keras/src/random/random.py/truncated_normal
def truncated_normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
    """Draw samples from a truncated normal distribution.

    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.

    Args:
        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`.
    """
    return backend.random.truncated_normal(
        shape, mean=mean, stddev=stddev, dtype=dtype, seed=seed
    )