merrymercy commented on a change in pull request #5962: URL: https://github.com/apache/incubator-tvm/pull/5962#discussion_r449990904
########## File path: python/tvm/ansor/compute_dag.py ########## @@ -0,0 +1,153 @@ +# 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. + +""" Computational graph and its analysis tools """ + +import hashlib + +import tvm._ffi +from tvm.runtime import Object +from tvm.te import PlaceholderOp, ComputeOp + +from .loop_state import State, StateObject +from .utils import get_const_tuple +from .workload_registry import workload_key_to_tensors + +from . import _ffi_api + + +@tvm._ffi.register_object("ansor.ComputeDAG") +class ComputeDAG(Object): + """ + The Ansor computational graph and related program analyses. + + We convert a compute declaration described by `tvm.compute` (could be a single operator or a + subgraph) to a ComputeDAG. It keeps the input/output tensors of the compute declaration, + a list of all operations in the DAG as well as static analysis results for the DAG (e.g. the + total float operation count, consumer/producer relations of each operation stage, whether an + operation stage should be tiled/compute inlined ...). These analyses can help the search policy + to make decisions during search process. + ComputeDAG is also responsible for the interaction between Ansor `LoopState` and TVM schedule + (e.g. applying the `LoopState` transform steps to TVM schedule, providing `LoopState` with extra + information got from TVM schedule ...). + + Parameters + ---------- + compute : Union[List[Tensor], str] + `Tensor`s or workload key for a compute declaration. + """ + def __init__(self, compute): + if isinstance(compute, str): + compute = workload_key_to_tensors(compute) + elif isinstance(compute, list): + for item in compute: + if not isinstance(item, tvm.te.Tensor): + raise ValueError("The input of ComputeDAG should be a list of Tensor") + else: + raise ValueError("Invalid compute: " + compute + + " . `ComputeDAG` expects a string or list of Tensor") + self.__init_handle_by_constructor__(_ffi_api.ComputeDAG, compute) + + def get_init_state(self): + """ Get the init state of this ComputeDAG. + + Returns + ------- + state : State + The initial State without any transform steps. + """ + return State(self.init_state, self) + + def apply_steps_from_state(self, state): + """ + Apply the history transform steps from a State to get a TVM schedule. + + Parameters + ---------- + state : Union[State, StateObject] + The state from which we get transform steps. + + Returns + ------- + A `te.schedule` and the a list of `te.Tensor` to be used in `tvm.lower` or `tvm.build`. + """ + state_obj = state if isinstance(state, StateObject) else state.state_object + return _ffi_api.ComputeDAGApplyStepsFromState(self, state_obj) + + def print_python_code_from_state(self, state): + """ + Print transform steps in the history of a State as TVM's python schedule primitive. + + This can be used for debugging or to apply the schedule on a former TVM version without + Ansor support. Review comment: ```suggestion This is used for debugging. ``` ---------------------------------------------------------------- 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. For queries about this service, please contact Infrastructure at: us...@infra.apache.org
