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import torch
from .Module import Module
from .utils import clear
class RReLU(Module):
def __init__(self, lower=1./8, upper=1./3, inplace=False):
super(RReLU, self).__init__()
self.lower = lower
self.upper = upper
self.inplace = inplace
assert self.lower <= self.upper and self.lower >= 0 and self.upper >= 0
self.noise = torch.Tensor()
self.train = True
def updateOutput(self, input):
self._backend.RReLU_updateOutput(
self._backend.library_state,
input,
self.output,
self.noise,
self.lower,
self.upper,
self.train,
self.inplace,
torch.default_generator if not input.is_cuda else 0
)
return self.output
def updateGradInput(self, input, gradOutput):
self._backend.RReLU_updateGradInput(
self._backend.library_state,
input,
gradOutput,
self.gradInput,
self.noise,
self.lower,
self.upper,
self.train,
self.inplace
)
return self.gradInput
def __repr__(self):
return super(RReLU, self).__repr__() + '({:.4f}, {:.4f})'.format(self.lower, self.upper)
def clearState(self):
clear(self, 'noise')
return super(RReLU, self).clearState()
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