def dropout(x, keep_prob, name=None):
"""
Computes dropout.
With probability `keep_prob`, outputs the input element scaled up by
`1 / keep_prob`, otherwise outputs `0`. The scaling is so that the expected
sum is unchanged.
Args:
x: A tensor.
keep_prob: A float. The probability that each element is kept.
name: A name for this operation (optional).
Returns:
A Tensor of the same shape of `x`.
"""
return ops.Dropout(x, 1 - keep_prob)
def Setup(self, bottom):
super(DropoutLayer, self).Setup(bottom)
input = bottom[0] if isinstance(bottom, list) else bottom
return ops.Dropout(input, **self._param)
def dropout(x, keep_prob, name=None):
return ops.Dropout(x, 1 - keep_prob)
def dropout(x, keep_prob, name=None):
return _ops.Dropout(x, 1. - keep_prob, name=name)
def LayerSetup(self, bottom):
return _ops.Dropout(bottom, **self.arguments)
