def METHOD_NAME(self):
    """ Test torch.nn.init.uniform_(ShardedTensor, a, b) """
    spec = ChunkShardingSpec(
        dim=0,
        placements=[
            "rank:0/cuda:0",
            "rank:1/cuda:1",
            "rank:2/cuda:2",
            "rank:3/cuda:3",
        ],
    )
    h, w = 8, 2
    expected_h = 2
    expected_device = torch.device(f"cuda:{self.rank}")
    a, b = 10, 20
    seed = 1234
    dtype = torch.double
    st = sharded_tensor.empty(spec, h, w, dtype=dtype)
    self.assertEqual(1, len(st.local_shards()))
    # Clone local tensor to ensure torch.nn.init starts from the same input
    local_tensor_clone = torch.clone(st.local_shards()[0].tensor)
    torch.manual_seed(seed)
    torch.nn.init.uniform_(st, a=a, b=b)
    torch.manual_seed(seed)
    torch.nn.init.uniform_(local_tensor_clone, a=a, b=b)
    self.assertEqual(local_tensor_clone, st.local_shards()[0].tensor)