{"action":"opened","issue":{"url":"https://api.github.com/repos/thuml/Xlearn/issues/18","repository_url":"https://api.github.com/repos/thuml/Xlearn","labels_url":"https://api.github.com/repos/thuml/Xlearn/issues/18/labels{/name}","comments_url":"https://api.github.com/repos/thuml/Xlearn/issues/18/comments","events_url":"https://api.github.com/repos/thuml/Xlearn/issues/18/events","html_url":"https://github.com/thuml/Xlearn/issues/18","id":363444900,"node_id":"MDU6SXNzdWUzNjM0NDQ5MDA=","number":18,"title":"How can I solve this problem, Thank you!","user":{"login":"TGISer","id":16577071,"node_id":"MDQ6VXNlcjE2NTc3MDcx","avatar_url":"https://avatars0.githubusercontent.com/u/16577071?v=4","gravatar_id":"","url":"https://api.github.com/users/TGISer","html_url":"https://github.com/TGISer","followers_url":"https://api.github.com/users/TGISer/followers","following_url":"https://api.github.com/users/TGISer/following{/other_user}","gists_url":"https://api.github.com/users/TGISer/gists{/gist_id}","starred_url":"https://api.github.com/users/TGISer/starred{/owner}{/repo}","subscriptions_url":"https://api.github.com/users/TGISer/subscriptions","organizations_url":"https://api.github.com/users/TGISer/orgs","repos_url":"https://api.github.com/users/TGISer/repos","events_url":"https://api.github.com/users/TGISer/events{/privacy}","received_events_url":"https://api.github.com/users/TGISer/received_events","type":"User","site_admin":false},"labels":[],"state":"open","locked":false,"assignee":null,"assignees":[],"milestone":null,"comments":0,"created_at":"2018-09-25T07:28:35Z","updated_at":"2018-09-25T07:28:35Z","closed_at":null,"author_association":"NONE","body":"F:\\ProgramData\\Anaconda3\\python.exe \"E:/coding/domain adaptation/Xlearn-master/pytorch/src/train.py\"\r\n{'name': 'JAN', 'trade_off': 1.0}\r\nTraceback (most recent call last):\r\n  File \"<string>\", line 1, in <module>\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\spawn.py\", line 105, in spawn_main\r\n    exitcode = _main(fd)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\spawn.py\", line 114, in _main\r\n    prepare(preparation_data)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\spawn.py\", line 225, in prepare\r\n    _fixup_main_from_path(data['init_main_from_path'])\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\spawn.py\", line 277, in _fixup_main_from_path\r\n    run_name=\"__mp_main__\")\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\runpy.py\", line 263, in run_path\r\n    pkg_name=pkg_name, script_name=fname)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\runpy.py\", line 96, in _run_module_code\r\n    mod_name, mod_spec, pkg_name, script_name)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\runpy.py\", line 85, in _run_code\r\n    exec(code, run_globals)\r\n  File \"E:\\coding\\domain adaptation\\Xlearn-master\\pytorch\\src\\train.py\", line 5, in <module>\r\n    import torch\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\site-packages\\torch\\__init__.py\", line 78, in <module>\r\n    from torch._C import *\r\nImportError: DLL load failed: 页面文件太小，无法完成操作。\r\nTraceback (most recent call last):\r\n  File \"E:/coding/domain adaptation/Xlearn-master/pytorch/src/train.py\", line 292, in <module>\r\n    transfer_classification(config)\r\n  File \"E:/coding/domain adaptation/Xlearn-master/pytorch/src/train.py\", line 224, in transfer_classification\r\n    print(image_classification_test(dset_loaders[\"target\"], nn.Sequential(base_network, bottleneck_layer, classifier_layer), test_10crop=prep_dict[\"target\"][\"test_10crop\"], gpu=use_gpu))\r\n  File \"E:/coding/domain adaptation/Xlearn-master/pytorch/src/train.py\", line 63, in image_classification_test\r\n    iter_test = [iter(loader['test'+str(i)]) for i in range(10)]\r\n  File \"E:/coding/domain adaptation/Xlearn-master/pytorch/src/train.py\", line 63, in <listcomp>\r\n    iter_test = [iter(loader['test'+str(i)]) for i in range(10)]\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\site-packages\\torch\\utils\\data\\dataloader.py\", line 451, in __iter__\r\n    return _DataLoaderIter(self)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\site-packages\\torch\\utils\\data\\dataloader.py\", line 239, in __init__\r\n    w.start()\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\process.py\", line 105, in start\r\n    self._popen = self._Popen(self)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\context.py\", line 223, in _Popen\r\n    return _default_context.get_context().Process._Popen(process_obj)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\context.py\", line 322, in _Popen\r\n    return Popen(process_obj)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\popen_spawn_win32.py\", line 65, in __init__\r\n    reduction.dump(process_obj, to_child)\r\n  File \"F:\\ProgramData\\Anaconda3\\lib\\multiprocessing\\reduction.py\", line 60, in dump\r\n    ForkingPickler(file, protocol).dump(obj)\r\nBrokenPipeError: [Errno 32] Broken pipe\r\n"}}
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