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# tf.compat.v1.nn.dropout

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.

`x` A floating point tensor.
`keep_prob` (deprecated) A deprecated alias for `(1-rate)`.
`noise_shape` A 1-D integer `Tensor`, representing the shape for randomly generated keep/drop flags.
`seed` A Python integer. Used to create random seeds. See `tf.random.set_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.

A Tensor of the same shape of `x`.

`ValueError` If `rate` is not in `[0, 1)` or if `x` is not a floating point tensor.

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