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update doc of softmax_op. #3887

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Sep 6, 2017
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update doc of softmax_op. #3887

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26 changes: 22 additions & 4 deletions paddle/operators/softmax_op.cc
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Original file line number Diff line number Diff line change
Expand Up @@ -24,7 +24,7 @@ class SoftmaxOp : public framework::OperatorWithKernel {
protected:
void InferShape(const framework::InferShapeContext &ctx) const override {
PADDLE_ENFORCE(ctx.Input<Tensor>("X")->dims().size() == 2UL,
"The input of softmax op must be matrix");
"The input of softmax op must be a matrix.");
ctx.Output<Tensor>("Y")->Resize(ctx.Input<Tensor>("X")->dims());
}
};
Expand All @@ -34,9 +34,27 @@ class SoftmaxOpMaker : public framework::OpProtoAndCheckerMaker {
SoftmaxOpMaker(framework::OpProto *proto,
framework::OpAttrChecker *op_checker)
: OpProtoAndCheckerMaker(proto, op_checker) {
AddInput("X", "input of softmax");
AddOutput("Y", "output of softmax");
AddComment("Softmax Op");
AddInput("X",
"The input tensor of softmax. "
"2-D with shape [batch_size, input_feature_dimensions].");
AddOutput("Y", "The normalized values with the same shape as X.");
AddComment(R"DOC(
The input of softmax operator is a 2-D tensor with shape N x K (N is the
batch_size, K is the dimension of input feature). The output tensor has the
same shape as the input tensor.

For each row of the input tensor, the softmax operator squashes the
K-dimensional vector of arbitrary real values to a K-dimensional vector of real
values in the range [0, 1] that add up to 1. Specifically, it computes the
exponential of the given dimension and the sum of exponential values of all
the other dimensions in the K-dimensional vector input. Then the ratio of the
exponential of the given dimension and the sum of exponential values of all
the other dimensions is the output of the softmax operator.

For each row `i` and each column `j` in X, we have:
Y[i, j] = exp(X[i, j]) / sum_j(exp(X[i, j]))

)DOC");
}
};

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