class_docstr: CMlp
class_docstr_tok: ["CMlp"]
code: def __init__(
      self,
      in_features,
      hidden_features=None,
      out_features=None,
      act_layer=nn.GELU,
      drop=0.0,
  ):
      super().__init__()
      out_features = out_features or in_features
      hidden_features = hidden_features or in_features
      self.fc1 = conv_1x1x1(in_features, hidden_features)
      self.act = act_layer()
      self.fc2 = conv_1x1x1(hidden_features, out_features)
      self.drop = nn.Dropout(drop)
  
imports: from collections import OrderedDict
  import torch
  from torch import nn
  from torch.utils import checkpoint
  from functools import partial
  from towhee.models.utils.general_utils import to_2tuple
  from towhee.models.utils.weight_init import trunc_normal_
  from towhee.models.layers.droppath import DropPath
  from towhee.models.layers.mlp import Mlp
  from towhee.models.layers.attention import MultiHeadAttention
  from towhee.models.uniformer.config import _C
  import os
label_desc: Use image node_id 1 to create a new CMlp object from inherited base classes: nn with example: obj = CMlp(in_features, hidden_features, out_features, act_layer, drop)