def forward(self, x, index=None):
size_i = x.shape[1:]
size_o = [
size_i[0],
]
size_o.extend(
transpose_out_size(size_i[1:], self._kernel, self._stride,
self._padding))
return max_unpool2d(x, index, size_i, size_o, self._kernel,
self._stride, self._padding)
def __new__(cls, x, index, filter, stride, padding):
filter, stride, padding = (tuplize(x)
for x in (filter, stride, padding))
in_shape = x.shape[1:]
out_shape = [
x.shape[1],
]
out_shape.extend(
transpose_out_size(in_shape[1:], filter, stride, padding))
return cls.calc_value(x, index, in_shape, out_shape, filter, stride,
padding)
def __new__(cls, x, w, b, filter=3, stride=1, padding=0, dilation=1):
filter, stride, padding, dilation = (tuplize(x)
for x in (filter, stride, padding,
dilation))
in_shape = x.shape[1:]
out_shape = [
w.shape[1],
]
out_shape.extend(
transpose_out_size(in_shape[1:], filter, stride, padding,
dilation))
return cls.calc_value(x, w, b, in_shape, out_shape, filter, stride,
padding, dilation)