code: def forward(self, inputs):
      chunks = inputs.chunk(self.num_local_experts, dim=1)
      expert_outputs = []
      for chunk, expert in zip(chunks, self.deepspeed_experts):
          out = expert(chunk)
          if type(out) is tuple:
              out = out[0]  # Ignore the bias term for now
          expert_outputs += [out]
  
      expert_output = torch.cat(expert_outputs, dim=1)
      return expert_output
  
imports: import torch
  import copy
label_desc: Use image node_id 2 for calling the Experts obj's underlying member method code with example usage: obj.forward(inputs) and returns: expert_output