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``mx.nd.softmax.cross.entropy``
==============================================================
Description
----------------------
Calculate cross entropy of softmax output and one-hot label.
- This operator computes the cross entropy in two steps:
- Applies softmax function on the input array.
- Computes and returns the cross entropy loss between the softmax output and the labels.
- The softmax function and cross entropy loss is given by:
- Softmax Function:
.. math:: \text{softmax}(x)_i = \frac{exp(x_i)}{\sum_j exp(x_j)}
- Cross Entropy Function:
.. math:: \text{CE(label, output)} = - \sum_i \text{label}_i \log(\text{output}_i)
**Example**::
x = [[1, 2, 3],
[11, 7, 5]]
label = [2, 0]
softmax(x) = [[0.09003057, 0.24472848, 0.66524094],
[0.97962922, 0.01794253, 0.00242826]]
softmax_cross_entropy(data, label) = - log(0.66524084) - log(0.97962922) = 0.4281871
Arguments
------------------
+----------------------------------------+------------------------------------------------------------+
| Argument | Description |
+========================================+============================================================+
| ``data`` | NDArray-or-Symbol. |
| | |
| | Input data |
+----------------------------------------+------------------------------------------------------------+
| ``label`` | NDArray-or-Symbol. |
| | |
| | Input label |
+----------------------------------------+------------------------------------------------------------+
Value
----------
``out`` The result mx.ndarray
Link to Source Code: http://github.com/apache/incubator-mxnet/blob/1.6.0/src/operator/loss_binary_op.cc#L59