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27cc11226d
Summary: Pull Request resolved: https://github.com/pytorch/pytorch/pull/68365 title. broadcast fastpath has been running fine for the enabled ops for a while now, so make it the default for these ops. Test Plan: diff is a no-op, so sandcastle Differential Revision: D32107847 fbshipit-source-id: b239b127b219985bf7df6a0eea2d879b8e9c79a4
79 lines
1.8 KiB
C++
79 lines
1.8 KiB
C++
#ifndef CAFFE2_OPERATORS_ELEMENTWISE_ADD_OP_H_
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#define CAFFE2_OPERATORS_ELEMENTWISE_ADD_OP_H_
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#include <algorithm>
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#include <functional>
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#include <vector>
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#include "caffe2/operators/elementwise_ops.h"
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#include "caffe2/operators/elementwise_ops_utils.h"
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#include "caffe2/utils/math.h"
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namespace caffe2 {
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template <class Context>
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struct AddFunctor {
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template <typename TIn, typename TOut>
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bool Forward(
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const std::vector<int>& A_dims,
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const std::vector<int>& B_dims,
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const TIn* A,
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const TIn* B,
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TOut* C,
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Context* context) const {
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math::Add(
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A_dims.size(),
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A_dims.data(),
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B_dims.size(),
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B_dims.data(),
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A,
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B,
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C,
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context);
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return true;
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}
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template <typename TGrad, typename TIn, typename TOut>
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bool Backward(
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const std::vector<int>& A_dims,
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const std::vector<int>& B_dims,
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const TGrad* dC,
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const TIn* /* A */,
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const TIn* /* B */,
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const TOut* /* C */,
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TGrad* dA,
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TGrad* dB,
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Context* context) const {
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const std::vector<int> C_dims =
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elementwise_ops_utils::ComputeBinaryBroadcastForwardDims(
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A_dims, B_dims);
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std::vector<int> A_back_dims;
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std::vector<int> B_back_dims;
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elementwise_ops_utils::ComputeBinaryBroadcastBackwardDims(
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A_dims, B_dims, &A_back_dims, &B_back_dims);
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math::ReduceSum(
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C_dims.size(),
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C_dims.data(),
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A_back_dims.data(),
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TGrad(1),
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dC,
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dA,
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context,
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true);
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math::ReduceSum(
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C_dims.size(),
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C_dims.data(),
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B_back_dims.data(),
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TGrad(1),
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dC,
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dB,
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context,
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true);
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return true;
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}
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};
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} // namespace caffe2
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#endif // CAFFE2_OPERATORS_ELEMENTWISE_ADD_OP_H_
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