# 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. import numpy as np from x2paddle.optimizer.pytorch_optimizer.pattern_matcher import FuseBase from x2paddle.core.program import PaddleGraph, PaddleLayer from x2paddle.core.util import * class ConstantFuser(FuseBase): def __init__(self): super(ConstantFuser, self).__init__(graph_type="dygraph") def build_pattern(self): """ 描述需要替换的constant图结构。 constant层模式python实现代码示例: x3 = 10 for _x70 in range(x3): ... """ self.pattern.add_layer( "prim.constant", inputs={}, outputs=["x1"], value=2) self.pattern.build() self.pattern.outputs = ["x1"] def insert_new_layer(self, graph, parameters, matches): def replace_value(layer_connect, match_name, match_value): for k, v in layer_connect.inputs.items(): if v == match_name: layer_connect.inputs.pop(k) layer_connect.attrs[k] = match_value break for k, v in layer_connect.attrs.items(): if v == match_name: layer_connect.attrs[k] = match_value break if layer_connect.kernel == "prim.loop" or \ layer_connect.kernel == "prim.if": for block in layer_connect.blocks: for b_layer_id, b_layer in block.layers.items(): if block.edges_in.get(b_layer_id, 0) != 0 and \ -1 in block.edges_in[b_layer_id]: replace_value(b_layer, match_name, match_value) layer_id = list(matches.keys())[0] layer = list(matches.values())[0] layer_output_name = layer.outputs[0] layer_value = layer.attrs["value"] if graph.edges_out.get(layer_id, 0) != 0: for layer_id_out in graph.edges_out[layer_id]: layer_connect = graph.layers[layer_id_out] replace_value(layer_connect, layer_output_name, layer_value)