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76 lines
2.8 KiB
76 lines
2.8 KiB
4 years ago
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/* Copyright (c) 2020 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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#ifdef PADDLE_WITH_XPU
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#include "paddle/fluid/operators/uniform_random_op.h"
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#include <string>
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#include "paddle/fluid/framework/generator.h"
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#include "paddle/fluid/framework/op_registry.h"
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#include "paddle/fluid/framework/operator.h"
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namespace paddle {
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namespace operators {
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template <typename T>
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class XPUUniformRandomKernel : public framework::OpKernel<T> {
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public:
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void Compute(const framework::ExecutionContext &ctx) const override {
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framework::Tensor *tensor = nullptr;
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auto out_var = ctx.OutputVar("Out");
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if (out_var->IsType<framework::LoDTensor>()) {
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tensor = out_var->GetMutable<framework::LoDTensor>();
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} else if (out_var->IsType<framework::SelectedRows>()) {
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auto shape = ctx.Attr<std::vector<int64_t>>("shape");
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auto *selected_rows = out_var->GetMutable<framework::SelectedRows>();
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tensor = selected_rows->mutable_value();
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tensor->Resize(framework::make_ddim(shape));
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selected_rows->mutable_rows()->reserve(shape[0]);
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} else {
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PADDLE_THROW(platform::errors::InvalidArgument(
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"Expected type of Output(out) in uniform_random_op must be "
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"LoDTensor, "
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"SelectedRows. But got unsupport type: %s.",
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framework::ToTypeName(out_var->Type())));
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}
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T *data = tensor->mutable_data<T>(ctx.GetPlace());
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int64_t size = tensor->numel();
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std::uniform_real_distribution<T> dist(
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static_cast<T>(ctx.Attr<float>("min")),
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static_cast<T>(ctx.Attr<float>("max")));
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unsigned int seed = static_cast<unsigned int>(ctx.Attr<int>("seed"));
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// TODO(pangyoki): implement GetXPURandomEngine to set different seeds on
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// corresponding XPU device.
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auto engine = framework::GetCPURandomEngine(seed);
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std::unique_ptr<T[]> data_cpu(new T[size]);
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for (int64_t i = 0; i < size; ++i) {
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data_cpu[i] = dist(*engine);
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}
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memory::Copy(BOOST_GET_CONST(platform::XPUPlace, ctx.GetPlace()), data,
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platform::CPUPlace(), reinterpret_cast<void *>(data_cpu.get()),
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size * sizeof(T));
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}
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};
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} // namespace operators
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} // namespace paddle
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REGISTER_OP_XPU_KERNEL(uniform_random,
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paddle::operators::XPUUniformRandomKernel<float>);
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#endif // PADDLE_WITH_XPU
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