mxnet.ndarray.softmax_cross_entropy¶
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mxnet.ndarray.softmax_cross_entropy(data=None, label=None, out=None, name=None, **kwargs)¶ 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:
\[\text{softmax}(x)_i = \frac{exp(x_i)}{\sum_j exp(x_j)}\]Cross Entropy Function:
\[\text{CE(label, output)} = - \sum_i \text{label}_i \log(\text{output}_i)\]
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
Defined in src/operator/loss_binary_op.cc:L59