tf.keras.layers.GlobalAveragePooling1D
| View source on GitHub |
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).
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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/GlobalAveragePooling1D