tf.keras.layers.AveragePooling1D

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Average pooling for temporal data.

tf.keras.layers.AveragePooling1D(
    pool_size=2, strides=None, padding='valid', data_format='channels_last',
    **kwargs
)

Arguments:

• pool_size: Integer, size of the average pooling windows.
• strides: Integer, or None. Factor by which to downscale. E.g. 2 will halve the input. If None, it will default to pool_size.
• padding: One of "valid" or "same" (case-insensitive).
• 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).

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:

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