tf.keras.random.beta

Draw samples from a Beta distribution.

tf.keras.random.beta(
    shape, alpha, beta, dtype=None, seed=None
)

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

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 Optional Python integer or instance of keras.random.SeedGenerator. By default, the seed argument is None, and an internal global keras.random.SeedGenerator is used. The seed argument can be used to ensure deterministic (repeatable) random number generation. Note that passing an integer as the seed value will produce the same random values for each call. To generate different random values for repeated calls, an instance of keras.random.SeedGenerator must be provided as the seed value. Remark concerning the JAX backend: When tracing functions with the JAX backend the global keras.random.SeedGenerator is not supported. Therefore, during tracing the default value seed=None will produce an error, and a seed argument must be provided.