optimum/onnxruntime/preprocessors/passes/fully_connected.py (16 lines of code) (raw):

# Copyright 2022 The HuggingFace Team. 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 typing import Set, Tuple from onnx import ModelProto from onnxruntime.transformers.onnx_model import OnnxModel from .. import PreprocessorPass class IncludeFullyConnectedNodes(PreprocessorPass): def __init__(self): super().__init__() def __call__(self, graph: ModelProto, model: OnnxModel) -> Tuple[Set[str], Set[str]]: fc_subgraphs = [] for add_node in model.get_nodes_by_op_type("Add"): fc_components = model.match_parent_path(add_node, ["MatMul"], [1]) if fc_components is not None: fc_components.append(add_node) fc_subgraphs.append(fc_components) fc_components = {node.name for fc in fc_subgraphs for node in fc} return fc_components, set()