zxros10
35 lines
1.2 KiB
Python
35 lines
1.2 KiB
Python
# Copyright 2020 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 torch
|
|
from efficientnet_pytorch import EfficientNet
|
|
|
|
# Specify which model to use
|
|
model_name = 'efficientnet-b3'
|
|
image_size = EfficientNet.get_image_size(model_name)
|
|
print('Image size: ', image_size)
|
|
|
|
# Load model
|
|
model = EfficientNet.from_pretrained(model_name)
|
|
model.set_swish(memory_efficient=False)
|
|
model.eval()
|
|
print('Model image size: ', model._global_params.image_size)
|
|
|
|
# Dummy input for ONNX
|
|
dummy_input = torch.randn(1, 3, 300, 300)
|
|
|
|
# Export with ONNX
|
|
torch.onnx.export(model, dummy_input, f"{model_name}.onnx", verbose=True)
|