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a9b0a921d5
Summary: As GoogleTest `TEST` macro is non-compliant with it as well as `DEFINE_DISPATCH` All changes but the ones to `.clang-tidy` are generated using following script: ``` for i in `find . -type f -iname "*.c*" -or -iname "*.h"|xargs grep cppcoreguidelines-avoid-non-const-global-variables|cut -f1 -d:|sort|uniq`; do sed -i "/\/\/ NOLINTNEXTLINE(cppcoreguidelines-avoid-non-const-global-variables)/d" $i; done ``` Pull Request resolved: https://github.com/pytorch/pytorch/pull/62008 Reviewed By: driazati, r-barnes Differential Revision: D29838584 Pulled By: malfet fbshipit-source-id: 1b2f8602c945bd4ce50a9bfdd204755556e31d13
85 lines
2.1 KiB
C++
85 lines
2.1 KiB
C++
#include "caffe2/operators/flatten_op.h"
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namespace caffe2 {
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REGISTER_CPU_OPERATOR(Flatten, FlattenOp<CPUContext>);
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OPERATOR_SCHEMA(Flatten)
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.NumInputs(1)
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.NumOutputs(1)
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.TensorInferenceFunction(TensorInferenceForFlatten)
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.SetDoc(R"DOC(
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Flattens the input tensor into a 2D matrix. If input tensor has shape
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$(d_0, d_1, ..., d_n)$ then the output will have shape
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$\bigl((d_0 * d_1 * ... * d_{(axis-1)}), (d_{axis} * d_{(axis+1)} * ... * d_n)\bigr)$.
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Github Links:
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- https://github.com/pytorch/pytorch/blob/master/caffe2/operators/flatten_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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"Flatten",
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["X"],
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["Y"],
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axis=1
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)
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workspace.FeedBlob("X", np.random.rand(1,3,2,2))
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print("X:", workspace.FetchBlob("X"))
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workspace.RunOperatorOnce(op)
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print("Y:", workspace.FetchBlob("Y"))
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```
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**Result**
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```
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X: [[[[0.53432311 0.23734561]
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[0.56481598 0.52152617]]
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[[0.33662627 0.32472711]
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[0.17939016 0.97175851]]
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[[0.87226421 0.49045439]
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[0.92470531 0.30935077]]]]
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Y: [[0.53432311 0.23734561 0.56481598 0.52152617 0.33662627 0.32472711
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0.17939016 0.97175851 0.87226421 0.49045439 0.92470531 0.30935077]]
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```
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</details>
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)DOC")
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.Input(0, "X", "*(type: Tensor)* Input Tensor of rank >= axis.")
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.Output(
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0,
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"Y",
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"*(type: Tensor)* A 2D tensor with the contents of the input tensor, "
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"with input dimensions up to `axis` flattened to the outer dimension "
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"of the output and the remaining input dimensions flattened into the "
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"inner dimension of the output.")
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.Arg(
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"axis",
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"*(type: int; default: 1)* Indicates up to which input dimensions "
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"(exclusive) should be flattened to the outer dimension of the output.")
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.InheritOnnxSchema();
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class GetFlattenGradient : public GradientMakerBase {
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using GradientMakerBase::GradientMakerBase;
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vector<OperatorDef> GetGradientDefs() override {
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return SingleGradientDef(
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"ResizeLike", "", vector<string>{GO(0), I(0)}, vector<string>{GI(0)});
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}
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};
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REGISTER_GRADIENT(Flatten, GetFlattenGradient);
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} // namespace caffe2
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