tf.nn.dropout
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 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-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). |
rate |
A scalar Tensor with the same type as x. The probability that each element of x is discarded. |
| Returns | |
|---|---|
A Tensor of the same shape of x. |
| Raises | |
|---|---|
ValueError |
If rate is not in [0, 1) or if x is not a floating point tensor. |
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Licensed under the Creative Commons Attribution License 3.0.
Code samples licensed under the Apache 2.0 License.
https://www.tensorflow.org/versions/r1.15/api_docs/python/tf/nn/dropout