tf.keras.random.truncated_normal

Draw samples from a truncated normal distribution.

tf.keras.random.truncated_normal(
    shape, mean=0.0, stddev=1.0, dtype=None, seed=None
)

The values are drawn from a normal distribution with specified mean and standard deviation, discarding and re-drawing any samples that are more than two standard deviations from the mean.

shape The shape of the random values to generate.
mean Float, defaults to 0. Mean of the random values to generate.
stddev Float, defaults to 1. Standard deviation of the random values to generate.
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.