tf.raw_ops.ParameterizedTruncatedNormal

Outputs random values from a normal distribution.

Compat aliases for migration

tf.compat.v1.raw_ops.ParameterizedTruncatedNormal

tf.raw_ops.ParameterizedTruncatedNormal(
    shape, means, stdevs, minvals, maxvals, seed=0, seed2=0, name=None
)

The parameters may each be a

scalar which applies to the entire output, or a vector of length shape[0] which stores the parameters for each batch.

Args
`shape`	A `Tensor`. Must be one of the following types: `int32`, `int64`. The shape of the output tensor. Batches are indexed by the 0th dimension.
`means`	A `Tensor`. Must be one of the following types: `half`, `bfloat16`, `float32`, `float64`. The mean parameter of each batch.
`stdevs`	A `Tensor`. Must have the same type as `means`. The standard deviation parameter of each batch. Must be greater than 0.
`minvals`	A `Tensor`. Must have the same type as `means`. The minimum cutoff. May be -infinity.
`maxvals`	A `Tensor`. Must have the same type as `means`. The maximum cutoff. May be +infinity, and must be more than the minval for each batch.
`seed`	An optional `int`. Defaults to `0`. If either `seed` or `seed2` are set to be non-zero, the random number generator is seeded by the given seed. Otherwise, it is seeded by a random seed.
`seed2`	An optional `int`. Defaults to `0`. A second seed to avoid seed collision.
`name`	A name for the operation (optional).

Returns
A `Tensor`. Has the same type as `means`.

Args