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Updated Large-scale multi-label text classification example for Keras v3 #1779

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Updated Large-scale multi-label text classification example for Keras v3 #1779

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7 changes: 4 additions & 3 deletions examples/nlp/multi_label_classification.py
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Expand Up @@ -30,8 +30,9 @@
## Imports
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Can you update Last modified above and add yourself to the authors list?

"""

from tensorflow.keras import layers
from tensorflow import keras
import keras
from keras import layers

import tensorflow as tf

from sklearn.model_selection import train_test_split
Expand Down Expand Up @@ -145,7 +146,7 @@
"""

terms = tf.ragged.constant(train_df["terms"].values)
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Would it work to use padding here instead of ragged tensors?
https://keras.io/api/ops/numpy/#pad-function

lookup = tf.keras.layers.StringLookup(output_mode="multi_hot")
lookup = layers.StringLookup(output_mode="multi_hot")
lookup.adapt(terms)
vocab = lookup.get_vocabulary()

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