code: def forward(
      self,
      x: torch.Tensor,
      s: torch.Tensor,
      g_action: torch.Tensor = None,
      g_value: torch.Tensor = None,
  ):
      if g_action is None:
          return self._eval_forward(x, s)
      else:
          assert g_value is not None
          return self._train_forward(x, s, g_action, g_value)
  
file_path: nebuly/optimization/open_alpha_tensor/open_alpha_tensor/core/modules/alpha_tensor.py
imports: import torch
  from open_alpha_tensor.core.modules.extras import QuantileLoss, ValueRiskManagement
  from open_alpha_tensor.core.modules.heads import PolicyHead, ValueHead
  from open_alpha_tensor.core.modules.torso import TorsoModel
label_desc: Use image node_id 5 for calling the AlphaTensorModel obj's underlying member method code with example usage: obj.forward(x, s, g_action, g_value) and returns: self, self