|TensorFlow 2.0 version||View source on GitHub|
Computes dropout. (deprecated arguments)
tf.nn.dropout( x, keep_prob=None, noise_shape=None, seed=None, name=None, rate=None )
For each element of
x, with probability
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
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]
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.
x: A floating point tensor.
keep_prob: (deprecated) A deprecated alias for
noise_shape: A 1-D
int32, representing the shape for randomly generated keep/drop flags.
seed: A Python integer. Used to create random seeds. See
name: A name for this operation (optional).
rate: A scalar
Tensorwith the same type as
x. The probability that each element of
A Tensor of the same shape of
rateis not in
[0, 1)or if
xis not a floating point tensor.