wehub-resource-sync
63 lines
2.1 KiB
C++
63 lines
2.1 KiB
C++
// Copyright (c) 2022 PaddlePaddle Authors. All Rights Reserved.
|
|
//
|
|
// Licensed under the Apache License, Version 2.0 (the "License");
|
|
// you may not use this file except in compliance with the License.
|
|
// You may obtain a copy of the License at
|
|
//
|
|
// http://www.apache.org/licenses/LICENSE-2.0
|
|
//
|
|
// Unless required by applicable law or agreed to in writing, software
|
|
// distributed under the License is distributed on an "AS IS" BASIS,
|
|
// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
// See the License for the specific language governing permissions and
|
|
// limitations under the License.
|
|
|
|
#include "paddle/extension.h"
|
|
|
|
namespace {
|
|
std::vector<std::vector<int64_t>> InferShape(
|
|
std::vector<int64_t> x_shape,
|
|
std::vector<int64_t> y_shape,
|
|
const std::string &reduction,
|
|
const int &ignoreIndex,
|
|
const bool &inputIsLogProbability) {
|
|
// reduction type: Sum, Mean, None
|
|
if (reduction == "None") {
|
|
return {y_shape};
|
|
} else {
|
|
return {{1}};
|
|
}
|
|
}
|
|
|
|
std::vector<paddle::DataType> InferDtype(paddle::DataType x_dtype,
|
|
paddle::DataType y_dtype) {
|
|
return {x_dtype};
|
|
}
|
|
|
|
std::vector<paddle::Tensor> OpForward(const paddle::Tensor &x,
|
|
const paddle::Tensor &y) {
|
|
return {x};
|
|
}
|
|
|
|
std::vector<paddle::Tensor> OpBackward(const paddle::Tensor &x) { return {x}; }
|
|
} // namespace
|
|
|
|
// https://github.com/graphcore/popart/blob/sdk-release-2.5/willow/src/builder.cpp#L775
|
|
// type of `reduction` is std::string
|
|
// `ignoreIndex` is optional, if no need, need to remove it manually(which is a
|
|
// new custom op in paddle)
|
|
PD_BUILD_OP(custom_nll)
|
|
.Inputs({"X", "Y"})
|
|
.Outputs({"Out"})
|
|
.Attrs({"reduction: std::string",
|
|
"ignoreIndex: int",
|
|
"inputIsLogProbability: bool"})
|
|
.SetInferShapeFn(PD_INFER_SHAPE(InferShape))
|
|
.SetInferDtypeFn(PD_INFER_DTYPE(InferDtype))
|
|
.SetKernelFn(PD_KERNEL(OpForward));
|
|
|
|
PD_BUILD_GRAD_OP(custom_nll)
|
|
.Inputs({paddle::Grad("Out")})
|
|
.Outputs({paddle::Grad("X")})
|
|
.SetKernelFn(PD_KERNEL(OpBackward));
|