class_docstr: Implements the encoder in DETR transformer.
  
  Args:
      num_layers (int): The number of `TransformerEncoderLayer`.
      embed_dims (int): Same as `TransformerEncoderLayer`.
      num_heads (int): Same as `TransformerEncoderLayer`.
      feedforward_channels (int): Same as `TransformerEncoderLayer`.
      dropout (float): Same as `TransformerEncoderLayer`. Default 0.0.
      order (tuple[str]): Same as `TransformerEncoderLayer`.
      act_cfg (dict): Same as `TransformerEncoderLayer`. Defalut ReLU.
      norm_cfg (dict): Same as `TransformerEncoderLayer`. Default
          layer normalization.
      num_fcs (int): Same as `TransformerEncoderLayer`. Default 2.
class_docstr_tok: ["Implements","the","encoder","in","DETR","transformer",".","Args",":","num_layers","(","int",")",":","The","number","of","`","TransformerEncoderLayer","`",".","embed_dims","(","int",")",":","Same","as","`","TransformerEncoderLayer","`",".","num_heads","(","int",")",":","Same","as","`","TransformerEncoderLayer","`",".","feedforward_channels","(","int",")",":","Same","as","`","TransformerEncoderLayer","`",".","dropout","(","float",")",":","Same","as","`","TransformerEncoderLayer","`",".","Default","0.0.","order","(","tuple","[","str","]",")",":","Same","as","`","TransformerEncoderLayer","`",".","act_cfg","(","dict",")",":","Same","as","`","TransformerEncoderLayer","`",".","Defalut","ReLU",".","norm_cfg","(","dict",")",":","Same","as","`","TransformerEncoderLayer","`",".","Default","layer","normalization",".","num_fcs","(","int",")",":","Same","as","`","TransformerEncoderLayer","`",".","Default","2","."]
docstr: str: a string that describes the module
docstr_tok: ["str",":","a","string","that","describes","the","module"]
code: def __repr__(self):
      """str: a string that describes the module"""
      repr_str = self.__class__.__name__
      repr_str += f"(num_layers={self.num_layers}, "
      repr_str += f"embed_dims={self.embed_dims}, "
      repr_str += f"num_heads={self.num_heads}, "
      repr_str += f"feedforward_channels={self.feedforward_channels}, "
      repr_str += f"dropout={self.dropout}, "
      repr_str += f"order={self.order}, "
      repr_str += f"act_cfg={self.act_cfg}, "
      repr_str += f"norm_cfg={self.norm_cfg}, "
      repr_str += f"num_fcs={self.num_fcs})"
      return repr_str
  
imports: import torch
  import torch.nn
  from mmcv.cnn import Linear, build_activation_layer, build_norm_layer, xavier_init
  from .builder import TRANSFORMER
label_desc: Use image node_id 3 for calling the TransformerEncoder obj's underlying member method code with example usage: obj.__repr__() and returns: repr_str