For each element of x, with probability rate, outputs 0, and otherwise
scales up the input by 1 / (1-rate). The scaling is such that the expected
sum is unchanged.
By default, each element is kept or dropped independently. If noise_shape
is specified, it must be
to the shape of x, and only dimensions with noise_shape[i] == shape(x)[i]
will make independent decisions. For example, if shape(x) = [k, l, m, n]
and noise_shape = [k, 1, 1, n], each batch and channel component will be
kept independently and each row and column will be kept or not kept together.
A floating point tensor.
(deprecated) A deprecated alias for (1-rate).
A 1-D integer Tensor, representing the
shape for randomly generated keep/drop flags.