class_docstr: Wrapper around nn.Module that prints registered buffers and parameter names.
class_docstr_tok: ["Wrapper","around","nn.Module","that","prints","registered","buffers","and","parameter","names","."]
code: def extra_repr(self) -> str:
      named_modules = set()
      for p in self.named_modules():
          named_modules.update([p[0]])
      named_modules = list(named_modules)
  
      string_repr = ""
      for p in self.named_parameters():
          name = p[0].split(".")[0]
          if name not in named_modules:
              string_repr += self.get_readable_tensor_repr(name, p)
  
      for p in self.named_buffers():
          name = p[0].split(".")[0]
          string_repr += self.get_readable_tensor_repr(name, p)
  
      return string_repr
  
imports: import einops
  import numpy
  import torch
  import torch.nn
label_desc: Use image node_id 2 for calling the VerboseNNModule obj's underlying member method code with example usage: obj.extra_repr() and returns: string_repr