本文主要是介绍onnx模型转换opset版本和固定动态输入尺寸，希望对大家解决编程问题提供一定的参考价值，需要的开发者们随着小编来一起学习吧！
背景：之前我想把onnx模型从opset12变成opset12，太慌乱就没找着，最近找到了官网上有示例的，大爱onnx官网，分享给有需求没找着的小伙伴们。
1. onnx模型转换opset版本
官网示例：
import onnx
from onnx import version_converter, helper# Preprocessing: load the model to be converted.
model_path = "path/to/the/model.onnx"
original_model = onnx.load(model_path)print(f"The model before conversion:\n{original_model}")# A full list of supported adapters can be found here:
# https://github.com/onnx/onnx/blob/main/onnx/version_converter.py#L21
# Apply the version conversion on the original model
converted_model = version_converter.convert_version(original_model, <int target_version>)print(f"The model after conversion:\n{converted_model}")其github地址如下：
onnx/docs/PythonAPIOverview.md at main · onnx/onnx (github.com)
https://github.com/onnx/onnx/blob/main/docs/PythonAPIOverview.md#converting-version-of-an-onnx-model-within-default-domain-aionnx其小伙伴拉到gitee上的地址如下（以防有的小伙伴github打不开）：
docs/PythonAPIOverview.md · meiqicheng/github-onnx-onnx - Gitee.comhttps://gitee.com/meiqicheng1216/onnx/blob/master/docs/PythonAPIOverview.md#converting-version-of-an-onnx-model-within-default-domain-aionnx最后附上完整代码：
import onnx
from onnx import version_converter, helper# A full list of supported adapters can be found here:
# https://github.com/onnx/onnx/blob/main/onnx/version_converter.py#L21
# Apply the version conversion on the original model# Preprocessing: load the model to be converted.
model_path = r"./demo.onnx"
original_model = onnx.load(model_path)
print(f"The model before conversion:\n{original_model}")converted_model = version_converter.convert_version(original_model, 11)
print(f"The model after conversion:\n{converted_model}")save_model = model_path[:-5] + "_opset11.onnx"
onnx.save(converted_model, save_model)2. onnx模型转固定动态输入尺寸
def change_dynamic_input_shape(model_path, shape_list: list):"""将动态输入的尺寸变成固定尺寸Args:model_path: onnx model pathshape_list: [1, 3, ...]Returns:"""import osimport onnxmodel_path = os.path.abspath(model_path)output_path = model_path[:-5] + "_fixed.onnx"model = onnx.load(model_path)# print(onnx.helper.printable_graph(model.graph))inputs = model.graph.input # inputs是一个列表，可以操作多输入~# look_input = inputs[0].type.tensor_type.shape.dim# print(look_input)# print(type(look_input))# inputs[0].type.tensor_type.shape.dim[0].dim_value = 1for idx, i_e in enumerate(shape_list):inputs[0].type.tensor_type.shape.dim[idx].dim_value = i_e# print(onnx.helper.printable_graph(model.graph))onnx.save(model, output_path)if __name__ == "__main__":model_path = "./demo.onnx"shape_list = [1]change_dynamic_input_shape(model_path, shape_list)这篇关于onnx模型转换opset版本和固定动态输入尺寸的文章就介绍到这儿，希望我们推荐的文章对编程师们有所帮助！
