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test_transducer.py
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test_transducer.py
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#!/usr/bin/env python3
# Copyright 2021 Xiaomi Corp. (authors: Fangjun Kuang)
#
# See ../../../../LICENSE for clarification regarding multiple authors
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
"""
To run this file, do:
cd icefall/egs/librispeech/ASR
python ./transducer/test_transducer.py
"""
import k2
import torch
from conformer import Conformer
from decoder import Decoder
from joiner import Joiner
from model import Transducer
def test_transducer():
# encoder params
input_dim = 10
output_dim = 20
# decoder params
vocab_size = 3
blank_id = 0
embedding_dim = 128
num_layers = 2
encoder = Conformer(
num_features=input_dim,
output_dim=output_dim,
subsampling_factor=4,
d_model=512,
nhead=8,
dim_feedforward=2048,
num_encoder_layers=12,
)
decoder = Decoder(
vocab_size=vocab_size,
embedding_dim=embedding_dim,
blank_id=blank_id,
num_layers=num_layers,
hidden_dim=output_dim,
output_dim=output_dim,
embedding_dropout=0.0,
rnn_dropout=0.0,
)
joiner = Joiner(output_dim, vocab_size)
transducer = Transducer(encoder=encoder, decoder=decoder, joiner=joiner)
y = k2.RaggedTensor([[1, 2, 1], [1, 1, 1, 2, 1]])
N = y.dim0
T = 50
x = torch.rand(N, T, input_dim)
x_lens = torch.randint(low=30, high=T, size=(N,), dtype=torch.int32)
x_lens[0] = T
loss = transducer(x, x_lens, y)
print(loss)
def main():
test_transducer()
if __name__ == "__main__":
main()