text: import paddle
  import numpy as np
  
  inp = np.random.uniform(-0.1, 0.1, [10, 10]).astype("float32")
  linear = paddle.nn.Linear(10, 10)
  inp = paddle.to_tensor(inp)
  out = linear(inp)
  loss = paddle.mean(out)
  adam = paddle.optimizer.Adam(learning_rate=0.1,
          parameters=linear.parameters())
  out.backward()
  adam.step()
  adam.clear_grad()
  