[Adam/AdamW] Update adamw.py

[HydrogenSulfate]

amsgrad will be supported in PaddlePaddle/Paddle#68079 and added into parameter list of those two optimizers, therefore number of return value of _C_ops.XX will be incresed by 1. So _ need to be replaced with *_ for compatibility.

[megemini]

另外，貌似应该把 moment2_max 为 None 也传进去，如：

In [45]: out = _legacy_C_ops.adamw(
    ...:     param,
    ...:     grad,
    ...:     lr,
    ...:     moment1,
    ...:     moment2,
    ...:     None,   # `momen2_max` ，如果不需要 `amsgrad`，则传入 `None`
    ...:     beta1_pow,
    ...:     beta2_pow,
    ...:     None,   # `master_param` 根据实际需要传入参数
    ...:     param,
    ...:     moment1,
    ...:     moment2,
    ...:     None,   # `momen2_max` ，如果不需要 `amsgrad`，则传入 `None`
    ...:     beta1_pow,
    ...:     beta2_pow,
    ...:     None,   # `master_param` 根据实际需要传入参数
    ...:     'epsilon',
    ...:     epsilon,
    ...:     'lazy_mode',
    ...:     False,
    ...:     'min_row_size_to_use_multithread',
    ...:     1000,
    ...:     'beta1',
    ...:     beta1,
    ...:     'beta2',
    ...:     beta2,
    ...:     "with_decay",
    ...:     True,
    ...:     'coeff',
    ...:     0.5,
    ...:     'multi_precision',
    ...:     False,
    ...:     'lr_ratio',
    ...:     1.0,
    ...:     'amsgrad',  # `amsgrad` 参数
    ...:     False,      # `amsgrad` 参数
    ...: )

In [46]: out
Out[46]: 
(Tensor(shape=[102, 105], dtype=float32, place=Place(gpu:0), stop_gradient=True,
        [[ 0.20898449,  0.89920276,  0.67242330, ...,  0.26126957,
           0.79362839,  0.82994431],
         [-0.41922054, -0.49964213, -0.72876191, ...,  0.64584875,
           0.38303095,  0.07835867],
         [ 0.82518733, -0.13006617, -0.18193051, ..., -0.83834726,
          -0.48943013,  0.28921935],
         ...,
         [-0.11833674, -0.87520474,  0.71153826, ...,  0.88105798,
          -0.84247899, -0.03978884],
         [ 0.03530697, -0.51926482, -0.60509771, ..., -0.93831873,
          -0.40703350,  0.06399230],
         [-0.96511489,  0.76393193,  0.27214301, ..., -0.11625432,
          -0.12905845, -0.89011657]]),
 Tensor(shape=[102, 105], dtype=float32, place=Place(gpu:0), stop_gradient=True,
        [[ 0.11505818, -0.12621984, -0.01848486, ...,  0.22509800,
          -0.09953045,  0.56122953],
         [ 0.05467438,  0.15807387, -0.00716698, ..., -0.16195901,
          -0.27719164,  0.73311120],
         [-0.21436734, -0.12942475, -0.19450223, ...,  0.26065761,
          -0.09446586,  0.61139995],
         ...,
         [ 0.01895352, -0.44893426, -0.35492349, ...,  0.78992486,
          -0.46006823,  0.70998996],
         [-0.83486271,  0.08806995, -0.31217605, ..., -0.04586679,
           0.63772619, -0.62238657],
         [ 0.40758044,  0.40442133,  0.29918492, ...,  0.60868609,
           0.73768240,  0.27699226]]),
 Tensor(shape=[102, 105], dtype=float32, place=Place(gpu:0), stop_gradient=True,
        [[0.04723934, 0.06505238, 0.23348683, ..., 0.10994066, 0.22805302,
          0.44461903],
         [0.03345066, 0.11195458, 0.18727647, ..., 0.22885345, 0.15290459,
          0.71300763],
         [0.08683055, 0.22121914, 0.06403468, ..., 0.06969104, 0.13063110,
          0.51002014],
         ...,
         [0.11580127, 0.34216970, 0.38666964, ..., 0.77789527, 0.38964579,
          0.50754905],
         [0.68814623, 0.03124339, 0.27777275, ..., 0.22106472, 0.46024293,
          0.40622491],
         [0.32853597, 0.28381625, 0.27526388, ..., 0.47823176, 0.61193144,
          0.35178134]]),
 Tensor(Not initialized),
 Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
        0.01142096),
 Tensor(shape=[], dtype=float32, place=Place(gpu:0), stop_gradient=True,
        0.03978442),
 Tensor(Not initialized))

对应的 moment2_max_out 为 Tensor(Not initialized) ～