keras/src/random/random.py/beta
def beta(shape, alpha, beta, dtype=None, seed=None):
    """Draw samples from a Beta distribution.

    The values are drawm from a Beta distribution parametrized
    by alpha and beta.

    Args:
        shape: The shape of the random values to generate.
        alpha: Float or an array of floats representing the first
            parameter alpha. Must be broadcastable with `beta` and `shape`.
        beta: Float or an array of floats representing the second
            parameter beta. Must be broadcastable with `alpha` and `shape`.
        dtype: Optional dtype of the tensor. Only floating point types are
            supported. If not specified, `keras.config.floatx()` is used,
            which defaults to `float32` unless you configured it otherwise (via
            `keras.config.set_floatx(float_dtype)`).
        seed: A Python integer or instance of
            `keras.random.SeedGenerator`.
            Used to make the behavior of the initializer
            deterministic. Note that an initializer seeded with an integer
            or None (unseeded) will produce the same random values
            across multiple calls. To get different random values
            across multiple calls, use as seed an instance
            of `keras.random.SeedGenerator`.
    """
    return backend.random.beta(
        shape=shape, alpha=alpha, beta=beta, dtype=dtype, seed=seed
    )