Otherwise, Knuth's algorithm is used to acquire samples via multiplying uniform
random variables.
See Donald E. Knuth (1969). Seminumerical Algorithms. The Art of Computer
Programming, Volume 2. Addison Wesley
  }];

  let arguments = (ins
    Arg<TF_I32OrI64Tensor, [{1-D integer tensor. Shape of independent samples to draw from each

*   `tf.keras`:

    *   `Model.fit` major improvements:
        *   You can now use custom training logic with `Model.fit` by overriding
            `Model.train_step`.
        *   Easily write state-of-the-art training loops without worrying about
            all of the features `Model.fit` handles for you (distribution
            strategies, callbacks, data formats, looping logic, etc)
        *   See the default