/* 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. */ #pragma once #include #include #include #include #include #include "paddle/framework/attribute.h" #include "paddle/framework/grad_op_builder.h" #include "paddle/framework/op_desc.pb.h" #include "paddle/framework/scope.h" namespace paddle { namespace framework { // this class not only make proto but also init attribute checkers. class OpProtoAndCheckerMaker { public: OpProtoAndCheckerMaker(OpProto* proto, OpAttrChecker* op_checker) : proto_(proto), op_checker_(op_checker) {} ~OpProtoAndCheckerMaker() { PADDLE_ENFORCE(validated_, "should call Validate after build"); } void Validate() { validated_ = true; CheckNoDuplicatedInOutAttrs(); } protected: struct VariableBuilder { VarProto* var_; std::function on_multiple_; std::function on_temporary_; VariableBuilder& SetMultiple() { var_->set_multiple(true); on_multiple_(); return *this; } VariableBuilder& SetTemporary() { PADDLE_ENFORCE(bool(on_temporary_), "Cannot set temporary"); var_->set_temporary(true); on_temporary_(); return *this; } VariableBuilder& IgnoreGradient() { var_->set_ignore_gradient(true); return *this; } }; VariableBuilder AddInput(const std::string& name, const std::string& comment) { auto input = proto_->mutable_inputs()->Add(); *input->mutable_name() = name; *input->mutable_comment() = comment; return VariableBuilder{input, [=] { this->SetHasMultipleInput(); }, nullptr}; } VariableBuilder AddOutput(const std::string& name, const std::string& comment) { auto output = proto_->mutable_outputs()->Add(); *output->mutable_name() = name; *output->mutable_comment() = comment; return VariableBuilder{output, [=] { this->SetHasMultipleOutput(); }, [=] { this->SetHasTemporaryOutput(); }}; } template TypedAttrChecker& AddAttr(const std::string& name, const std::string& comment, bool generated = false) { auto attr = proto_->mutable_attrs()->Add(); *attr->mutable_name() = name; *attr->mutable_comment() = comment; attr->set_generated(generated); attr->set_type(AttrTypeID()); return op_checker_->AddAttrChecker(name); } void AddComment(const std::string& comment) { *(proto_->mutable_comment()) = comment; } private: void SetHasMultiple(const std::string& in_out, bool* flag) { if (!*flag) { AddAttr>(in_out + "_format", "The multiple index of " + in_out + "\n" R"DOC( This attribute is used by Paddle core framework. Paddle's Op support each input or output could be a list of variable. This attribute is used to show how that list organized. e.g. input = ["a", "b", "c", "d", "e", "f"] input_format = [0, 4, 5, 6] means The number of all input variables this op is six, and they are segmented into three inputs. The first input is input[0:4], second is input[4:5], third is input[5:6]. )DOC", /*generated*/ true); *flag = true; } } void SetHasMultipleInput() { SetHasMultiple("input", &has_multiple_input_); } void SetHasMultipleOutput() { SetHasMultiple("output", &has_multiple_output_); } void SetHasTemporaryOutput() { if (!has_temporary_output_) { AddAttr>("temporary_index", R"DOC(The temporary index of output. Not all output of Paddle Op is used by user. For faster computation, each op could output some its internal state to other op, other op could take that output to make compute faster. Add a mark to which output is temporary is helpful for future optimization. )DOC", /*generated*/ true) .SetDefault(std::vector()); has_temporary_output_ = true; } } void CheckNoDuplicatedInOutAttrs() { std::unordered_set names; auto checker = [&](const std::string& name) { PADDLE_ENFORCE(!names.count(name), "[%s] is duplicated", name); names.insert(name); }; for (auto& attr : proto_->attrs()) { checker(attr.name()); } for (auto& input : proto_->inputs()) { checker(input.name()); } for (auto& output : proto_->outputs()) { checker(output.name()); } } OpProto* proto_; OpAttrChecker* op_checker_; bool validated_{false}; bool has_multiple_input_{false}; bool has_multiple_output_{false}; bool has_temporary_output_{false}; }; class OpRegistry { using OpCreator = std::function; using VarIndexMap = std::unordered_map; using VarNameList = std::vector; public: template static void RegisterOp(const std::string& op_type) { op_creators()[op_type] = [] { return new OpType; }; OpAttrChecker& op_checker = op_checkers()[op_type]; OpProto& op_proto = protos()[op_type]; auto maker = ProtoMakerType(&op_proto, &op_checker); maker.Validate(); *op_proto.mutable_type() = op_type; PADDLE_ENFORCE( op_proto.IsInitialized(), "Fail to initialize %s's OpProto, because %s is not initialized", op_type, op_proto.InitializationErrorString()); VarIndexMaps()[op_type].reset(new VarIndexMap()); auto& varmap = *VarIndexMaps()[op_type]; int idx = 0; for (auto& var : op_proto.inputs()) { varmap[var.name()] = idx++; } idx = 0; for (auto& var : op_proto.outputs()) { varmap[var.name()] = idx++; } } template static void RegisterGradOp(const std::string& op_type, const std::string& grad_op_type) { op_creators()[grad_op_type] = [] { return new GradOpType; }; grad_ops()[op_type] = grad_op_type; } static std::shared_ptr CreateOp(const std::string& type, const VarNameList& inputs, const VarNameList& outputs, const AttributeMap& attrs) { auto op_create_it = op_creators().find(type); PADDLE_ENFORCE(op_create_it != op_creators().end(), "Operator %s cannot be found.", type); auto op = op_create_it->second(); op->type_ = type; op->inputs_ = inputs; op->outputs_ = outputs; op->attrs_ = attrs; op_checkers().at(type).Check(op->attrs_); GenerateTempVariableName(op); { auto var_index_it = VarIndexMaps().find(type); if (var_index_it != VarIndexMaps().end()) { op->in_out_idxs_ = var_index_it->second; } } op->Init(); return std::shared_ptr(op); } static std::shared_ptr CreateOp(const OpDesc& op_desc) { std::vector inputs; inputs.reserve((size_t)op_desc.inputs_size()); std::copy(op_desc.inputs().begin(), op_desc.inputs().end(), std::back_inserter(inputs)); std::vector outputs; outputs.reserve((size_t)op_desc.outputs_size()); std::copy(op_desc.outputs().begin(), op_desc.outputs().end(), std::back_inserter(outputs)); AttributeMap attrs; for (auto& attr : op_desc.attrs()) { attrs[attr.name()] = GetAttrValue(attr); } return CreateOp(op_desc.type(), inputs, outputs, attrs); } static std::shared_ptr CreateGradOp(const OperatorBase& op) { PADDLE_ENFORCE(!op.IsNetOp(), "Use framework::Backward to get backward ops"); std::shared_ptr grad_op(BuildGradOp(&op)); grad_op->Init(); return grad_op; } static std::unordered_map& protos() { static std::unordered_map protos_; return protos_; } static std::unordered_map& grad_ops() { static std::unordered_map grad_ops_; return grad_ops_; } static std::unordered_map>& VarIndexMaps() { static std::unordered_map> maps_; return maps_; } static std::unordered_map& op_creators() { static std::unordered_map op_creators_; return op_creators_; } private: static std::unordered_map& op_checkers() { static std::unordered_map op_checkers_; return op_checkers_; } static void GenerateTempVariableName(OperatorBase* op) { static std::atomic gUniqId(0UL); for (auto& outname : op->outputs_) { if (outname == kTempVarName) { outname += op->type_; outname += "@"; outname += std::to_string(gUniqId.fetch_add(1)); } } } }; class Registrar { public: void Touch() {} }; template class OpRegistrar : public Registrar { public: explicit OpRegistrar(const char* op_type) { OpRegistry::RegisterOp(op_type); } }; template class GradOpRegistrar : public Registrar { public: GradOpRegistrar(const char* op_type, const char* grad_op_type) { OpRegistry::RegisterGradOp(op_type, grad_op_type); } }; template class OpKernelRegistrar : public Registrar { public: explicit OpKernelRegistrar(const char* op_type) { ::paddle::framework::OperatorWithKernel::OpKernelKey key; key.place_ = PlaceType(); ::paddle::framework::OperatorWithKernel::AllOpKernels()[op_type][key].reset( new KernelType); } }; /** * check if MACRO is used in GLOBAL NAMESPACE. */ #define STATIC_ASSERT_GLOBAL_NAMESPACE(uniq_name, msg) \ struct __test_global_namespace_##uniq_name##__ {}; \ static_assert(std::is_same<::__test_global_namespace_##uniq_name##__, \ __test_global_namespace_##uniq_name##__>::value, \ msg) /** * Macro to Register Operator. */ #define REGISTER_OP(op_type, op_class, op_maker_class) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __reg_op__##op_type, "REGISTER_OP must be called in global namespace"); \ static ::paddle::framework::OpRegistrar \ __op_registrar_##op_type##__(#op_type); \ int TouchOpRegistrar_##op_type() { \ __op_registrar_##op_type##__.Touch(); \ return 0; \ } /** * Macro to Register Gradient Operator. */ #define REGISTER_GRADIENT_OP(op_type, grad_op_type, grad_op_class) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __reg_gradient_op__##op_type##_##grad_op_type, \ "REGISTER_GRADIENT_OP must be called in global namespace"); \ static ::paddle::framework::GradOpRegistrar \ __op_gradient_registrar_##op_type##_##grad_op_type##__(#op_type, \ #grad_op_type); \ int TouchOpGradientRegister_##op_type() { \ __op_gradient_registrar_##op_type##_##grad_op_type##__.Touch(); \ return 0; \ } /** * Macro to Register OperatorKernel. */ #define REGISTER_OP_KERNEL(op_type, DEVICE_TYPE, place_class, ...) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __reg_op_kernel_##op_type##_##DEVICE_TYPE##__, \ "REGISTER_OP_KERNEL must be called in global namespace"); \ static ::paddle::framework::OpKernelRegistrar \ __op_kernel_registrar_##op_type##_##DEVICE_TYPE##__(#op_type); \ int TouchOpKernelRegistrar_##op_type##_##DEVICE_TYPE() { \ __op_kernel_registrar_##op_type##_##DEVICE_TYPE##__.Touch(); \ return 0; \ } /** * Macro to Forbid user register Gradient Operator. */ #define NO_GRADIENT(op_type) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __reg_gradient_op__##op_type##_##op_type##_grad, \ "NO_GRADIENT must be called in global namespace") #define REGISTER_OP_GPU_KERNEL(op_type, ...) \ REGISTER_OP_KERNEL(op_type, GPU, ::paddle::platform::GPUPlace, __VA_ARGS__) #define REGISTER_OP_CPU_KERNEL(op_type, ...) \ REGISTER_OP_KERNEL(op_type, CPU, ::paddle::platform::CPUPlace, __VA_ARGS__) /** * Macro to mark what Operator and Kernel we will use and tell the compiler to * link them into target. */ #define USE_OP_ITSELF(op_type) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __use_op_itself_##op_type, \ "USE_OP_ITSELF must be called in global namespace"); \ extern int TouchOpRegistrar_##op_type(); \ static int use_op_itself_##op_type##_ __attribute__((unused)) = \ TouchOpRegistrar_##op_type() #define USE_OP_KERNEL(op_type, DEVICE_TYPE) \ STATIC_ASSERT_GLOBAL_NAMESPACE( \ __use_op_kernel_##op_type##_##DEVICE_TYPE##__, \ "USE_OP_KERNEL must be in global namespace"); \ extern int TouchOpKernelRegistrar_##op_type##_##DEVICE_TYPE(); \ static int use_op_kernel_##op_type##_##DEVICE_TYPE##_ \ __attribute__((unused)) = \ TouchOpKernelRegistrar_##op_type##_##DEVICE_TYPE() #ifdef PADDLE_ONLY_CPU #define USE_OP(op_type) \ USE_OP_ITSELF(op_type); \ USE_OP_KERNEL(op_type, CPU) #else #define USE_OP(op_type) \ USE_OP_ITSELF(op_type); \ USE_OP_KERNEL(op_type, CPU); \ USE_OP_KERNEL(op_type, GPU) #endif } // namespace framework } // namespace paddle