2
J'utilise Keras 2.0.6 pour construire des modèles. Je garde plusieurs modèles dans une liste appelée keras_models. Ainsi, au lieu simplement sauver un modèle, je veux sauver la liste complète des modèles dans un fichier de conserves au vinaigre comme ci-dessous:enregistrer une liste des modèles Keras
joblib.dump(keras_models, 'keras_models.pkl')
Cette approche fonctionne très bien quand j'ai une liste de modèle de forêt aléatoire sklearn et une liste de régression de crête des modèles. Cependant, j'ai eu les erreurs suivantes avec une liste de modèles keras. Une idée de ce qui n'allait pas? Existe-t-il un moyen d'enregistrer la liste complète des modèles keras dans un fichier? Merci!
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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