Returns a dropout op applied to the input.
tf.contrib.layers.dropout(
inputs, keep_prob=0.5, noise_shape=None, is_training=True,
outputs_collections=None, scope=None, seed=None
)
With probability keep_prob
, outputs the input element scaled up by
1 / keep_prob
, otherwise outputs 0
. The scaling is so that the expected
sum is unchanged.
Args |
inputs
|
The tensor to pass to the nn.dropout op.
|
keep_prob
|
A scalar Tensor with the same type as x. The probability that
each element is kept.
|
noise_shape
|
A 1-D Tensor of type int32 , representing the shape for
randomly generated keep/drop flags.
|
is_training
|
A bool Tensor indicating whether or not the model is in
training mode. If so, dropout is applied and values scaled. Otherwise,
inputs is returned.
|
outputs_collections
|
Collection to add the outputs.
|
scope
|
Optional scope for name_scope.
|
seed
|
A Python integer. Used to create random seeds. See
tf.compat.v1.set_random_seed for behavior.
|
Returns |
A tensor representing the output of the operation.
|