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change CinnLanuchOp inherit from OperatorWithKernel
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| /* Copyright (c) 2021 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. */ | ||
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| #include "paddle/fluid/operators/cinn_launch_op.h" | ||
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| /* see [Why use single type kernel] */ | ||
| REGISTER_OP_CUDA_KERNEL(cinn_launch, | ||
| paddle::operators::CinnLaunchOpKernel< | ||
| paddle::platform::CUDADeviceContext, float>); |
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| // Copyright (c) 2021 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. | ||
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| #pragma once | ||
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| #include <memory> | ||
| #include <string> | ||
| #include <unordered_map> | ||
| #include "cinn/hlir/framework/graph_compiler.h" | ||
| #include "cinn/hlir/framework/scope.h" | ||
| #include "cinn/runtime/cinn_runtime.h" | ||
| #include "paddle/fluid/framework/ir/graph.h" | ||
| #include "paddle/fluid/framework/op_registry.h" | ||
| #include "paddle/fluid/framework/operator.h" | ||
| #include "paddle/fluid/framework/paddle2cinn/cinn_compiler.h" | ||
| #include "paddle/fluid/operators/cinn_launch_op_helper.h" | ||
| #include "paddle/fluid/string/string_helper.h" | ||
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| namespace paddle { | ||
| namespace operators { | ||
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| static constexpr char kX[] = "X"; | ||
| static constexpr char kOutputs[] = "Out"; | ||
| static constexpr char kCompilationKey[] = "compilation_key"; | ||
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| using LoDTensor = framework::LoDTensor; | ||
| using Name2ConstTensor = std::map<std::string, const LoDTensor*>; | ||
| using CinnTensor = cinn::hlir::framework::Tensor; | ||
| using Name2CinnTensor = std::unordered_map<std::string, CinnTensor>; | ||
| using framework::paddle2cinn::CinnCompiler; | ||
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| template <typename DeviceContext, typename T> | ||
| class CinnLaunchOpKernel : public framework::OpKernel<T> { | ||
| public: | ||
| void Compute(const framework::ExecutionContext& ctx) const override { | ||
| // Step 1. Find graph object and prepare input | ||
| PADDLE_ENFORCE_EQ(ctx.HasAttr(kCompilationKey), true, | ||
| platform::errors::NotFound( | ||
| "No Attribute(%s) found for CinnLaunchOp operator.", | ||
| kCompilationKey)); | ||
| const auto& compilation_key = | ||
| ctx.template Attr<std::string>(kCompilationKey); | ||
| VLOG(2) << "CinnLaunchOp compilation_key:" << compilation_key; | ||
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| const auto& graph = CinnCompiler::GetInstance()->FindGraph(compilation_key); | ||
| auto input_variable_names = ctx.InputNames(kX); | ||
| Name2ConstTensor input_tensors = | ||
| details::GetConstTensors(ctx.scope(), input_variable_names); | ||
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| // Step 2. Get compilation result of the graph | ||
| auto target = details::PlaceToCinnTarget(ctx.GetPlace()); | ||
| const auto& cinn_compiled_object = | ||
| CinnCompiler::GetInstance()->Compile(graph, input_tensors, target); | ||
| VLOG(2) << "CinnLaunchOp compile graph done on " << ctx.GetPlace(); | ||
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| const auto& cinn_runtime_program = cinn_compiled_object.runtime_program; | ||
| const auto& compiled_scope = *(cinn_compiled_object.scope.get()); | ||
| const auto& paddle2cinn_varmap = cinn_compiled_object.paddle2cinn_varmap; | ||
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| // Step 3. Initialize all variables of the compilation runtime program | ||
| // in paddle, and pack them into execution arguments | ||
| VLOG(2) << "CinnLaunchOp prepare execution arguments"; | ||
| std::map<std::string, cinn_pod_value_t> name2argument; | ||
| std::vector<std::unique_ptr<cinn_buffer_t>> hold_buffers; | ||
| // prepare input variables | ||
| Name2CinnTensor input_compiled_tensors = details::GetCompiledTensors( | ||
| input_variable_names, compiled_scope, paddle2cinn_varmap); | ||
| details::CheckTensorEquivalent(input_tensors, input_compiled_tensors); | ||
| details::AppendExecutionArguments(ctx.scope(), input_variable_names, | ||
| paddle2cinn_varmap, &name2argument, | ||
| &hold_buffers); | ||
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| // prepare output variables | ||
| auto output_variable_names = ctx.OutputNames(kOutputs); | ||
| Name2CinnTensor output_compiled_tensors = details::GetCompiledTensors( | ||
| output_variable_names, compiled_scope, paddle2cinn_varmap); | ||
| details::InitializeOutputVar(ctx.scope(), ctx.GetPlace(), | ||
| output_compiled_tensors); | ||
| Name2ConstTensor output_tensors = | ||
| details::GetConstTensors(ctx.scope(), output_variable_names); | ||
| details::CheckTensorEquivalent(output_tensors, output_compiled_tensors); | ||
| details::AppendExecutionArguments(ctx.scope(), output_variable_names, | ||
| paddle2cinn_varmap, &name2argument, | ||
| &hold_buffers); | ||
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| // prepare temporary variables | ||
| auto temp_variable_names = | ||
| details::SeperateTempVar(compiled_scope, paddle2cinn_varmap, | ||
| input_variable_names, output_variable_names); | ||
| auto temp_scope = ctx.scope().NewTmpScope(); | ||
| if (!temp_variable_names.empty()) { | ||
| details::InitializeTempVar(temp_variable_names, compiled_scope, | ||
| ctx.GetPlace(), temp_scope.get()); | ||
| details::AppendExecutionArguments(*temp_scope, temp_variable_names, | ||
| paddle2cinn_varmap, &name2argument, | ||
| &hold_buffers); | ||
| } | ||
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| // Step 4. Launch CINN to execute the compilation runtime program | ||
| cinn_runtime_program->Execute(&name2argument); | ||
| VLOG(2) << "CinnLaunchOp launch runtime_program execution done."; | ||
| } | ||
| }; | ||
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| } // namespace operators | ||
| } // namespace paddle |
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