提交 bfecee32 authored 作者: sebastien-j's avatar sebastien-j

Minor changes

上级 e0afde95
...@@ -965,16 +965,17 @@ class DownsampleFactorMaxGradGrad(Op): ...@@ -965,16 +965,17 @@ class DownsampleFactorMaxGradGrad(Op):
raise NotImplementedError( raise NotImplementedError(
'padding_h and padding_w must be smaller than strides') 'padding_h and padding_w must be smaller than strides')
self.mode = mode self.mode = mode
assert self.mode == 'max'
def make_node(self, x, maxout, gz): def make_node(self, x, maxout, gz):
# make_node should only be called by the grad function of # make_node should only be called by the grad function of
# MaxPoolGrad, so these asserts should not fail. # MaxPoolGrad, so these asserts should not fail.
assert isinstance(x, Variable) and x.ndim == 4
assert isinstance(maxout, Variable) and maxout.ndim == 4
assert isinstance(gz, Variable) and gz.ndim == 4
x = tensor.as_tensor_variable(x) x = tensor.as_tensor_variable(x)
maxout = tensor.as_tensor_variable(maxout) maxout = tensor.as_tensor_variable(maxout)
gz = tensor.as_tensor_variable(gz) gz = tensor.as_tensor_variable(gz)
assert x.ndim == 4
assert maxout.ndim == 4
assert gz.ndim == 4
return Apply(self, [x, maxout, gz], [x.type()]) return Apply(self, [x, maxout, gz], [x.type()])
......
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