# Copyright 2021 Huawei Technologies Co., Ltd
#
# 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 argparse
import sys
sys.path.append('./ResNeSt')
import torch
import torch.onnx
from resnest.torch import resnest50
from collections import OrderedDict
def proc_node_module(checkpoint):
new_state_dict = OrderedDict()
for k, v in checkpoint.items():
if (k[0:7] == "module."):
name = k[7:]
else:
name = k[0:]
new_state_dict[name] = v
return new_state_dict
def pth2onnx(input_file, output_file):
checkpoint = torch.load(input_file, map_location=None)
checkpoint = proc_node_module(checkpoint)
model = resnest50()
model.load_state_dict(checkpoint)
model.eval()
input_names = ["actual_input_1"]
output_names = ["output1"]
dynamic_axes = {'actual_input_1': {0: '-1'}, 'output1': {0: '-1'}}
dummy_input = torch.randn(1, 3, 224, 224)
# Providing input and output names sets the display names for values
# within the model's graph. Setting these does not change the semantics
# of the graph; it is only for readability.
#
# The inputs to the network consist of the flat list of inputs (i.e.
# the values you would pass to the forward() method) followed by the
# flat list of parameters. You can partially specify names, i.e. provide
# a list here shorter than the number of inputs to the model, and we will
# only set that subset of names, starting from the beginning.
torch.onnx.export(model,
dummy_input,
output_file,
dynamic_axes=dynamic_axes,
verbose=True,
input_names=input_names,
output_names=output_names,
opset_version=11)
if __name__ == '__main__':
parser = argparse.ArgumentParser()
parser.add_argument('--source', type=str, default="./resnest50.pth")
parser.add_argument('--target', type=str, default="resnest50.onnx")
args = parser.parse_args()
pth2onnx(args.source, args.target)