UnpicklingError:遇到load persistent id指令，但未指定persistent_load函数
UnpicklingError:遇到load persistent id指令，但未指定persistent_load函数
提问于 2021-02-24 00:55:48
我正在尝试运行一个名为api.py的python文件。在这个文件中，我加载了深度学习模型的pickle文件，该模型是使用PyTorch构建和训练的。
api.py在api.py中，下面给出的函数是最重要的。
def load_model_weights(model_architecture, weights_path):
if os.path.isfile(weights_path):
cherrypy.log("CHERRYPYLOG Loading model from: {}".format(weights_path))
model_architecture.load_state_dict(torch.load(weights_path))
else:
raise ValueError("Path not found {}".format(weights_path))
def load_recommender(vector_dim, hidden, activation, dropout, weights_path):
rencoder_api = model.AutoEncoder(layer_sizes=[vector_dim] + [int(l) for l in hidden.split(',')],
nl_type=activation,
is_constrained=False,
dp_drop_prob=dropout,
last_layer_activations=False)
load_model_weights(rencoder_api, weights_path)
rencoder_api.eval()
rencoder_api = rencoder_api.cuda()
return rencoder_api目录结构
?MP1
┣ ?.ipynb_checkpoints
┃ ┗ ?RS_netflix3months_100epochs_64,128,128-checkpoint.ipynb
┣ ?data
┃ ┣ ?AutoEncoder.png
┃ ┣ ?collaborative_filtering.gif
┃ ┣ ?movie_titles.txt
┃ ┗ ?shut_up.gif
┣ ?DeepRecommender
┃ ┣ ?data_utils
┃ ┃ ┣ ?movielens_data_convert.py
┃ ┃ ┗ ?netflix_data_convert.py
┃ ┣ ?reco_encoder
┃ ┃ ┣ ?data
┃ ┃ ┃ ┣ ?__pycache__
┃ ┃ ┃ ┃ ┣ ?input_layer.cpython-37.pyc
┃ ┃ ┃ ┃ ┣ ?input_layer_api.cpython-37.pyc
┃ ┃ ┃ ┃ ┗ ?__init__.cpython-37.pyc
┃ ┃ ┃ ┣ ?input_layer.py
┃ ┃ ┃ ┣ ?input_layer_api.py
┃ ┃ ┃ ┗ ?__init__.py
┃ ┃ ┣ ?model
┃ ┃ ┃ ┣ ?__pycache__
┃ ┃ ┃ ┃ ┣ ?model.cpython-37.pyc
┃ ┃ ┃ ┃ ┗ ?__init__.cpython-37.pyc
┃ ┃ ┃ ┣ ?model.py
┃ ┃ ┃ ┗ ?__init__.py
┃ ┃ ┣ ?__pycache__
┃ ┃ ┃ ┗ ?__init__.cpython-37.pyc
┃ ┃ ┗ ?__init__.py
┃ ┣ ?__pycache__
┃ ┃ ┗ ?__init__.cpython-37.pyc
┃ ┣ ?compute_RMSE.py
┃ ┣ ?infer.py
┃ ┣ ?run.py
┃ ┗ ?__init__.py
┣ ?model_save
┃ ┣ ?model.epoch_99
┃ ┃ ┗ ?archive
┃ ┃ ┃ ┣ ?data
┃ ┃ ┃ ┃ ┣ ?92901648
┃ ┃ ┃ ┃ ┣ ?92901728
┃ ┃ ┃ ┃ ┣ ?92901808
┃ ┃ ┃ ┃ ┣ ?92901888
┃ ┃ ┃ ┃ ┣ ?92901968
┃ ┃ ┃ ┃ ┣ ?92902048
┃ ┃ ┃ ┃ ┣ ?92902128
┃ ┃ ┃ ┃ ┣ ?92902208
┃ ┃ ┃ ┃ ┣ ?92902288
┃ ┃ ┃ ┃ ┣ ?92902368
┃ ┃ ┃ ┃ ┣ ?92902448
┃ ┃ ┃ ┃ ┗ ?92902608
┃ ┃ ┃ ┣ ?data.pkl
┃ ┃ ┃ ┗ ?version
┃ ┣ ?model.epoch_99.zip
┃ ┗ ?model.onnx
┣ ?Netflix
┃ ┣ ?N1Y_TEST
┃ ┃ ┗ ?n1y.test.txt
┃ ┣ ?N1Y_TRAIN
┃ ┃ ┗ ?n1y.train.txt
┃ ┣ ?N1Y_VALID
┃ ┃ ┗ ?n1y.valid.txt
┃ ┣ ?N3M_TEST
┃ ┃ ┗ ?n3m.test.txt
┃ ┣ ?N3M_TRAIN
┃ ┃ ┗ ?n3m.train.txt
┃ ┣ ?N3M_VALID
┃ ┃ ┗ ?n3m.valid.txt
┃ ┣ ?N6M_TEST
┃ ┃ ┗ ?n6m.test.txt
┃ ┣ ?N6M_TRAIN
┃ ┃ ┗ ?n6m.train.txt
┃ ┣ ?N6M_VALID
┃ ┃ ┗ ?n6m.valid.txt
┃ ┣ ?NF_TEST
┃ ┃ ┗ ?nf.test.txt
┃ ┣ ?NF_TRAIN
┃ ┃ ┗ ?nf.train.txt
┃ ┗ ?NF_VALID
┃ ┃ ┗ ?nf.valid.txt
┣ ?test
┃ ┣ ?testData_iRec
