junrushao1994 commented on a change in pull request #8615: URL: https://github.com/apache/tvm/pull/8615#discussion_r681351829
########## File path: include/tvm/tir/schedule/instruction.h ########## @@ -0,0 +1,288 @@ +/* + * 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_ + +#include <tvm/node/reflection.h> + +#include <utility> + +namespace tvm { + +// Forward declaration +template <typename, typename> +class AttrRegistry; + +namespace tir { + +// Forward declaration +class Schedule; + +/*! + * \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)>; + +/*! + * \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)>; + +/*! + * \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)>; + +/*! + * \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)>; + +/*! + * \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}; Review comment: If the instruction is pure, which doesn't have any effect on the IR, e.g. `GetBlock`, then we can remove this instruction in dead-code elimination -- This is an automated message from the Apache Git Service. To respond to the message, please log on to GitHub and use the URL above to go to the specific comment. To unsubscribe, e-mail: [email protected] For queries about this service, please contact Infrastructure at: [email protected]
