# Path: deep_architect/contrib/deep_learning_backend/backend.py
# def get_func(fname):
#     global _backend, _func_dict
#     if _backend is None or _func_dict is None:
#         raise RuntimeError('Backend is not set yet')
#     if fname not in _func_dict:
#         raise NotImplementedError(
#             'Function %s has not been implemented for backend %s' (fname,
#                                                                    _backend))
#     return _func_dict[fname]


from deep_architect.contrib.deep_learning_backend.backend import get_func


def dropout(h_keep_prob):
    fn = get_func('dropout')
    return fn(h_keep_prob=h_keep_prob)


def conv2d(h_num_filters, h_filter_width, h_stride, h_use_bias):

# Path: deep_architect/contrib/deep_learning_backend/backend.py
# def get_func(fname):
#     global _backend, _func_dict
#     if _backend is None or _func_dict is None:
#         raise RuntimeError('Backend is not set yet')
#     if fname not in _func_dict:
#         raise NotImplementedError(
#             'Function %s has not been implemented for backend %s' (fname,
#                                                                    _backend))
#     return _func_dict[fname]


# Path: deep_architect/contrib/deep_learning_backend/general_ops.py
from deep_architect.contrib.deep_learning_backend.backend import get_func



def dropout(h_keep_prob):
    fn = get_func('dropout')
    return fn(h_keep_prob=h_keep_prob)


def conv2d(h_num_filters, h_filter_width, h_stride, h_use_bias):

    fn = get_func('conv2d')