class_docstr: Transformer Encoder without hierarchical structure
      
class_docstr_tok: ["Transformer","Encoder","without","hierarchical","structure"]
code: def forward(self, x, pos):
      for _, block in enumerate(self.blocks):
          x = block(x + pos)
      return x
  
imports: import torch
  import torch.nn
  import torch.nn.functional
  from timm.models.layers import DropPath
  from lavis.models.ulip_models.pointbert.dvae import Group
  from lavis.models.ulip_models.pointbert.dvae import Encoder
  from lavis.models.ulip_models.pointbert.logger import print_log
  from lavis.models.ulip_models.pointbert.checkpoint import get_missing_parameters_message, get_unexpected_parameters_message
label_desc: Use image node_id 2 for calling the TransformerEncoder obj's underlying member method code with example usage: obj.forward(x, pos) and returns: x