def METHOD_NAME(test_case):
    device = "cuda"
    channel = random(1, 32).to(int)
    height = random(1, 2).to(int)
    width = random(1024, 8192).to(int)
    def get_random_norm_shape():
        begin_axis = random(1, 3).to(int).value()
        return tuple((channel.value(), height.value(), width.value())[begin_axis:])
    m = torch.nn.LayerNorm(
        normalized_shape=get_random_norm_shape(),
        elementwise_affine=random().to(bool),
    ).to(device)
    x = random_tensor(ndim=4, dim1=channel, dim2=height, dim3=width).to(device)
    y = m(x)
    return y