This op uses the algorithm by Marsaglia et al. to acquire samples via
transformation-rejection from pairs of uniform and normal random variables.
See http://dl.acm.org/citation.cfm?id=358414
Args
shape
A Tensor. Must be one of the following types: int32, int64.
1-D integer tensor. Shape of independent samples to draw from each
distribution described by the shape parameters given in alpha.
alpha
A Tensor. Must be one of the following types: half, float32, float64.
A tensor in which each scalar is a "shape" parameter describing the
associated gamma distribution.
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.
[[["Easy to understand","easyToUnderstand","thumb-up"],["Solved my problem","solvedMyProblem","thumb-up"],["Other","otherUp","thumb-up"]],[["Missing the information I need","missingTheInformationINeed","thumb-down"],["Too complicated / too many steps","tooComplicatedTooManySteps","thumb-down"],["Out of date","outOfDate","thumb-down"],["Samples / code issue","samplesCodeIssue","thumb-down"],["Other","otherDown","thumb-down"]],["Last updated 2024-01-23 UTC."],[],[]]