tf.contrib.layers.dropout

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.