TensorFlow 1 version
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    View source on GitHub
  
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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 | |
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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).
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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).
  TensorFlow 1 version
    View source on GitHub