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tf.keras.layers.GlobalAveragePooling1D

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Global average pooling operation for temporal data.

tf.keras.layers.GlobalAveragePooling1D(
    data_format='channels_last', **kwargs
)

Examples:

input_shape = (2, 3, 4)
x = tf.random.normal(input_shape)
y = tf.keras.layers.GlobalAveragePooling1D()(x)
print(y.shape)
(2, 4)
Arguments
data_format A string, one of channels_last (default) or channels_first. The ordering of the dimensions in the inputs. channels_last corresponds to inputs with shape (batch, steps, features) while channels_first corresponds to inputs with shape (batch, features, steps).

Call arguments:

  • inputs: A 3D tensor.
  • mask: Binary tensor of shape (batch_size, steps) indicating whether a given step should be masked (excluded from the average).

Input shape:

  • If data_format='channels_last': 3D tensor with shape: (batch_size, steps, features)
  • If data_format='channels_first': 3D tensor with shape: (batch_size, features, steps)

Output shape:

2D tensor with shape (batch_size, features).

© 2020 The TensorFlow Authors. All rights reserved.
Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r2.3/api_docs/python/tf/keras/layers/GlobalAveragePooling1D