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112 lines
3.8 KiB
112 lines
3.8 KiB
/* Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
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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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http://www.apache.org/licenses/LICENSE-2.0
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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 <vector>
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#include "paddle/fluid/framework/data_type.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/operators/math/math_function.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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inline framework::DDim GetShape(const framework::ExecutionContext &ctx) {
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// 1. shape is a Tensor
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if (ctx.HasInput("ShapeTensor")) {
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auto *shape_tensor = ctx.Input<framework::LoDTensor>("ShapeTensor");
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auto *shape_data = shape_tensor->data<int>();
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framework::Tensor cpu_shape_tensor;
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if (platform::is_gpu_place(shape_tensor->place())) {
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TensorCopySync(*shape_tensor, platform::CPUPlace(), &cpu_shape_tensor);
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shape_data = cpu_shape_tensor.data<int>();
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}
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auto vec_shape =
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std::vector<int>(shape_data, shape_data + shape_tensor->numel());
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return framework::make_ddim(vec_shape);
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}
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// 2. shape is a list/tuple containing Tensor
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auto shape_tensor_list = ctx.MultiInput<framework::Tensor>("ShapeTensorList");
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if (shape_tensor_list.size() > 0) {
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std::vector<int> vec_shape;
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for (size_t i = 0; i < shape_tensor_list.size(); ++i) {
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auto tensor = shape_tensor_list[i];
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PADDLE_ENFORCE_EQ(
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tensor->dims(), framework::make_ddim({1}),
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"ShapeError: If the element type of 'shape' in FillConstantOp is "
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"Tensor, "
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"the element's shape must be [1]. But received the element's shape "
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"is [%s]",
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tensor->dims());
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if (platform::is_gpu_place(tensor->place())) {
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framework::Tensor temp;
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TensorCopySync(*tensor, platform::CPUPlace(), &temp);
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vec_shape.push_back(*temp.data<int>());
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} else {
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vec_shape.push_back(*tensor->data<int>());
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}
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}
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return framework::make_ddim(vec_shape);
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}
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// 3. shape is a list/tuple without containing Tensor
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auto vec_shape = ctx.Attr<std::vector<int64_t>>("shape");
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return framework::make_ddim(vec_shape);
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}
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template <typename T>
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class FillConstantKernel : public framework::OpKernel<T> {
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public:
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void Compute(const paddle::framework::ExecutionContext &ctx) const override {
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auto data_type =
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static_cast<framework::proto::VarType::Type>(ctx.Attr<int>("dtype"));
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auto value = ctx.Attr<float>("value");
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auto force_cpu = ctx.Attr<bool>("force_cpu");
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framework::Tensor *tensor = nullptr;
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framework::Variable *out_var = ctx.OutputVar("Out");
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auto shape = GetShape(ctx);
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if (out_var->IsType<framework::LoDTensor>()) {
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tensor = out_var->GetMutable<framework::LoDTensor>();
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tensor->Resize(shape);
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} else if (out_var->IsType<framework::SelectedRows>()) {
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tensor = out_var->GetMutable<framework::SelectedRows>()->mutable_value();
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tensor->Resize(shape);
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} else {
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PADDLE_THROW(
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"fill constant op's output only"
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"supports SelectedRows and LoDTensor");
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}
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if (force_cpu) {
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tensor->mutable_data(platform::CPUPlace(), data_type);
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} else {
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tensor->mutable_data(ctx.GetPlace(), data_type);
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}
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platform::DeviceContextPool &pool = platform::DeviceContextPool::Instance();
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auto &dev_ctx = *pool.Get(ctx.GetPlace());
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math::set_constant(dev_ctx, tensor, value);
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}
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};
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} // namespace operators
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} // namespace paddle
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