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[Meta Schedule][M3a] Instruction and Trace (#8615)
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| /* | ||
| * Licensed to the Apache Software Foundation (ASF) under one | ||
| * or more contributor license agreements. See the NOTICE file | ||
| * distributed with this work for additional information | ||
| * regarding copyright ownership. The ASF licenses this file | ||
| * to you 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. | ||
| */ | ||
| #ifndef TVM_TIR_SCHEDULE_INSTRUCTION_H_ | ||
| #define TVM_TIR_SCHEDULE_INSTRUCTION_H_ | ||
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| #include <tvm/node/reflection.h> | ||
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| #include <utility> | ||
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| namespace tvm { | ||
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| // Forward declaration | ||
| template <typename, typename> | ||
| class AttrRegistry; | ||
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| namespace tir { | ||
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| // Forward declaration | ||
| class Schedule; | ||
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| /*! | ||
| * \brief Type of the functor that applies the instruction to a TensorIR schedule | ||
| * \param sch The schedule to be applied on | ||
| * \param inputs The input random variables | ||
| * \param attrs Instruction attributes | ||
| * \param decision Decisions made on the instruction | ||
| * \return The functor returns an array of output random variables | ||
| */ | ||
| using FInstructionApply = runtime::TypedPackedFunc<Array<ObjectRef>( | ||
| Schedule sch, const Array<ObjectRef>& inputs, const Array<ObjectRef>& attrs, | ||
| const Optional<ObjectRef>& decision)>; | ||
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| /*! | ||
| * \brief Type of the functor that converts the instruction to a statement in python syntax | ||
| * \param inputs Names of the input random variables | ||
| * \param attrs Instruction attributes | ||
| * \param decisions Decisions made on the instruction | ||
| * \param outputs Names of the output random variables | ||
| * \return A string representing the python api call | ||
| */ | ||
| using FInstructionAsPython = runtime::TypedPackedFunc<String( | ||
| const Array<ObjectRef>& inputs, const Array<ObjectRef>& attrs, | ||
| const Optional<ObjectRef>& decision, const Array<String>& outputs)>; | ||
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| /*! | ||
| * \brief Type of the functor that serialize its attributes to JSON | ||
| * \param attrs The attributes to be serialized | ||
| * \return An array, serialized attributes | ||
| * \note This functor is nullable | ||
| */ | ||
| using FInstructionAttrsAsJSON = runtime::TypedPackedFunc<ObjectRef(Array<ObjectRef> attrs)>; | ||
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| /*! | ||
| * \brief Type of the functor that deserialize its attributes from JSON | ||
| * \param json_attrs The attributes to be serialized | ||
| * \return An array, deserialized attributes | ||
| * \note This functor is nullable | ||
| */ | ||
| using FInstructionAttrsFromJSON = runtime::TypedPackedFunc<Array<ObjectRef>(ObjectRef json_attrs)>; | ||
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| /*! | ||
| * \brief Kind of an instruction, e.g. Split, Reorder, etc. | ||
| * Besides the name, every kind of instruction has its own properties, including: | ||
| * 1) A boolean indicating if the instruction is pure, i.e. change nothing in the schedule state | ||
| * 2) A functor that applies the instruction to a TensorIR schedule | ||
| * 3) A functor that converts the instruction to a statement in python syntax | ||
| * 4) A functor that serialize its attributes to JSON | ||
| * 5) A functor that deserialize its attributes from JSON | ||
| * | ||
| * Unlike `tvm::OpNode`, `InstructionKindNode` doesn't support unstructured properties, | ||
| * mainly because there is no such usecase yet to add any other property. | ||
| */ | ||
| class InstructionKindNode : public runtime::Object { | ||
| public: | ||
| /*! \brief The name of a kind of instructions */ | ||
