tf.contrib.layers.maxout

tf.contrib.layers.maxout(
    inputs, num_units, axis=-1, scope=None
)

"Maxout Networks" Ian J. Goodfellow, David Warde-Farley, Mehdi Mirza, Aaron Courville, Yoshua Bengio

Usually the operation is performed in the filter/channel dimension. This can also be used after fully-connected layers to reduce number of features.

Arguments
`inputs`	Tensor input
`num_units`	Specifies how many features will remain after maxout in the `axis` dimension (usually channel). This must be a factor of number of features.
`axis`	The dimension where max pooling will be performed. Default is the last dimension.
`scope`	Optional scope for variable_scope.

Returns
A `Tensor` representing the results of the pooling operation.

Raises
`ValueError`	if num_units is not multiple of number of features.

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Last updated 2020-10-01 UTC.

Arguments