ModelScope还是在报这个错误?
Traceback (most recent call last):
File "<string>", line 1, in <module>
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 116, in spawn_main
exitcode = _main(fd, parent_sentinel)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 125, in _main
prepare(preparation_data)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 236, in prepare
_fixup_main_from_path(data['init_main_from_path'])
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 287, in _fixup_main_from_path
main_content = runpy.run_path(main_path,
File "E:\Anaconda3\envs\modelscope\lib\runpy.py", line 265, in run_path
return _run_module_code(code, init_globals, run_name,
File "E:\Anaconda3\envs\modelscope\lib\runpy.py", line 97, in _run_module_code
_run_code(code, mod_globals, init_globals,
File "E:\Anaconda3\envs\modelscope\lib\runpy.py", line 87, in _run_code
exec(code, run_globals)
File "D:\pythonWarkSpace\modelscope_test\mgeo_train.py", line 86, in <module>
finetune(
File "D:\pythonWarkSpace\modelscope_test\mgeo_train.py", line 27, in finetune
trainer.train()
File "E:\Anaconda3\envs\modelscope\lib\site-packages\modelscope\trainers\trainer.py", line 693, in train
self.train_loop(self.train_dataloader)
File "E:\Anaconda3\envs\modelscope\lib\site-packages\modelscope\trainers\trainer.py", line 1207, in train_loop
for i, data_batch in enumerate(data_loader):
File "E:\Anaconda3\envs\modelscope\lib\site-packages\torch\utils\data\dataloader.py", line 441, in __iter__
return self._get_iterator()
File "E:\Anaconda3\envs\modelscope\lib\site-packages\torch\utils\data\dataloader.py", line 388, in _get_iterator
return _MultiProcessingDataLoaderIter(self)
File "E:\Anaconda3\envs\modelscope\lib\site-packages\torch\utils\data\dataloader.py", line 1042, in __init__
w.start()
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\process.py", line 121, in start
self._popen = self._Popen(self)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\context.py", line 224, in _Popen
return _default_context.get_context().Process._Popen(process_obj)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\context.py", line 327, in _Popen
return Popen(process_obj)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\popen_spawn_win32.py", line 45, in __init__
prep_data = spawn.get_preparation_data(process_obj._name)
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 154, in get_preparation_data
_check_not_importing_main()
File "E:\Anaconda3\envs\modelscope\lib\multiprocessing\spawn.py", line 134, in _check_not_importing_main
raise RuntimeError('''
RuntimeError:
An attempt has been made to start a new process before the
current process has finished its bootstrapping phase.
This probably means that you are not using fork to start your
child processes and you have forgotten to use the proper idiom
in the main module:
if __name__ == '__main__':
freeze_support()
...
The "freeze_support()" line can be omitted if the program
is not going to be frozen to produce an executable.
错误信息是:
RuntimeError: Expected tensor to have 1 dimension at non-zero indices, but got dimension 0 at index 0
这可能是由于模型的输入序列的长度不匹配导致的。
可以尝试检查模型的输入序列的长度是否正确,并确保输入序列的长度和 output_sequence 的长度相等。
如果仍然出现错误,可以尝试使用 torch.tensor() 将输入序列转换成张量,并将张量传递给模型。
例如,以下代码可以将一个列表转换成张量:
x = torch.tensor([1, 2, 3])
然后,可以将这个张量传递给模型。
例如,以下代码可以使用模型预测下一句话:
output = model(x)