| String name; | ||
| /*! | ||
| * \brief Indicates if the instruction is pure, i.e. removing it alone doesn't mutate the schedule | ||
| * state. For example, the instruction `GetBlock` is pure because it changes | ||
| * nothing, while `ComputeInline` is not because removing it leads to a different resulting | ||
| * schedule. | ||
| */ | ||
| bool is_pure{false}; | ||
| /*! \brief A functor that applies the instruction to a TensorIR schedule */ | ||
| FInstructionApply f_apply_to_schedule{nullptr}; | ||
| /*! \brief A functor that converts the instruction to a statement in python syntax */ | ||
| FInstructionAsPython f_as_python{nullptr}; | ||
| /*! | ||
| * \brief A functor that serialize its attributes to JSON | ||
| * \note If the functor is null, it means no conversion is needed | ||
| */ | ||
| FInstructionAttrsAsJSON f_attrs_as_json{nullptr}; | ||
| /*! | ||
| * \brief A functor that deserialize its attributes from JSON | ||
| * \note If the functor is null, it means no conversion is needed | ||
| */ | ||
| FInstructionAttrsFromJSON f_attrs_from_json{nullptr}; | ||
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| void VisitAttrs(tvm::AttrVisitor* v) { | ||
| v->Visit("name", &name); | ||
| v->Visit("_is_pure", &is_pure); | ||
| // not visited: f_apply_to_schedule | ||
| // not visited: f_as_python | ||
| // not visited: f_attrs_as_json | ||
| // not visited: f_attrs_from_json | ||
| } | ||
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| static constexpr const char* _type_key = "tir.InstructionKind"; | ||
| TVM_DECLARE_FINAL_OBJECT_INFO(InstructionKindNode, runtime::Object); | ||
| }; | ||
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| /*! | ||
| * \brief Managed reference to InstructionKindNode | ||
| * \sa InstructionKindNode | ||
| */ | ||
| class InstructionKind : public runtime::ObjectRef { | ||
| public: | ||
| /*! | ||
| * \brief Retrieve an InstructionKind using its name | ||
| * \param name The registered name of the InstructionKind | ||
| * \return The InstructionKind retrieved | ||
| */ | ||
| static InstructionKind Get(const String& name); | ||
| TVM_DEFINE_OBJECT_REF_METHODS(InstructionKind, runtime::ObjectRef, InstructionKindNode); | ||
| }; | ||
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| /*! \brief Schedule instructions each corresponds to a schedule primitive */ | ||
| class InstructionNode : public runtime::Object { | ||
| public: | ||
| /*! \brief The kind of the instruction */ | ||
| InstructionKind kind; | ||
| /*! | ||
| * \brief The input random variables of the instruction, and the type of each element can be one | ||
| * of the following: | ||
| * - BlockRV | ||
| * - LoopRV | ||
| * - ExprRV | ||
| * - FloatImm | ||
| * - IntImm | ||
| * - String | ||
| * - null pointer | ||
| */ | ||
| Array<ObjectRef> inputs; | ||
| /*! | ||
| * \brief The attributes of the instruction. Similar to attributes of an operator, | ||
| * attributes of an instruction are arbitrary constant metadata required by the instructions. | ||
| * For example, the name of the block to be retrieved in `GetBlock`. | ||
| */ | ||
| Array<ObjectRef> attrs; | ||
| /*! \brief The output random variables of the instruction, and the type of each element can be one | ||
| * of the following: | ||
| * - BlockRV | ||
| * - LoopRV | ||
| * - ExprRV, atomic variables only, won't be constants or composite PrimExpr | ||
| */ | ||
| Array<ObjectRef> outputs; | ||
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| void VisitAttrs(tvm::AttrVisitor* v) { | ||
| v->Visit("kind", &kind); | ||
| v->Visit("inputs", &inputs); | ||
| v->Visit("attrs", &attrs); | ||
| v->Visit("outputs", &outputs); | ||
| } | ||
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| static constexpr const char* _type_key = "tir.Instruction"; | ||
| TVM_DECLARE_FINAL_OBJECT_INFO(InstructionNode, runtime::Object); | ||
| }; | ||
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| /*! | ||
| * \brief Managed reference to InstructionNode | ||
| * \sa InstructionNode | ||
| */ | ||
| class Instruction : public runtime::ObjectRef { | ||
| public: | ||
| /*! | ||
| * \brief Constructor | ||
| * \param kind The kind of the instruction | ||
