mx.symbol.SoftmaxActivation
¶
Description¶
Applies softmax activation to input. This is intended for internal layers.
This operator has been deprecated, please use softmax.
If mode = instance
, this operator will compute a softmax for each instance in the batch.
This is the default mode.
If mode = channel
, this operator will compute a k-class softmax at each position
of each instance, where k = num_channel
. This mode can only be used when the input array
has at least 3 dimensions.
This can be used for fully convolutional network, image segmentation, etc.
Example:
>>> input_array = mx.nd.array([[3., 0.5, -0.5, 2., 7.],
>>> [2., -.4, 7., 3., 0.2]])
>>> softmax_act = mx.nd.SoftmaxActivation(input_array)
>>> print softmax_act.asnumpy()
[[ 1.78322066e-02 1.46375655e-03 5.38485940e-04 6.56010211e-03 9.73605454e-01]
[ 6.56221947e-03 5.95310994e-04 9.73919690e-01 1.78379621e-02 1.08472735e-03]]
Usage¶
mx.symbol.SoftmaxActivation(...)
Arguments¶
Argument |
Description |
---|---|
|
NDArray-or-Symbol. The input array. |
|
{‘channel’, ‘instance’},optional, default=’instance’. Specifies how to compute the softmax. If set to
|
|
string, optional. Name of the resulting symbol. |
Value¶
out
The result mx.symbol
Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/nn/softmax_activation.cc#L59