raceback (most recent call last): File "D:\projectfiles\ESP32\esp-dl-master\tools\quantization_tool\examples\pytorch_to_onnx\onnx.py", line 7, in <module> torch.onnx.export(model, dummy_input, output_file, verbose=False) File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\site-packages\torch\onnx\utils.py", line 506, in export _export( File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\site-packages\torch\onnx\utils.py", line 1525, in _export with exporter_context(model, training, verbose): File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\contextlib.py", line 119, in __enter__ return next(self.gen) File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\site-packages\torch\onnx\utils.py", line 178, in exporter_context with select_model_mode_for_export( File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\contextlib.py", line 119, in __enter__ return next(self.gen) File "C:\Users\NLER\.conda\envs\pytorch-Demo2\lib\site-packages\torch\onnx\utils.py", line 139, in disable_apex_o2_state_dict_hook for module in model.modules(): AttributeError: 'str' object has no attribute 'modules'
时间: 2023-06-30 13:12:33 浏览: 233
这个错误提示是因为您传递给torch.onnx.export函数的model参数是一个字符串而不是模型对象。请确保您已经正确加载了模型,并将其传递给export函数。
例如,如果您的PyTorch模型保存在名为"model.pth"的文件中,您可以使用以下代码加载模型并将其导出为ONNX格式:
```
import torch
# 加载PyTorch模型
model = torch.load("model.pth")
# 创建一个随机输入张量
dummy_input = torch.randn(1, 3, 224, 224)
# 导出模型为ONNX格式
output_file = "model.onnx"
torch.onnx.export(model, dummy_input, output_file, verbose=False)
```
请注意,这里的model参数是一个模型对象,它是使用torch.load函数从文件中加载的。如果您使用不同的方法加载模型,请确保将正确的模型对象传递给export函数。
相关问题
Traceback (most recent call last): File "F:\pythonProject\main.py", line 1, in <module> import matplotlib.pyplot as plt
引用\[1\]:Traceback (most recent call last): File "test.py", line 2, in <module> import pandas ImportError: No module named pandas 。 引用\[2\]:安装完后执行python detect.py,遇到如下问题: traceback (most recent call last): File "detect.py", line 5, in <module> import cv2 File "/root/anaconda3/envs/python367/lib/python3.6/site-packages/cv2/__init__.py", line 5, in <module> from .cv2 import * ImportError: libGL.so.1: cannot open shared object file: No such file or directory 。 引用\[3\]: 然后安装requiremens.txt,yolov5 4.0版本要求如下: # base ---------------------------------------- matplotlib>=3.2.2 numpy>=1.18.5 opencv-python>=4.1.2 Pillow PyYAML>=5.3.1 scipy>=1.4.1 torch>=1.7.0 torchvision>=0.8.1 tqdm>=4.41.0 # logging ------------------------------------- tensorboard>=2.4.1 # wandb # plotting ------------------------------------ seaborn>=0.11.0 pandas # export -------------------------------------- # coremltools>=4.1 # onnx>=1.8.1 # scikit-learn==0.19.2 # for coreml quantization # extras -------------------------------------- thop # FLOPS computation pycocotools>=2.0 # COCO mAP 。 问题:Traceback (most recent call last): File "F:\pythonProject\main.py", line 1, in <module> import matplotlib.pyplot as plt
回答: 根据您提供的引用内容,问题出现在导入matplotlib.pyplot时。根据引用\[1\],错误信息显示没有找到pandas模块。这可能是因为您的环境中没有安装pandas模块。您可以尝试使用pip install pandas命令来安装pandas模块。另外,根据引用\[2\],错误信息显示找不到libGL.so.1共享对象文件。这可能是由于缺少libGL.so.1库文件导致的。您可以尝试安装相应的库文件来解决此问题。最后,根据引用\[3\],要使用matplotlib.pyplot,您需要确保已安装了matplotlib模块。您可以使用pip install matplotlib命令来安装matplotlib模块。如果问题仍然存在,请确保您的环境中已正确安装了所有所需的依赖项。
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[ .reference_list ]
C:\Users\80977\.conda\envs\pytorchenv\python.exe D:\work\DL-codes\deep-learning-for-image-processing-master\deep-learning-for-image-processing-master\pytorch_object_detection\faster_rcnn\train_mobilenetv2.py Using cuda device training. Using [0, 0.5, 0.6299605249474366, 0.7937005259840997, 1.0, 1.2599210498948732, 1.5874010519681994, 2.0, inf] as bins for aspect ratio quantization Count of instances per bin: [ 5 25 929 117 260 4198 135 48] Using 8 dataloader workers Traceback (most recent call last): File "<string>", line 1, in <module> File "C:\Users\80977\.conda\envs\pytorchenv\lib\multiprocessing\spawn.py", line 116, in spawn_main exitcode = _main(fd, parent_sentinel) File "C:\Users\80977\.conda\envs\pytorchenv\lib\multiprocessing\spawn.py", line 125, in _main prepare(preparation_data) File "C:\Users\80977\.conda\envs\pytorchenv\lib\multiprocessing\spawn.py", line 236, in prepare _fixup_main_from_path(data['init_main_from_path']) File "C:\Users\80977\.conda\envs\pytorchenv\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path main_content = runpy.run_path(main_path, File "C:\Users\80977\.conda\envs\pytorchenv\lib\runpy.py", line 288, in run_path return _run_module_code(code, init_globals, run_name, File "C:\Users\80977\.conda\envs\pytorchenv\lib\runpy.py", line 97, in _run_module_code _run_code(code, mod_globals, init_globals, File "C:\Users\80977\.conda\envs\pytorchenv\lib\runpy.py", line 87, in _run_code exec(code, run_globals) File "D:\work\DL-codes\deep-learning-for-image-processing-master\deep-learning-for-image-processing-master\pytorch_object_detection\faster_rcnn\train_mobilenetv2.py", line 4, in <module> import torch File "C:\Users\80977\AppData\Roaming\Python\Python39\site-packages\torch\__init__.py", line 123, in <module> raise err OSError: [WinError 1455] 页面文件太小,无法完成操作。 Error loading "C:\Users\80977\AppData\Roaming\Python\Python39\site-packages\torch\lib\caffe2_detectron_ops_gpu.dll" or one of its dependencies.
这个错误提示是在运行 PyTorch 目标检测的 Faster R-CNN 模型时出现的。根据错误提示,似乎是在加载 `caffe2_detectron_ops_gpu.dll` 或其某个依赖项时出现了问题。
可能的原因和解决方法如下:
1. 内存不足:错误提示中提到“页面文件太小”,这可能是因为内存不足导致的。可以尝试关闭一些占用内存较多的程序或者增加内存。
2. 文件损坏:`caffe2_detectron_ops_gpu.dll` 文件或其某个依赖项可能被损坏了,需要重新安装 PyTorch。
3. 缺失依赖项:该文件可能依赖于其他一些文件,而这些文件可能缺失或损坏了。可以尝试重新安装 PyTorch 或者查找缺失的文件并手动安装。
4. 不兼容的操作系统:该文件可能不兼容当前操作系统。可以尝试更新操作系统或者查找适用于当前操作系统的版本。
希望以上方法能够帮助您解决问题。
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