code: def value_loss(
      new_values: Tensor,
      old_values: Tensor,
      returns: Tensor,
      clip_coef: float,
      clip_vloss: bool,
      vf_coef: float,
  ) -> Tensor:
      new_values = new_values.view(-1)
      if not clip_vloss:
          values_pred = new_values
      else:
          values_pred = old_values + torch.clamp(
              new_values - old_values, -clip_coef, clip_coef
          )
      return vf_coef * F.mse_loss(values_pred, returns)
  
imports: import torch
  import torch.nn.functional
  from torch import Tensor
label_desc: Use image node_id 2 for calling a global function with example usage: value_loss(new_values, old_values, returns, clip_coef, clip_vloss, vf_coef) and returns: unknown