_decay instead.\n",
            "\n",
            "W1012 15:13:43.144028 140273920317312 module_wrapper.py:139] From /content/optimization.py:32: The name tf.train.polynomial_decay is deprecated. Please use tf.compat.v1.train.polynomial_decay instead.\n",
            "\n",
            "WARNING:tensorflow:From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/math_grad.py:1375: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
            "W1012 15:13:43.437216 140273920317312 deprecation.py:323] From /usr/local/lib/python3.6/dist-packages/tensorflow_core/python/ops/math_grad.py:1375: where (from tensorflow.python.ops.array_ops) is deprecated and will be removed in a future version.\n",
            "Instructions for updating:\n",
            "Use tf.where in 2.0, which has the same broadcast rule as np.where\n",
            "INFO:tensorflow:Done calling model_fn.\n",
            "I1012 15:13:55.032850 140273920317312 estimator.py:1150] Done calling model_fn.\n",
            "INFO:tensorflow:Create CheckpointSaverHook.\n",
            "I1012 15:13:55.034299 140273920317312 basic_session_run_hooks.py:541] Create CheckpointSaverHook.\n",
            "INFO:tensorflow:Graph was finalized.\n",
            "I1012 15:14:00.053341 140273920317312 monitored_session.py:240] Graph was finalized.\n",
            "2019-10-12 15:14:00.083834: I tensorflow/core/platform/profile_utils/cpu_utils.cc:94] CPU Frequency: 2300000000 Hz\n",
            "2019-10-12 15:14:00.084090: I tensorflow/compiler/xla/service/service.cc:168] XLA service 0x2801800 initialized for platform Host (this does not guarantee that XLA will be used). Devices:\n",
            "2019-10-12 15:14:00.084136: I tensorflow/compiler/xla/service/service.cc:176]   StreamExecutor device (0): Host, Default Version\n",
            "INFO:tensorflow:Running local_init_op.\n",
            "I1012 15:14:22.266234 140273920317312 session_manager.py:500] Running local_init_op.\n",
            "INFO:tensorflow:Done running local_init_op.\n",
            "I1012 15:14:22.758874 140273920317312 session_manager.py:502] Done running local_init_op.\n",
            "INFO:tensorflow:Saving checkpoints for 0 into /content/output/model.ckpt.\n",
            "I1012 15:14:34.803289 140273920317312 basic_session_run_hooks.py:606] Saving checkpoints for 0 into /content/output/model.ckpt.\n",
            "^C\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "id": "j_XPGRvdjJIL",
        "colab_type": "code",
        "outputId": "b92fad1e-93fe-4ae7-c308-c988645fedae",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 204
        }
      },
      "source": [
        "#Code to run evaluate-v2.0 to get f1 score\n",
        "!python3 evaluate-v2.0.py \\\n",
        "dev-v2.0.json pred.json"
      ],
      "execution_count": 17,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "{\n",
            "  \"exact\": 64.81091552261434,\n",
            "  \"f1\": 67.60971132981278,\n",
            "  \"total\": 11873,\n",
            "  \"HasAns_exact\": 59.159919028340084,\n",
            "  \"HasAns_f1\": 64.7655368790259,\n",
            "  \"HasAns_total\": 5928,\n",
            "  \"NoAns_exact\": 70.4457527333894,\n",
            "  \"NoAns_f1\": 70.4457527333894,\n",
            "  \"NoAns_total\": 5945\n",
            "}\n"
          ],
          "name": "stdout"
        }
      ]
    },
    {
      "cell_type": "code",
      "metadata": {
        "colab_type": "code",
        "id": "z8EQXsLCTEPX",
        "outputId": "c967cdaa-eb9c-441f-f9ab-d05d97167ee1",
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 680
        }
      },
      "source": [
        "#Code to run the run_squad.py file with predicting set and test set of SQuAD 2.0\n",
        "!python3 run_squad.py \\\n",
        "--vocab_file = model_repo/uncased_L-24_H-1024_A-16/vocab.txt \\\n",
        "--bert_config_file = model_repo/uncased_L-24_H-1024_A-16/bert_config.json \\\n",
        "--init_checkpoint = model_repo/uncased_L-24_H-1024_A-16/bert_model.ckpt \\\n",
        "--do_train = False \\\n",
        "--train_file = train-v2.0.json \\\n",
        "--do_predict = True \\\n",
        "--predict_file = dev-v2.0.json \\\n",
        "--train_batch_size = 24 \\\n",
        "--learning_rate = 3e-5 \\\n",
        "--num_train_epochs = 2.0 \\\n",
        "--max_seq_length = 384 \\\n",
        "--doc_stride = 128 \\\n",
        "--version_2_with_negative = True \\\n",
        "--output_dir = /content/output\n",
        "#--use_tpu = True \\\n",
        "#--tpu_name = v2-128 \\"
      ],
      "execution_count": 18,
      "outputs": [
        {
          "output_type": "stream",
          "text": [
            "WARNING:tensorflow:From /content/optimization.py:87: The name tf.train.Optimizer is deprecated. Please use tf.compat.v1.train.Optimizer instead.\n",
            "\n",
            "WARNING:tensorflow:From run_squad.py:1283: The name tf.app.run is deprecated. Please use tf.compat.v1.app.run instead.\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_flag.py\", line 181, in _parse\n",
            "    return self.parser.parse(argument)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_argument_parser.py\", line 152, in parse\n",
            "    val = self.convert(argument)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_argument_parser.py\", line 265, in convert\n",
            "    return int(argument, base)\n",
            "ValueError: invalid literal for int() with base 10: '='\n",
            "\n",
            "During handling of the above exception, another exception occurred:\n",
            "\n",
            "Traceback (most recent call last):\n",
            "  File \"run_squad.py\", line 1283, in <module>\n",
            "    tf.app.run()\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/platform/app.py\", line 40, in run\n",
            "    _run(main=main, argv=argv, flags_parser=_parse_flags_tolerate_undef)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/app.py\", line 293, in run\n",
            "    flags_parser,\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/app.py\", line 362, in _run_init\n",
            "    flags_parser=flags_parser,\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/app.py\", line 212, in _register_and_parse_flags_with_usage\n",
            "    args_to_main = flags_parser(original_argv)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/platform/app.py\", line 31, in _parse_flags_tolerate_undef\n",
            "    return flags.FLAGS(_sys.argv if argv is None else argv, known_only=True)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/tensorflow_core/python/platform/flags.py\", line 112, in __call__\n",
            "    return self.__dict__['__wrapped'].__call__(*args, **kwargs)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_flagvalues.py\", line 626, in __call__\n",
            "    unknown_flags, unparsed_args = self._parse_args(args, known_only)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_flagvalues.py\", line 774, in _parse_args\n",
            "    flag.parse(value)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_flag.py\", line 166, in parse\n",
            "    self.value = self._parse(argument)\n",
            "  File \"/usr/local/lib/python3.6/dist-packages/absl/flags/_flag.py\", line 184, in _parse\n",
            "    'flag --%s=%s: %s' % (self.name, argument, e))\n",
            "absl.flags._exceptions.IllegalFlagValueError: flag --train_batch_size==: invalid literal for int() with base 10: '='\n"
          ],
          "name": "stdout"
        }
      ]
    }
  ]
}