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Global average pooling operation for temporal data.

Inherits From: Layer, Module

Used in the notebooks

Used in the guide Used in the tutorials


input_shape = (2, 3, 4)
x = tf.random.normal(input_shape)
y = tf.keras.layers.GlobalAveragePooling1D()(x)
(2, 4)

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).