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()