┃ ┃ ┣ ?.part-00199-f683aa3b-8840-4835-b8bc-a8d1eaa11c78.txt.crc
┃ ┃ ┣ ?part-00000-f683aa3b-8840-4835-b8bc-a8d1eaa11c78.txt
┃ ┃ ┣ ?part-00003-f683aa3b-8840-4835-b8bc-a8d1eaa11c78.txt
┃ ┃ ┗ ?_SUCCESS
┃ ┣ ?testData_uRec
┃ ┃ ┣ ?.part-00000-4a844096-8dd9-425e-9d9d-bd9062cc6940.txt.crc
┃ ┃ ┣ ?._SUCCESS.crc
┃ ┃ ┣ ?part-00161-4a844096-8dd9-425e-9d9d-bd9062cc6940.txt
┃ ┃ ┣ ?part-00196-4a844096-8dd9-425e-9d9d-bd9062cc6940.txt
┃ ┃ ┗ ?part-00199-4a844096-8dd9-425e-9d9d-bd9062cc6940.txt
┃ ┣ ?data_layer_tests.py
┃ ┣ ?test_model.py
┃ ┗ ?__init__.py
┣ ?__pycache__
┃ ┣ ?api.cpython-37.pyc
┃ ┣ ?load_test.cpython-37.pyc
┃ ┣ ?parameters.cpython-37.pyc
┃ ┗ ?utils.cpython-37.pyc
┣ ?api.py
┣ ?compute_RMSE.py
┣ ?load_test.py
┣ ?logger.py
┣ ?netflix_1y_test.csv
┣ ?netflix_1y_train.csv
┣ ?netflix_1y_valid.csv
┣ ?netflix_3m_test.csv
┣ ?netflix_3m_train.csv
┣ ?netflix_3m_valid.csv
┣ ?netflix_6m_test.csv
┣ ?netflix_6m_train.csv
┣ ?netflix_6m_valid.csv
┣ ?netflix_full_test.csv
┣ ?netflix_full_train.csv
┣ ?netflix_full_valid.csv
┣ ?parameters.py
┣ ?preds.txt
┣ ?RS_netflix3months_100epochs_64,128,128.ipynb
┗ ?utils.py我收到这样的错误(serialization.py)。有人能帮我纠正这个错误吗？
D:\Anaconda\envs\practise\lib\site-packages\torch\serialization.py in _legacy_load(f, map_location, pickle_module, **pickle_load_args)
762 "functionality.")
763
--> 764 magic_number = pickle_module.load(f, **pickle_load_args)
765 if magic_number != MAGIC_NUMBER:
766 raise RuntimeError("Invalid magic number; corrupt file?")
UnpicklingError: A load persistent id instruction was encountered,
but no persistent_load function was specified.回答 1
Stack Overflow用户
回答已采纳
发布于 2021-03-02 00:32:06
在搜索PyTorch文档后，我最终将模型保存为ONNX格式，然后将该ONNX模型加载到PyTorch模型中，并将其用于推理。
import onnx
from onnx2pytorch import ConvertModel
def load_model_weights(model_architecture, weights_path):
if os.path.isfile("model.onnx"):
cherrypy.log("CHERRYPYLOG Loading model from: {}".format(weights_path))
onnx_model = onnx.load("model.onnx")
pytorch_model = ConvertModel(onnx_model)
## model_architecture.load_state_dict(torch.load(weights_path))
else:
raise ValueError("Path not found {}".format(weights_path))
def load_recommender(vector_dim, hidden, activation, dropout, weights_path):
rencoder_api = model.AutoEncoder(layer_sizes=[vector_dim] + [int(l) for l in hidden.split(',')],
nl_type=activation,
is_constrained=False,
dp_drop_prob=dropout,
last_layer_activations=False)
load_model_weights(rencoder_api, weights_path)
rencoder_api.eval()
rencoder_api = rencoder_api.cuda()
return rencoder_api一些有用的资源：
页面原文内容由Stack Overflow提供。腾讯云小微IT领域专用引擎提供翻译支持
原文链接：
https://stackoverflow.com/questions/66337562
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