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Adds a maxout op from https://arxiv.org/abs/1302.4389
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. |