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import torch
from .Module import Module
from .SpatialMaxPooling import SpatialMaxPooling
class SpatialMaxUnpooling(Module):
def __init__(self, poolingModule):
super(SpatialMaxUnpooling, self).__init__()
assert isinstance(poolingModule, SpatialMaxPooling)
assert poolingModule.kH == poolingModule.dH
assert poolingModule.kW == poolingModule.dW
self.pooling = poolingModule
def _setParams(self):
self.indices = self.pooling.indices
self.oheight = self.pooling.iheight
self.owidth = self.pooling.iwidth
def updateOutput(self, input):
self._setParams()
self._backend.SpatialMaxUnpooling_updateOutput(
self._backend.library_state,
input,
self.output,
self.indices,
self.owidth, self.oheight
)
return self.output
def updateGradInput(self, input, gradOutput):
self._setParams()
self._backend.SpatialMaxUnpooling_updateGradInput(
self._backend.library_state,
input,
gradOutput,
self.gradInput,
self.indices,
self.owidth, self.oheight
)
return self.gradInput
def __repr__(self):
return 'nn.SpatialMaxUnpooling associated to ' + self.pooling.__repr__()
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