keras/src/backend/torch/random.py/normal
def normal(shape, mean=0.0, stddev=1.0, dtype=None, seed=None):
    dtype = dtype or floatx()
    dtype = to_torch_dtype(dtype)
    # Do not use generator during symbolic execution.
    if get_device() == "meta":
        return torch.normal(
            mean, stddev, size=shape, dtype=dtype, device=get_device()
        )
    generator = torch_seed_generator(seed)
    return torch.normal(
        mean,
        stddev,
        size=shape,
        generator=generator,
        dtype=dtype,
        device=get_device(),
    )