View source on GitHub |
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). "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) . |
data_format='channels_last'
: 3D tensor with shape (batch_size, steps, features)
.data_format='channels_first'
: 3D tensor with shape (batch_size, features, steps)
.data_format='channels_last'
: 3D tensor with shape (batch_size, downsampled_steps, features)
.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