# Copyright (c) 2020 PaddlePaddle Authors. All Rights Reserved. # # 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. from x2paddle.core.program import PaddleGraph class PatternMatcher(object): def __init__(self, pattern): self.pattern = pattern # matches的每个match是按照拓扑排序组成layer的dict self.matches = list() def operate(self, graph, match_kind="topo"): if match_kind == "topo": self.detect_patterns_by_topo(graph) elif match_kind == "edge": self.detect_patterns_by_edge(graph) self.remove_overlapped_match() return self.matches def detect_patterns_by_topo(self, graph): """ 找到与模式匹配的子图， 并将子图的id以拓扑排序存放到subgraph_id2layers。 """ def get_subgraph(pattern, graph, start_index, is_subblock=False): pattern_index = 0 pattern_id2layers = pattern.get_global_layers() pattern_ids = list(pattern_id2layers.keys()) subgraph_id2layers = dict() graph_layers = dict(list(graph.layers.items())[start_index:]) for layer_id, layer in graph_layers.items(): pattern_layer = pattern.layers[list(pattern.layers.keys())[ pattern_index]] if layer.kernel == pattern_layer.kernel: subgraph_id2layers[layer_id] = layer pattern_layer_id = pattern_layer.id # 判断输入连接是否一致 if layer_id in graph.edges_in: if pattern_layer_id not in pattern.edges_in: if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue else: if len(graph.edges_in[layer_id]) != len( pattern.edges_in[pattern_layer_id]): if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue layer_in = graph.edges_in[layer_id] pattern_layer_in = pattern.edges_in[pattern_layer_id] for i in range(len(layer_in)): layer_id_in = layer_in[i] pattern_layer_id_in = pattern_layer_in[i] if pattern_layer_id_in != -1: subgraph_ids = list(subgraph_id2layers.keys()) if layer_id_in not in subgraph_ids: return False if pattern_ids.index(pattern_layer_id_in) == \ subgraph_ids.index(layer_id_in): # 判断pattern输入在pattern_ids的索引 # 和graph输入在subgraph_ids的索引一致 continue if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue # 判断subgraph中的节点是否被外部图使用到(如若被使用到则无效) if layer_id in graph.edges_out: if pattern_layer_id not in pattern.edges_out: if not set(pattern_layer.outputs).issubset( pattern.outputs): # 若pattern当前layer的输出是pattern的输出，则是正确的 if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue else: if len(graph.edges_out[layer_id]) != len( pattern.edges_out[pattern_layer_id]): # 如果在每个节点edges_in相同的情况下，edges_out数目相同则说明无节点在subgraph外被用到 if not set(pattern_layer.outputs).issubset( pattern.outputs): # 若pattern当前layer的输出是pattern的输出，则是正确的 if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue # 当为控制流时的处理 if layer.kernel == "prim.if" or layer.kernel == "prim.loop": if len(pattern_layer.blocks) != len(layer.blocks): if pattern_index == 0 or is_subblock: return False else: subgraph_id2layers.pop(layer_id) continue is_subblock_match = True for i, b in enumerate(pattern_layer.blocks): match_info = get_subgraph( pattern_layer.blocks[i], layer.blocks[i], 0, is_subblock=True) if match_info is not False: subgraph_id2layers.update(match_info) else: is_subblock_match = False break if not is_subblock_match: if pattern_index == 0 or is_subblock: return False else: index = list(subgraph_id2layers.keys()).index( layer_id) for key in list(subgraph_id2layers.keys())[ index:]: subgraph_id2layers.pop(key) continue pattern_index += 1 if pattern_index == len(pattern.layers): return subgraph_id2layers else: if pattern_index == 0 or is_subblock: return False else: continue if pattern_index == len(pattern.layers): return subgraph_id2layers return False for i, (layer_id, layer) in enumerate(graph.layers.items()): match_info = get_subgraph(self.pattern, graph, i) if match_info: self.matches.append(match_info) for j, block in enumerate(layer.blocks): if len(block.layers) > 0: self.detect_patterns_by_topo(layer.blocks[j]) def detect_patterns_by_edge(self, graph, ignore_list_inputs=True): """当遇见顺序没有强制规定的pattern时使用该方式 """ def get_subgraph(pattern, graph, start_index): pattern_id2layers = pattern.get_global_layers() pattern_ids = list(pattern_id2layers.keys()) pattern_layer_id = pattern_ids[0] subgraph_id2layers = dict() graph_layers = dict(list(graph.layers.items())[start_index:]) layer_id = list(graph_layers.keys())[0] def update(layer_id, pattern_layer_id): layer = graph_layers[layer_id] pattern_layer = pattern_id2layers[pattern_layer_id] if layer.kernel != pattern_layer.kernel: return False subgraph_id2layers[layer_id] = layer for i, pattern_layer_id_in in enumerate(pattern.edges_in[ pattern_layer_id]): if pattern_layer_id_in == -1 or ignore_list_inputs: continue layer_id_in = graph.edges_in[layer_id][i] subgraph_ids = list(subgraph_id2layers.keys()) if layer_id_in not in subgraph_ids: return False if pattern.edges_out.get(pattern_layer_id, 0) != 0: if len(pattern.edges_out[pattern_layer_id]) != \ len(graph.edges_out[layer_id]): return False for i, pattern_layer_id_out in enumerate(pattern.edges_out[ pattern_layer_id]): if pattern_layer_id_out in pattern_ids: new_layer_id_out = graph.edges_out[layer_id][i] for j, new_new_layer_id_in in enumerate( graph.edges_in[new_layer_id_out]): if new_new_layer_id_in not in subgraph_id2layers: if ignore_list_inputs: continue new_new_pattern_layer_id_in = pattern.edges_in[ pattern_layer_id_out][j] if new_new_pattern_layer_id_in == -1: continue update(new_new_layer_id_in, new_new_pattern_layer_id_in) update(new_layer_id_out, pattern_layer_id_out) while len(subgraph_id2layers) != len(pattern_id2layers): out = update(layer_id, pattern_layer_id) if out == False: return False else: if len(subgraph_id2layers) == len(pattern_id2layers): return subgraph_id2layers else: return False for i, (layer_id, layer) in enumerate(graph.layers.items()): match_info = get_subgraph(self.pattern, graph, i) if match_info: self.matches.append(match_info) for j, block in enumerate(layer.blocks): if len(block.layers) > 0: self.detect_patterns_by_edge(layer.blocks[j]) def remove_overlapped_match(self): """ 如果2个子图有重叠，只取前一个子图。 """ match_ids = [] for i, match in enumerate(self.matches): is_overlapped = False for id in match.keys(): if id in match_ids: self.matches.pop(i) is_overlapped = True break if not is_overlapped: match_ids.extend(list(match.keys())) def get_subgraph(prefix_layer_id, suffix_layer_id, graph): """ 根据prefix_layer_id和suffix_layer_id获取需要子图。 Args: prefix_layer_id (str): 起初为一个空字符串，之后为suffix_layer_id分割出来的前缀。 suffix_layer_id (str): 起初为以一个layer的id，之后将分割部分给prefix_layer_id；例如”57.0.1“； graph (x2paddle.core.program.PaddleGraph): 需要进行pass的子图。 """ id_part = suffix_layer_id.split(".") if len(id_part) == 1: return graph if prefix_layer_id == "": layer_id = id_part[0] prefix_layer_id += ".".join(id_part[:2]) else: layer_id = prefix_layer_id + "." + id_part[0] prefix_layer_id += ("." + ".".join(id_part[:2])) subgraph = graph.layers[layer_id].blocks[int(id_part[1])] suffix_layer_id = ".".join(id_part[2:]) return get_subgraph(prefix_layer_id, suffix_layer_id, subgraph) class FuseBase(object): def __init__(self, graph_type): self.pattern = PaddleGraph(graph_type=graph_type) def operate(self, graph, match_kind="topo"): parameters = graph.parameters self.build_pattern() self.perform_pattern_matcher(graph, match_kind) for match in self.matches: first_layer_id = list(match.keys())[0] subgraph = get_subgraph("", first_layer_id, graph) self.insert_new_layer(subgraph, parameters, match) self.delete_inter_layer(graph) graph.build() def perform_pattern_matcher(self, graph, match_kind="topo"): """ 执行模式匹配，找到匹配的子图。 """ pattern_matcher = PatternMatcher(self.pattern) self.matches = pattern_matcher.operate(graph, match_kind) def delete_inter_layer(self, graph): """ 删除不需要的中间layer及其对应参数。 """ for match in self.matches: first_layer_id = list(match.keys())[0] subgraph = get_subgraph("", first_layer_id, graph) for layer_id, layer in match.items(): if layer.kernel == "fluid.dygraph.base.to_variable" and \ layer.attrs["value"].startswith("params["): param_name = layer.attrs["value"][8:-2] if param_name in graph.parameters: graph.parameters.pop(param_name) if layer_id in subgraph.layers: # layer_id可能是属于子图的，此时删除父layer，即删除整个子图 subgraph.layers.pop(layer_id)