text: # Copyright (C) 2022. Huawei Technologies Co., Ltd. All rights reserved.
  
  # Permission is hereby granted, free of charge, to any person obtaining a copy of this software and associated documentation files (the "Software"),
  # to deal in the Software without restriction, including without limitation the rights to use, copy, modify, merge, publish, distribute, sublicense,
  # and/or sell copies of the Software, and to permit persons to whom the Software is furnished to do so, subject to the following conditions:
  
  # The above copyright notice and this permission notice shall be included in all copies or substantial portions of the Software.
  
  # THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR IMPLIED, INCLUDING BUT NOT LIMITED TO THE
  # WARRANTIES OF MERCHANTABILITY, FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE AUTHORS OR
  # COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
  # OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE SOFTWARE.
  
  
  import torch
  
  params = torch.tensor([1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1], requires_grad=True)
  params.grad = torch.tensor([1.0, 1, 1, 1, 1, 1, 1, 1, 1, 1])
  adam = torch.optim.AdamW([params], lr=0.8, betas=(0.5, 0.75), eps=0.6, weight_decay=0.2)
  
  # First step
  adam.step()
  print("Params after first step:", params)
  
  # Second step
  adam.step()
  print("Params after second step:", params)
  