obj = _unpickle(fobj, filename, mmap_mode) File "/home/(...)/python3.5/site-packages/joblib/numpy_pickle.py", line 508, in _unpickle obj = unpickler.load() File "/usr/lib/python3.5/pickle.py", line 1039, in load dispatch[key[0]](self) KeyError: 0 同一应用程序对对象进行 pickle...
dispatch[key[0]](self)File"D:\softwear_install_position\anaconda3\envs\py3.7\lib\pickle.py",line1376,inload_global klass=self.find_class(module,name)File"D:\softwear_install_position\anaconda3\envs\py3.7\lib\pickle.py",line1427,infind_class__import__(module,level=0)ModuleNotFoundError:N...
File"D:\softwear_install_position\anaconda3\envs\py3.7\lib\pickle.py",line1088,inload dispatch[key[0]](self) File"D:\softwear_install_position\anaconda3\envs\py3.7\lib\pickle.py",line1376,inload_global klass=self.find_class(module,name) File"D:\softwear_install_position\anaconda3\envs\...
File "/home/ec2-user/.local/lib/python3.7/site-packages/joblib/numpy_pickle.py", line 504, in _unpickle obj = unpickler.load() File "/usr/lib64/python3.7/pickle.py", line 1088, in load dispatch[key[0]](self) File "/usr/lib64/python3.7/pickle.py", line 1376, in load_global kl...
问使用joblib.load从磁盘读取xgboost模型时出现TypeErrorEN本文编写于 205 天前，最后修改于 205 天前，...
File "d:\condaPythonEnvs\tf210\lib\pickle.py", line 1212, in load dispatch[key[0]](self) KeyError: 0 1. 2. 3. 4. 5. 6. 7. 8. 9. 解决办法: 重启计算机,看错误是否消失 创建一个新的conda python环境 安装python包的时候尽量选用pip install的方式,至少尽量不要混合使用conda install和pip...
Traceback(mostrecentcalllast):File"/home/lesteve/dev/joblib/joblib/numpy_pickle.py",line453,inloadobj=unpickler.load()File"/home/lesteve/miniconda3/lib/python3.4/pickle.py",line1038,inloaddispatch[key[0]](self)File"/home/lesteve/miniconda3/lib/python3.4/pickle.py",line1176,inload_binstrin...
File"d:\condaPythonEnvs\tf210\lib\pickle.py", line 1212,inload dispatch[key[0]](self) KeyError: 0 解决办法: 重启计算机,看错误是否消失 创建一个新的conda python环境 安装python包的时候尽量选用pip install的方式,至少尽量不要混合使用conda install和pip install ...
问调用joblib.load时未知的gbm类型ENgbm是通用梯度回归模型（Generalized Boosted Regression Models）简称。
>>> joblib.dump(to_persist, filename + '.lz4') # doctest: +ELLIPSIS ['...test.joblib.lz4'] >>> joblib.load(filename + '.lz4') [('a', [1, 2, 3]), ('b', array([0, 1, 2, 3, 4, 5, 6, 7, 8, 9]))]