class_docstr: Stores embeddings of a fixed dictionary and size.
docstr: :meta private:
docstr_tok: [":","meta","private",":"]
code: def extra_repr(self) -> str:
      """:meta private:"""
      s = f"num_embeddings={self.num_embeddings}, embedding_dim={self.embedding_dim}"
  
      if self.pad_idx is not None:
          s = f"{s}, pad_idx={self.pad_idx}"
  
      return s
  
imports: from __future__ import annotations
  from abc import ABC, abstractmethod
  from typing import Callable, Optional, final
  import torch
  import torch.nn
  from torch import Tensor
  from torch.nn import Module
  from torch.nn.functional import embedding
  from torch.nn.parameter import Parameter
  from fairseq2.typing import DataType, Device, finaloverride
label_desc: Use image node_id 3 for calling the Embedding obj's underlying member method code with example usage: obj.extra_repr() and returns: s