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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
39 lines
1.3 KiB
C++
39 lines
1.3 KiB
C++
#include "caffe2/operators/index_hash_ops.h"
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namespace caffe2 {
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namespace {
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REGISTER_CPU_OPERATOR(IndexHash, IndexHashOp<CPUContext>);
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OPERATOR_SCHEMA(IndexHash)
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.NumInputs(1)
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.NumOutputs(1)
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.SetDoc(R"DOC(
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This operator translates a list of indices into a list of hashed indices.
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A seed can be fed as an argument to change the behavior of the hash function.
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If a modulo is specified, all the hashed indices will be modulo the
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specified number. All input and output indices are enforced to be positive.
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)DOC")
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.Input(0, "Indices", "Input feature indices.")
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.Output(0, "HashedIndices", "Hashed feature indices.")
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.AllowOneToOneInplace()
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.Arg("seed", "seed for the hash function")
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.Arg("modulo", "must be > 0, hashed ids will be modulo this number")
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.TensorInferenceFunction([](const OperatorDef& /* unused */,
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const vector<TensorShape>& in) {
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std::vector<TensorShape> out(1);
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std::vector<int64_t> output_dims = GetDimsVector(in[0]);
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out[0] = CreateTensorShape(output_dims, in[0].data_type());
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return out;
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});
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SHOULD_NOT_DO_GRADIENT(IndexHash);
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} // namespace
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} // namespace caffe2
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C10_EXPORT_CAFFE2_OP_TO_C10_CPU(
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IndexHash,
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"_caffe2::IndexHash(Tensor indices, int seed, int modulo) -> Tensor hashed_indices",
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caffe2::IndexHashOp<caffe2::CPUContext>);
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