# Path: gelato/layers/base.py
# def bayes(layercls, stack=1):
#     try:
#         issubcls = issubclass(layercls, lasagne.layers.base.Layer)
#     except TypeError:
#         raise TypeError('{} needs to be a Layer subclass'
#                         .format(layercls))
#     if issubcls:
#         if type(layercls) is LayerModelMeta:
#             raise TypeError('{} is already bayesian'
#                             .format(layercls))
#         else:
#             @six.add_metaclass(LayerModelMeta)
#             class BayesianAnalog(layercls, pm.Model):
#                 pass
#             frm = inspect.stack()[stack]
#             mod = inspect.getmodule(frm[0])
#             if mod is None:
#                 modname = '__main__'
#             else:
#                 modname = mod.__name__
#             BayesianAnalog.__module__ = modname
#             BayesianAnalog.__doc__ = layercls.__doc__
#             BayesianAnalog.__name__ = layercls.__name__
#             return BayesianAnalog
#     else:
#         raise TypeError('{} needs to be a Layer subclass'
#                         .format(layercls))


import sys
import lasagne.layers.conv as __cloned
from .base import bayes as __bayes
__module = sys.modules[__name__]
del sys
__all__ = []
for obj_name in __cloned.__all__:

# Path: gelato/layers/base.py
# def bayes(layercls, stack=1):
#     try:
#         issubcls = issubclass(layercls, lasagne.layers.base.Layer)
#     except TypeError:
#         raise TypeError('{} needs to be a Layer subclass'
#                         .format(layercls))
#     if issubcls:
#         if type(layercls) is LayerModelMeta:
#             raise TypeError('{} is already bayesian'
#                             .format(layercls))
#         else:
#             @six.add_metaclass(LayerModelMeta)
#             class BayesianAnalog(layercls, pm.Model):
#                 pass
#             frm = inspect.stack()[stack]
#             mod = inspect.getmodule(frm[0])
#             if mod is None:
#                 modname = '__main__'
#             else:
#                 modname = mod.__name__
#             BayesianAnalog.__module__ = modname
#             BayesianAnalog.__doc__ = layercls.__doc__
#             BayesianAnalog.__name__ = layercls.__name__
#             return BayesianAnalog
#     else:
#         raise TypeError('{} needs to be a Layer subclass'
#                         .format(layercls))


# Path: gelato/layers/conv.py
import sys
import lasagne.layers.conv as __cloned
from .base import bayes as __bayes

__module = sys.modules[__name__]
del sys
__all__ = []
for obj_name in __cloned.__all__:

    try: