Python tensorflow.keras.layers.GlobalAveragePooling1D() Examples

The following are 2 code examples of tensorflow.keras.layers.GlobalAveragePooling1D(). You can vote up the ones you like or vote down the ones you don't like, and go to the original project or source file by following the links above each example. You may also want to check out all available functions/classes of the module tensorflow.keras.layers , or try the search function

Example #1

Source File: model.py From cloudml-samples with Apache License 2.0

6 votes

def keras_estimator(model_dir, config, learning_rate, vocab_size):
  """Creates a Keras Sequential model with layers.

  Args:
    model_dir: (str) file path where training files will be written.
    config: (tf.estimator.RunConfig) Configuration options to save model.
    learning_rate: (int) Learning rate.
    vocab_size: (int) Size of the vocabulary in number of words.

  Returns:
      A keras.Model
  """
  model = models.Sequential()
  model.add(Embedding(vocab_size, 16))
  model.add(GlobalAveragePooling1D())
  model.add(Dense(16, activation=tf.nn.relu))
  model.add(Dense(1, activation=tf.nn.sigmoid))

  # Compile model with learning parameters.
  optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
  model.compile(
      optimizer=optimizer, loss='binary_crossentropy', metrics=['accuracy'])
  estimator = tf.keras.estimator.model_to_estimator(
      keras_model=model, model_dir=model_dir, config=config)
  return estimator

Example #2

Source File: embedding.py From nlp-journey with Apache License 2.0

5 votes

def _build_model(self):
        model = keras.Sequential([
            layers.Embedding(self.encoder.vocab_size, self.embedding_dim),
            layers.GlobalAveragePooling1D(),
            layers.Dense(16, activation='relu'),
            layers.Dense(1)
        ])
        model.compile(optimizer='adam',
                      loss=tf.keras.losses.BinaryCrossentropy(from_logits=True),
                      metrics=['accuracy'])
        model.summary()
        return model