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
broadcastable
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.
Args
x
A floating point tensor.
keep_prob
(deprecated) A deprecated alias for (1-rate).
noise_shape
A 1-D Tensor of type int32, representing the
shape for randomly generated keep/drop flags.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2020-10-01 UTC."],[],[]]