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* add rename guard * add device_data_transform * add device_data_transform_test * modify GetExpectedKernelType * update operator.run * support test test_label_semantic_roles * optimize code * optimize code * rename GetActualKernelType to GetExpectedKernelType * fix chunk_eval_op and device_data_transform_test * add is_same_place to place * optimize code, refine rename_guard * refine rename guard, add GetKernelTypeForVar * optimize code * add some log * rename guard * use sub scope to create var * fix compile * add IsInitialized for Tensor * add VarIsTensor * fix op_registry_test * test * tmp disable priority * restore switch_kernel.md * code clean
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,46 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. | ||
| 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. */ | ||
|
|
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| #include "paddle/framework/device_data_transform.h" | ||
|
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| namespace paddle { | ||
| namespace framework { | ||
|
|
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| static const platform::DeviceContext* GetDeviceContext( | ||
| const platform::Place& src_place, const platform::Place& dst_place) { | ||
| platform::DeviceContextPool& pool = platform::DeviceContextPool::Instance(); | ||
|
|
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| if (platform::is_gpu_place(src_place) && platform::is_cpu_place(dst_place)) { | ||
| return pool.Get(src_place); | ||
| } else if (platform::is_cpu_place(src_place) && | ||
| platform::is_gpu_place(dst_place)) { | ||
| return pool.Get(dst_place); | ||
| } else { | ||
| PADDLE_THROW( | ||
| "Currently, model parallelism is only supported between CPU and CUDA"); | ||
| } | ||
| } | ||
|
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| Tensor* DeviceTransform(const Tensor& in, const platform::Place& dst_place) { | ||
| VLOG(3) << "DeviceTransform in, src_place " << in.place() | ||
| << " dst_place: " << dst_place; | ||
| Tensor* out = new Tensor(); | ||
| auto* dev_ctx = GetDeviceContext(in.place(), dst_place); | ||
| dev_ctx->Wait(); | ||
| CopyFrom(in, dst_place, *dev_ctx, out); | ||
| dev_ctx->Wait(); | ||
| return out; | ||
| } | ||
|
|
||
| } // namespace framework | ||
| } // namespace paddle |
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| @@ -0,0 +1,27 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. | ||
| 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. */ | ||
|
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| #pragma once | ||
|
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| #include "paddle/framework/lod_tensor.h" | ||
| #include "paddle/framework/tensor.h" | ||
| #include "paddle/framework/tensor_util.h" | ||
| #include "paddle/platform/device_context.h" | ||
|
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| namespace paddle { | ||
| namespace framework { | ||
|
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| Tensor* DeviceTransform(const Tensor& in, const platform::Place& dst_place); | ||
|
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| } // namespace framework | ||
| } // namespace paddle |
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| Original file line number | Diff line number | Diff line change |
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| @@ -0,0 +1,168 @@ | ||
| /* Copyright (c) 2016 PaddlePaddle Authors. All Rights Reserve. | ||
| 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. */ | ||
|
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| #include "gtest/gtest.h" | ||
|
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| #include "paddle/framework/init.h" | ||
| #include "paddle/framework/lod_tensor.h" | ||
| #include "paddle/framework/op_info.h" | ||
| #include "paddle/framework/op_registry.h" | ||
| #include "paddle/operators/elementwise_op_function.h" | ||
| #include "paddle/operators/math/math_function.h" | ||
| #include "paddle/platform/device_context.h" | ||
|
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| namespace paddle { | ||
| namespace framework { | ||
|
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| template <typename T> | ||
| struct AddFunctor { | ||
| inline HOSTDEVICE T operator()(T a, T b) const { return a + b; } | ||
| }; | ||
|
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| class OpKernelTestProtoAndCheckerMaker : public OpProtoAndCheckerMaker { | ||
| public: | ||
| OpKernelTestProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker) | ||
| : OpProtoAndCheckerMaker(proto, op_checker) { | ||
| AddInput("input", "input1 of test op"); | ||
| AddOutput("output", "output of test op"); | ||
| AddAttr<bool>("use_gpu", "force to use gpu kernel").SetDefault(false); | ||
| AddComment("This is test op"); | ||
| } | ||
| }; | ||
|
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| class TestOpWithKernel : public OperatorWithKernel { | ||
| public: | ||
| using OperatorWithKernel::OperatorWithKernel; | ||
|
|
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| protected: | ||
| void InferShape(framework::InferShapeContext* ctx) const override {} | ||
| OpKernelType GetExpectedKernelType( | ||
| const ExecutionContext& ctx) const override { | ||
