tf.keras.random.binomial

Draw samples from a Binomial distribution.

tf.keras.random.binomial(
    shape, counts, probabilities, dtype=None, seed=None
)

The values are drawn from a Binomial distribution with specified trial count and probability of success.

shape The shape of the random values to generate.
counts A number or array of numbers representing the number of trials. It must be broadcastable with probabilities.
probabilities A float or array of floats representing the probability of success of an individual event. It must be broadcastable with counts.
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.