def __init__(self,
filters,
batch_size,
input_space,
output_axes=('b', 'c', 0, 1),
subsample=(1, 1),
border_mode='valid',
filters_shape=None,
message=''):
assert batch_size is None or batch_size > 0
self._input_space = input_space
self._output_axes = output_axes
self._subsample = tuple(subsample)
self._border_mode = border_mode
super(Cudnn2D, self).__init__(
filters=filters,
img_shape=(batch_size, input_space.num_channels,
input_space.shape[0], input_space.shape[1]),
subsample=self._subsample,
border_mode=border_mode,
filters_shape=filters.get_value(borrow=True).shape,
message=message)
# conv_op has to be changed
self._conv_op = GpuDnnConv()
self._desc = GpuDnnConvDesc(border_mode=border_mode,
subsample=self._subsample,
conv_mode='conv')