| if (Attr<bool>("use_gpu")) { | ||
| VLOG(3) << "force use gpu kernel"; | ||
| return OpKernelType(proto::DataType::FP32, platform::CUDAPlace(0)); | ||
| } else { | ||
| VLOG(3) << "use default kernel"; | ||
| return OpKernelType(proto::DataType::FP32, | ||
| ctx.Input<Tensor>("input")->place()); | ||
| } | ||
| } | ||
| }; | ||
|
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| template <typename DeviceContext, typename T> | ||
| class TestKernel : public OpKernel<float> { | ||
| public: | ||
| void Compute(const ExecutionContext& ctx) const { | ||
| std::cout << ctx.op().DebugString() << std::endl; | ||
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| const Tensor* input = ctx.Input<Tensor>("input"); | ||
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| std::cout << "input place:" << input->place() << std::endl; | ||
| auto* output = ctx.Output<framework::LoDTensor>("output"); | ||
| output->Resize(input->dims()); | ||
| output->mutable_data<T>(ctx.GetPlace()); | ||
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| operators::TransformFunctor<AddFunctor<T>, T, DeviceContext> functor( | ||
| input, input, output, ctx.template device_context<DeviceContext>(), | ||
| AddFunctor<T>()); | ||
| functor.Run(); | ||
| } | ||
| }; | ||
|
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| } // namespace framework | ||
| } // namespace paddle | ||
|
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| REGISTER_OP_WITHOUT_GRADIENT( | ||
| test_op, paddle::framework::TestOpWithKernel, | ||
| paddle::framework::OpKernelTestProtoAndCheckerMaker); | ||
| REGISTER_OP_CPU_KERNEL( | ||
| test_op, | ||
| paddle::framework::TestKernel<paddle::platform::CPUDeviceContext, float>); | ||
| REGISTER_OP_CUDA_KERNEL( | ||
| test_op, | ||
| paddle::framework::TestKernel<paddle::platform::CUDADeviceContext, float>); | ||
|
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| static void BuildVar(const std::string& param_name, | ||
| std::initializer_list<const char*> arguments, | ||
| paddle::framework::proto::OpDesc::Var* var) { | ||
| var->set_parameter(param_name); | ||
| for (auto& arg_name : arguments) { | ||
| *var->mutable_arguments()->Add() = arg_name; | ||
| } | ||
| } | ||
|
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| TEST(Operator, CPUtoGPU) { | ||
| using namespace paddle::framework; | ||
| using namespace paddle::platform; | ||
|
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| ASSERT_EQ(InitDevices({"CPU", "GPU:0"}), true); | ||
|
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| paddle::framework::Scope scope; | ||
| paddle::platform::CPUPlace cpu_place; | ||
|
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| // create an op to run on CPU | ||
| paddle::framework::proto::OpDesc cpu_op_desc; | ||
| cpu_op_desc.set_type("test_op"); | ||
| BuildVar("input", {"IN1"}, cpu_op_desc.add_inputs()); | ||
| BuildVar("output", {"OUT1"}, cpu_op_desc.add_outputs()); | ||
|
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| auto cpu_op = paddle::framework::OpRegistry::CreateOp(cpu_op_desc); | ||
| // prepare input | ||
| auto* in_t = scope.Var("IN1")->GetMutable<LoDTensor>(); | ||
| auto* src_ptr = in_t->mutable_data<float>({2, 3}, CPUPlace()); | ||
| for (int i = 0; i < 2 * 3; ++i) { | ||
| src_ptr[i] = static_cast<float>(i); | ||
| } | ||
|
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| // get output | ||
| auto* output = scope.Var("OUT1"); | ||
| cpu_op->Run(scope, cpu_place); | ||
|
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| auto* output_ptr = output->Get<LoDTensor>().data<float>(); | ||
| for (int i = 0; i < 2 * 3; ++i) { | ||
| ASSERT_EQ(output_ptr[i], static_cast<float>(i) * 2); | ||
| } | ||
|
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| // create an op to run on GPU | ||
| paddle::framework::proto::OpDesc gpu_op_desc; | ||
| gpu_op_desc.set_type("test_op"); | ||
| BuildVar("input", {"OUT1"}, gpu_op_desc.add_inputs()); | ||
| BuildVar("output", {"OUT2"}, gpu_op_desc.add_outputs()); | ||
|
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| auto attr = gpu_op_desc.mutable_attrs()->Add(); | ||
| attr->set_name("use_gpu"); | ||
| attr->set_type(paddle::framework::proto::AttrType::BOOLEAN); | ||
| attr->set_b(true); | ||
|
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| auto gpu_op = paddle::framework::OpRegistry::CreateOp(gpu_op_desc); | ||
|
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| paddle::platform::CUDAPlace cuda_place(0); | ||
| // get output | ||
| auto* output2 = scope.Var("OUT2"); | ||
| gpu_op->Run(scope, cuda_place); | ||
|
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| // auto* output2_ptr = output2->Get<LoDTensor>().data<float>(); | ||
| DeviceContextPool& pool = DeviceContextPool::Instance(); | ||
| auto dev_ctx = pool.Get(cuda_place); | ||
|
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| paddle::framework::Tensor output_tensor; | ||
| CopyFrom(output2->Get<LoDTensor>(), paddle::platform::CPUPlace(), *dev_ctx, | ||
| &output_tensor); | ||
|
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| dev_ctx->Wait(); | ||
| float* output2_ptr = output_tensor.data<float>(); | ||
| for (int i = 0; i < 2 * 3; ++i) { | ||
| ASSERT_EQ(output2_ptr[i], static_cast<float>(i) * 4); | ||
| } | ||
| } |
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