MichaelJKlaiber commented on code in PR #12087: URL: https://github.com/apache/tvm/pull/12087#discussion_r939153921
########## python/tvm/relay/backend/contrib/uma/api/lower.py: ########## @@ -0,0 +1,159 @@ +# 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. +"""Lowering base class of the Universal Modular Accelerator Interface (UMA)""" + +from typing import List, Tuple, Callable, Optional + +import tvm +from tvm import relay, te +from tvm.relay.op.op import register_strategy +from . import _ffi_api +from .utils import PassPhase + + +class UMALower: + """Lowering base class of the Universal Modular Accelerator Interface (UMA).""" + + def __init__(self, target_name: str) -> None: + self.target_name = target_name + + self._operator_strategies: List[ + Tuple[ + str, + Callable[ + [tvm.ir.Attrs, tvm.ir.Array, tvm.ir.TensorType, tvm.target.Target], + tvm.relay.op.op.OpStrategy, + ], + Optional[int], + ] + ] = [] + self._tir_passes: List[Tuple[PassPhase, tvm.tir.transform.PrimFuncPass]] = [] + + def _lower_relay_to_tir(self, relay_prim_func: relay.Function) -> tvm.tir.PrimFunc: + """Lower a Relay primitive function to a S-TIR primitive function. + + Parameters + ---------- + prim_func : tvm.relay.Function + The Relay function to lower. + + Returns + ------- + out : tvm.tir.PrimFunc + The lowered schedulable TensorIR primitive function. + + """ + + def _get_tensors(te_cached_func): + outputs = list(te_cached_func.outputs) + stack = [] + visited = set() + for output_ in outputs: + if output_ not in visited: + visited.add(output_) + stack.append(output_) + + args = [] + while len(stack) != 0: + tensor = stack.pop() + if isinstance(tensor.op, tvm.te.tensor.PlaceholderOp): + args.append(tensor) + elif isinstance(tensor.op, tvm.te.tensor.ComputeOp): + inputs = tensor.op.input_tensors + for input_ in inputs: + if input_ not in visited: + visited.add(input_) + stack.append(input_) + + return args + outputs + + f = tvm._ffi.get_global_func("relay.backend.LowerToTE") + te_cached_func = f(relay_prim_func) + x = _get_tensors(te_cached_func) + tir_prim_func = te.create_prim_func(x) + tir_prim_func = tir_prim_func.with_attr( + "global_symbol", relay_prim_func.attrs["global_symbol"] + ) + # TODO: The target should probably come from somewhere else instead of being created here. + tir_prim_func = tir_prim_func.with_attr("target", tvm.target.Target(self.target_name)) Review Comment: @cgerum can you comment? -- 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]
