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tf.keras.layers.AveragePooling1D

Average pooling for temporal data.

Inherits From: Layer, Module

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). "valid" means no padding. "same" results in padding evenly to the left/right or up/down of the input such that output has the same height/width dimension as the input.
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).

© 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/r2.4/api_docs/python/tf/keras/layers/AveragePooling1D