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c2402a9257
Just a change pytorch/tree/master -> pytorch/tree/main pytorch/blob/master -> pytorch/blob/main Pull Request resolved: https://github.com/pytorch/pytorch/pull/100129 Approved by: https://github.com/huydhn
92 lines
1.9 KiB
C++
92 lines
1.9 KiB
C++
#include "caffe2/operators/exp_op.h"
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#include <string>
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#include <vector>
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namespace caffe2 {
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REGISTER_CPU_OPERATOR(
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Exp,
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UnaryElementwiseOp<TensorTypes<float>, CPUContext, ExpFunctor<CPUContext>>);
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OPERATOR_SCHEMA(Exp)
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.NumInputs(1)
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.NumOutputs(1)
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.AllowInplace({{0, 0}})
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.IdenticalTypeAndShape()
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.SetDoc(R"DOC(
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Calculates the exponential of the given input tensor ($exp(x)$), element-wise. This
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operation can be done in an in-place fashion too, by providing the same input
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and output blobs.
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Github Link:
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- https://github.com/pytorch/pytorch/blob/main/caffe2/operators/exp_op.cc
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<details>
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<summary> <b>Example</b> </summary>
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**Code**
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```
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workspace.ResetWorkspace()
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op = core.CreateOperator(
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"Exp",
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["X"],
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["X"],
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)
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workspace.FeedBlob("X", (np.random.rand(3,3)).astype(np.float32))
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print("X before running op:", workspace.FetchBlob("X"))
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workspace.RunOperatorOnce(op)
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print("X after running op:", workspace.FetchBlob("X"))
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```
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**Result**
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```
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X before running op:
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[[0.5821691 0.07719802 0.50159824]
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[0.40952456 0.36788362 0.84887683]
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[0.02472685 0.65730894 0.9066397 ]]
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X after running op:
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[[1.7899168 1.080256 1.6513585]
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[1.5061016 1.4446739 2.3370204]
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[1.0250351 1.9295927 2.4759884]]
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```
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</details>
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)DOC")
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.Input(0, "X", "*(type: Tensor`<float>`)* Input tensor.")
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.Output(
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0,
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"Y",
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"*(type: Tensor`<float>`)* The exponential of the input tensor computed "
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"element-wise.")
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.InheritOnnxSchema();
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namespace {
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class GetExpGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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std::vector<OperatorDef> GetGradientDefs() override {
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return SingleGradientDef(
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"Mul",
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"",
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std::vector<std::string>{O(0), GO(0)},
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std::vector<std::string>{GI(0)});
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}
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};
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} // namespace
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REGISTER_GRADIENT(Exp, GetExpGradient);
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} // namespace caffe2
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