code: def __init__(
      self,
      in_features,
      hidden_features=None,
      out_features=None,
      act_layer=nn.GELU,
      drop=0.0,
  ):
      super(Mlp, self).__init__()
      out_features = out_features or in_features
      hidden_features = hidden_features or in_features
      self.fc1 = nn.Linear(in_features, hidden_features)
      self.act = act_layer()
      self.fc2 = nn.Linear(hidden_features, out_features)
      self.drop = nn.Dropout(drop)
  
imports: import os
  import logging
  import torch
  import torch.nn
  import torch.nn.functional
  from functools import partial
  import torch.distributed
  from torch.nn.init import trunc_normal_
  from megatron.model.transformer import DropPath
  from megatron import get_args
  from megatron.model import LayerNorm
  import numpy
  from math import sqrt
label_desc: Use image node_id 1 to create a new Mlp object from inherited base classes: nn with example: obj = Mlp(in_features, hidden_features, out_features, act_layer, drop)