tf.nn.dropout(
x,
keep_prob=None,
noise_shape=None,
seed=None,
name=None,
rate=None
)
Defined in tensorflow/python/ops/nn_ops.py
.
Computes dropout. (deprecated arguments)
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-DTensor
of typeint32
, representing the shape for randomly generated keep/drop flags.seed
: A Python integer. Used to create random seeds. Seetf.set_random_seed
for behavior.name
: A name for this operation (optional).rate
: A scalarTensor
with the same type asx
. The probability that each element ofx
is discarded.
Returns:
A Tensor of the same shape of x
.
Raises:
ValueError
: Ifrate
is not in[0, 1)
or ifx
is not a floating point tensor.