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93 lines
3.2 KiB
93 lines
3.2 KiB
// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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//
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// Licensed under the Apache License, Version 2.0 (the "License");
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// you may not use this file except in compliance with the License.
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// You may obtain a copy of the License at
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//
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// http://www.apache.org/licenses/LICENSE-2.0
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//
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// Unless required by applicable law or agreed to in writing, software
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// distributed under the License is distributed on an "AS IS" BASIS,
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// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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// See the License for the specific language governing permissions and
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// limitations under the License.
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#pragma once
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#include <string>
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#include <vector>
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#include "paddle/fluid/framework/eigen.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/platform/enforce.h"
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namespace paddle {
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namespace operators {
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using Tensor = framework::Tensor;
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template <typename T>
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typename std::enable_if<std::is_same<T, bool>::value>::type CopyVecotorToTensor(
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const char* value_name, framework::Tensor* out,
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const framework::ExecutionContext& ctx) {
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// If attribute value dtype is vector<bool>, it will be converted to
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// vector<int>.
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// at the same time, we can not use vector<bool> to hold the value, because
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// the c++ use bit value to replace byte value.
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auto values = ctx.Attr<std::vector<int>>(value_name);
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framework::TensorFromVector(values, ctx.device_context(), out);
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// use the array to replace to vector
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bool* array_ptr = new T[values.size()];
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for (unsigned int i = 0; i < values.size(); i++) {
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array_ptr[i] = static_cast<T>(values[i]);
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}
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framework::TensorFromArray(array_ptr, values.size(), ctx.device_context(),
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out);
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delete[] array_ptr;
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}
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template <typename T>
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typename std::enable_if<!std::is_same<T, bool>::value>::type
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CopyVecotorToTensor(const char* value_name, framework::Tensor* out,
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const framework::ExecutionContext& ctx) {
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auto values = ctx.Attr<std::vector<T>>(value_name);
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framework::TensorFromVector(values, ctx.device_context(), out);
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}
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template <typename T>
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class AssignValueKernel : public framework::OpKernel<T> {
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public:
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virtual void Compute(const framework::ExecutionContext& ctx) const {
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auto shape = ctx.Attr<std::vector<int>>("shape");
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auto* out = ctx.Output<framework::Tensor>("Out");
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int dtype = ctx.Attr<int>("dtype");
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const char* value_name = nullptr;
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switch (dtype) {
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case framework::proto::VarType::BOOL:
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value_name = "bool_values";
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break;
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case framework::proto::VarType::INT32:
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value_name = "int32_values";
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break;
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case framework::proto::VarType::FP32:
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value_name = "fp32_values";
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break;
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case framework::proto::VarType::INT64:
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value_name = "int64_values";
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break;
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default:
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PADDLE_THROW(platform::errors::Unimplemented(
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"Unsupported data type(code %d) for AssignValue operator, only "
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"supports bool, int32, float32 and int64.",
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dtype));
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break;
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}
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CopyVecotorToTensor<T>(value_name, out, ctx);
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out->Resize(framework::make_ddim(shape));
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}
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};
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} // namespace operators
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} // namespace paddle
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