tf.compat.v1.nn.dilation2d

Computes dropout. (deprecated arguments)

tf.compat.v1.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.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.

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.

TensorFlow

tf.compat / v1 / v1.nn.dilation2d

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tf.compat / v1 / v1.nn.dilation2d

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