| * \param inputs The input random variables of the instruction | ||
| * \param attrs The attributes of the instruction | ||
| * \param outputs The output random variables of the instruction | ||
| */ | ||
| explicit Instruction(InstructionKind kind, Array<ObjectRef> inputs, Array<ObjectRef> attrs, | ||
| Array<ObjectRef> outputs); | ||
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| TVM_DEFINE_OBJECT_REF_METHODS(Instruction, runtime::ObjectRef, InstructionNode); | ||
| }; | ||
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| /*! | ||
| * \brief A helper macro to register InstructionKind, only used in `TVM_REGISTER_INST_KIND` | ||
| * \note This macro is not user-facing. | ||
| * \sa TVM_REGISTER_INST_KIND | ||
| */ | ||
| #define TVM_INST_KIND_REGISTER_VAR_DEF \ | ||
| static DMLC_ATTRIBUTE_UNUSED ::tvm::tir::InstructionKindRegEntry& __make_##InstructionKind | ||
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| /*! | ||
| * \brief Register an InstructionKind | ||
| * \param InstructionKindName The name of the InstructionKind | ||
| * | ||
| * Example: | ||
| * | ||
| * \code | ||
| * | ||
| * TVM_REGISTER_INST_KIND("ComputeInline") | ||
| * .set_is_pure(false) | ||
| * .set_apply_to_schedule(ApplyToSchedule) | ||
| * .set_attrs_as_json(AttrsAsJSON) | ||
| * .set_attrs_from_json(AttrsFromJSON) | ||
| * .set_as_python(AsPython); | ||
| * | ||
| * \endcode | ||
| */ | ||
| #define TVM_REGISTER_INST_KIND(InstructionKindName) \ | ||
| TVM_STR_CONCAT(TVM_INST_KIND_REGISTER_VAR_DEF, __COUNTER__) = \ | ||
| ::tvm::tir::InstructionKindRegEntry::RegisterOrGet(InstructionKindName).set_name() | ||
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| /*! \brief An entry in the registry of InstructionKind */ | ||
| class InstructionKindRegEntry { | ||
| public: | ||
| static InstructionKindRegEntry& RegisterOrGet(const String& name); | ||
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| InstructionKindRegEntry& set_name() { | ||
| get_mutable()->name = this->name; | ||
| return *this; | ||
| } | ||
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| InstructionKindRegEntry& set_is_pure(bool is_pure) { | ||
| get_mutable()->is_pure = is_pure; | ||
| return *this; | ||
| } | ||
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| InstructionKindRegEntry& set_apply_to_schedule(FInstructionApply f_apply_to_schedule) { | ||
| get_mutable()->f_apply_to_schedule = std::move(f_apply_to_schedule); | ||
| return *this; | ||
| } | ||
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| InstructionKindRegEntry& set_as_python(FInstructionAsPython f_as_python) { | ||
| get_mutable()->f_as_python = std::move(f_as_python); | ||
| return *this; | ||
| } | ||
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| InstructionKindRegEntry& set_attrs_as_json(FInstructionAttrsAsJSON f_attrs_as_json) { | ||
| get_mutable()->f_attrs_as_json = std::move(f_attrs_as_json); | ||
| return *this; | ||
| } | ||
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| InstructionKindRegEntry& set_attrs_from_json(FInstructionAttrsFromJSON f_attrs_from_json) { | ||
| get_mutable()->f_attrs_from_json = std::move(f_attrs_from_json); | ||
| return *this; | ||
| } | ||
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| private: | ||
| /*! \brief Private constructor, used only by AttrRegistry */ | ||
| explicit InstructionKindRegEntry(uint32_t reg_index); | ||
| /*! \brief Get the mutable reference to the internal InstructionKind */ | ||
| InstructionKindNode* get_mutable() const { | ||
| return const_cast<InstructionKindNode*>(inst_kind_.get()); | ||
| } | ||
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| /*! \brief The name of the registry entry */ | ||
| String name; | ||
| /*! \brief The instruction kind */ | ||
| InstructionKind inst_kind_; | ||
| template <typename, typename> | ||
| friend class ::tvm::AttrRegistry; | ||
| friend class InstructionKind; | ||
| }; | ||
|
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| } // namespace tir | ||
| } // namespace tvm | ||
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| #endif // TVM_TIR_SCHEDULE_INSTRUCTION_H_ |
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