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Paddle/paddle/fluid/operators/assign_value_op.h

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// Copyright (c) 2018 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.
#pragma once
#include <string>
#include <vector>
#include "paddle/fluid/framework/eigen.h"
#include "paddle/fluid/framework/op_registry.h"
#include "paddle/fluid/platform/enforce.h"
namespace paddle {
namespace operators {
using Tensor = framework::Tensor;
template <typename T>
typename std::enable_if<std::is_same<T, bool>::value>::type CopyVecotorToTensor(
const char* value_name, framework::Tensor* out,
const framework::ExecutionContext& ctx) {
// If attribute value dtype is vector<bool>, it will be converted to
// vector<int>.
// at the same time, we can not use vector<bool> to hold the value, because
// the c++ use bit value to replace byte value.
auto values = ctx.Attr<std::vector<int>>(value_name);
framework::TensorFromVector(values, ctx.device_context(), out);
// use the array to replace to vector
bool* array_ptr = new T[values.size()];
for (unsigned int i = 0; i < values.size(); i++) {
array_ptr[i] = static_cast<T>(values[i]);
}
framework::TensorFromArray(array_ptr, values.size(), ctx.device_context(),
out);
delete[] array_ptr;
}
template <typename T>
typename std::enable_if<!std::is_same<T, bool>::value>::type
CopyVecotorToTensor(const char* value_name, framework::Tensor* out,
const framework::ExecutionContext& ctx) {
auto values = ctx.Attr<std::vector<T>>(value_name);
framework::TensorFromVector(values, ctx.device_context(), out);
}
template <typename T>
class AssignValueKernel : public framework::OpKernel<T> {
public:
virtual void Compute(const framework::ExecutionContext& ctx) const {
auto shape = ctx.Attr<std::vector<int>>("shape");
auto* out = ctx.Output<framework::Tensor>("Out");
int dtype = ctx.Attr<int>("dtype");
const char* value_name = nullptr;
switch (dtype) {
case framework::proto::VarType::BOOL:
value_name = "bool_values";
break;
case framework::proto::VarType::INT32:
value_name = "int32_values";
break;
case framework::proto::VarType::FP32:
value_name = "fp32_values";
break;
case framework::proto::VarType::INT64:
value_name = "int64_values";
break;
default:
PADDLE_THROW("Unsupported dtype for assign_value_op: %d", dtype);
break;
}
CopyVecotorToTensor<T>(value_name, out, ctx);
out->Resize(framework::make_ddim(shape));
}
};
} // namespace operators
} // namespace paddle