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我使用Keras 2.0.6构建模型。我在名为keras_models的列表中保留了几个模型。因此，而不是仅仅节省一个模式，我想的车型整个列表保存到泡菜文件象下面这样：保存Keras模型列表
joblib.dump(keras_models, 'keras_models.pkl')
这种方法工作得很好，当我有sklearn随机森林模型的列表和岭回归名单楷模。但是，我收到了keras模型列表中的以下错误。任何想法有什么不对？有没有办法将整个keras模型列表保存到一个文件中？谢谢！
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AttributeError Traceback (most recent call last)
/usr/lib/python3.4/pickle.py in _getattribute(obj, name, allow_qualname)
271 try:
--> 272 obj = getattr(obj, subpath)
273 except AttributeError:
AttributeError: 'module' object has no attribute 'lock'
During handling of the above exception, another exception occurred:
AttributeError Traceback (most recent call last)
/usr/lib/python3.4/pickle.py in save_global(self, obj, name)
910 module = sys.modules[module_name]
--> 911 obj2 = _getattribute(module, name, allow_qualname=self.proto >= 4)
912 except (ImportError, KeyError, AttributeError):
/usr/lib/python3.4/pickle.py in _getattribute(obj, name, allow_qualname)
274 raise AttributeError("Can't get attribute {!r} on {!r}"
--> 275 .format(name, obj))
276 return obj
AttributeError: Can't get attribute 'lock' on <module '_thread' (built-in)>
During handling of the above exception, another exception occurred:
PicklingError Traceback (most recent call last)
<ipython-input-5-e038764ff1dd> in <module>()
145 #---------------------------------------------------------------------------
146
--> 147 joblib.dump(keras_models, 'keras_models_20170928.pkl')
148
149 keras_metric_df.to_pickle('keras_metric_20170928.pkl')
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in dump(value, filename, compress, protocol, cache_size)
481 elif is_filename:
482 with open(filename, 'wb') as f:
--> 483 NumpyPickler(f, protocol=protocol).dump(value)
484 else:
485 NumpyPickler(filename, protocol=protocol).dump(value)
/usr/lib/python3.4/pickle.py in dump(self, obj)
410 if self.proto >= 4:
411 self.framer.start_framing()
--> 412 self.save(obj)
413 self.write(STOP)
414 self.framer.end_framing()
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_list(self, obj)
772
773 self.memoize(obj)
--> 774 self._batch_appends(obj)
775
776 dispatch[list] = save_list
/usr/lib/python3.4/pickle.py in _batch_appends(self, items)
796 write(MARK)
797 for x in tmp:
--> 798 save(x)
799 write(APPENDS)
800 elif n:
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
522
523 # Save the reduce() output and finally memoize the object
--> 524 self.save_reduce(obj=obj, *rv)
525
526 def persistent_id(self, obj):
/usr/lib/python3.4/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
625
626 if state is not None:
--> 627 save(state)
628 write(BUILD)
629
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_dict(self, obj)
812
813 self.memoize(obj)
--> 814 self._batch_setitems(obj.items())
815
816 dispatch[dict] = save_dict
/usr/lib/python3.4/pickle.py in _batch_setitems(self, items)
838 for k, v in tmp:
839 save(k)
--> 840 save(v)
841 write(SETITEMS)
842 elif n:
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_list(self, obj)
772
773 self.memoize(obj)
--> 774 self._batch_appends(obj)
775
776 dispatch[list] = save_list
/usr/lib/python3.4/pickle.py in _batch_appends(self, items)
799 write(APPENDS)
800 elif n:
--> 801 save(tmp[0])
802 write(APPEND)
803 # else tmp is empty, and we're done
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
522
523 # Save the reduce() output and finally memoize the object
--> 524 self.save_reduce(obj=obj, *rv)
525
526 def persistent_id(self, obj):
/usr/lib/python3.4/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
625
626 if state is not None:
--> 627 save(state)
628 write(BUILD)
629
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_dict(self, obj)
812
813 self.memoize(obj)
--> 814 self._batch_setitems(obj.items())
815
816 dispatch[dict] = save_dict
/usr/lib/python3.4/pickle.py in _batch_setitems(self, items)
838 for k, v in tmp:
839 save(k)
--> 840 save(v)
841 write(SETITEMS)
842 elif n:
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
522
523 # Save the reduce() output and finally memoize the object
--> 524 self.save_reduce(obj=obj, *rv)
525
526 def persistent_id(self, obj):
/usr/lib/python3.4/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
625
626 if state is not None:
--> 627 save(state)
628 write(BUILD)
629
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_dict(self, obj)
812
813 self.memoize(obj)
--> 814 self._batch_setitems(obj.items())
815
816 dispatch[dict] = save_dict
/usr/lib/python3.4/pickle.py in _batch_setitems(self, items)
838 for k, v in tmp:
839 save(k)
--> 840 save(v)
841 write(SETITEMS)
842 elif n:
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
522
523 # Save the reduce() output and finally memoize the object
--> 524 self.save_reduce(obj=obj, *rv)
525
526 def persistent_id(self, obj):
/usr/lib/python3.4/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
625
626 if state is not None:
--> 627 save(state)
628 write(BUILD)
629
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_dict(self, obj)
812
813 self.memoize(obj)
--> 814 self._batch_setitems(obj.items())
815
816 dispatch[dict] = save_dict
/usr/lib/python3.4/pickle.py in _batch_setitems(self, items)
838 for k, v in tmp:
839 save(k)
--> 840 save(v)
841 write(SETITEMS)
842 elif n:
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
522
523 # Save the reduce() output and finally memoize the object
--> 524 self.save_reduce(obj=obj, *rv)
525
526 def persistent_id(self, obj):
/usr/lib/python3.4/pickle.py in save_reduce(self, func, args, state, listitems, dictitems, obj)
596 "args[0] from __newobj__ args has the wrong class")
597 args = args[1:]
--> 598 save(cls)
599 save(args)
600 write(NEWOBJ)
/usr/local/lib/python3.4/dist-packages/sklearn/externals/joblib/numpy_pickle.py in save(self, obj)
278 return
279
--> 280 return Pickler.save(self, obj)
281
282
/usr/lib/python3.4/pickle.py in save(self, obj, save_persistent_id)
477 f = self.dispatch.get(t)
478 if f is not None:
--> 479 f(self, obj) # Call unbound method with explicit self
480 return
481
/usr/lib/python3.4/pickle.py in save_type(self, obj)
964 elif obj is type(...):
965 return self.save_reduce(type, (...,), obj=obj)
--> 966 return self.save_global(obj)
967
968 dispatch[FunctionType] = save_global
/usr/lib/python3.4/pickle.py in save_global(self, obj, name)
913 raise PicklingError(
914 "Can't pickle %r: it's not found as %s.%s" %
--> 915 (obj, module_name, name))
916 else:
917 if obj2 is not obj:
PicklingError: Can't pickle <class '_thread.lock'>: it's not found as _thread.lock