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2e4c89eba9
Summary: 1) Adding MKL/AVX2 based implementation into perfkernels. This implementation is similar to caffe2/operators/batch_box_cox_op.cc 2) Migrating batch_box_cox_op of caffe2 use this implementation Test Plan: CI Differential Revision: D40208074 Pull Request resolved: https://github.com/pytorch/pytorch/pull/86569 Approved by: https://github.com/hyuen
40 lines
1015 B
C++
40 lines
1015 B
C++
#ifndef CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
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#define CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
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#include "caffe2/core/context.h"
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#include "caffe2/core/export_caffe2_op_to_c10.h"
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#include "caffe2/core/logging.h"
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#include "caffe2/core/operator.h"
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#include "caffe2/utils/math.h"
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C10_DECLARE_EXPORT_CAFFE2_OP_TO_C10(BatchBoxCox);
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namespace caffe2 {
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template <class Context>
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class BatchBoxCoxOp final : public Operator<Context> {
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public:
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USE_OPERATOR_CONTEXT_FUNCTIONS;
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template <class... Args>
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explicit BatchBoxCoxOp(Args&&... args)
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: Operator<Context>(std::forward<Args>(args)...),
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min_block_size_(
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this->template GetSingleArgument<int>("min_block_size", 256)) {}
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bool RunOnDevice() override {
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return DispatchHelper<TensorTypes<float, double>>::call(this, Input(DATA));
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}
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template <typename T>
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bool DoRunWithType();
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protected:
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std::size_t min_block_size_;
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INPUT_TAGS(DATA, LAMBDA1, LAMBDA2);
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};
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} // namespace caffe2
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#endif // CAFFE_OPERATORS_BATCH_BOX_COX_OPS_H_
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