def METHOD_NAME(device='cpu', batch_size=32, shape=[1e5], niter=3):
    batch_size = 4
    shape = [100000]
    val_range = [np.float32(10.0), np.nextafter(np.float32(10.0), np.float32(11.0))]
    pipe = Pipeline(batch_size=batch_size, device_id=0, num_threads=3, seed=123456)
    with pipe:
        pipe.set_outputs(dali.fn.random.uniform(device=device, range=val_range, shape=shape))
    pipe.build()
    for it in range(niter):
        outputs = pipe.run()
        data_out = outputs[0].as_cpu() \
            if isinstance(outputs[0], TensorListGPU) else outputs[0]
        for i in range(batch_size):
            data = np.array(data_out[i])
            assert (val_range[0] == data).all(), \
                f"{data} is outside of requested range"