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。
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):
- 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)
- 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 path
- shape_list: [1, 3, ...]
- Returns:
- """
- import os
- import onnx
- model_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 = 1
- for 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)