Computes dropout.
tf.compat.v2.nn.dropout(
x, rate, noise_shape=None, seed=None, name=None
)
With probability rate
, drops elements of x
. Input that are kept are
scaled up by 1 / (1 - rate)
, otherwise outputs 0
. The scaling is so 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. |
rate
|
A scalar Tensor with the same type as x. The probability
that each element is dropped. For example, setting rate=0.1 would drop
10% of input elements.
|
noise_
|
A 1-D Tensor of type int32 , representing the
shape for randomly generated keep/drop flags.
|
seed
|
A Python integer. Used to create random seeds. See
tf.compat.v1.set_random_seed for behavior.
|
name
|
A name for this operation (optional). |
Returns | |
---|---|
A Tensor of the same shape of x .
|
Raises | |
---|---|
ValueError
|
If rate is not in (0, or if x is not a floating point
tensor.
|