quickstart-11.py

embed_dim = 16

batch_size = 32
n_epochs = 20

import tensorflow as tf
from tensorflow.keras.layers import Conv1D, Flatten, Dense, Dropout

model2 = tf.keras.models.Sequential([
       QuantizedFeaturesEmbedding(n_features, n_bins, embed_dim),
       Dropout(0.2),
       Conv1D(filters=1, kernel_size=3),
       Flatten(),
       Dense(2, activation='softmax')
])

loss2 = tf.keras.losses.BinaryCrossentropy(from_logits=False)
metrics2 = [tf.keras.metrics.BinaryAccuracy()]
model2.compile(optimizer='adam',
              loss=loss2,
              metrics=metrics2)
model2(X_qt[:batch_size]) # build the model, inputs are int32

X_train = tf.data.Dataset.from_tensor_slices(X_train)
y_train = tf.data.Dataset.from_tensor_slices(y_train)
X_test = tf.data.Dataset.from_tensor_slices(X_test)
y_test = tf.data.Dataset.from_tensor_slices(y_test)

ds_train = tf.data.Dataset.zip((X_train, y_train)).shuffle(buffer_size=1024).batch(batch_size=batch_size, drop_remainder=True)
ds_test = tf.data.Dataset.zip((X_test, y_test)).batch(batch_size=batch_size, drop_remainder=True)