class_docstr: ## Embedding layer
  
  This is a standard embeddings layer with code to load the checkpoint.
class_docstr_tok: ["#","#","Embedding","layer","This","is","a","standard","embeddings","layer","with","code","to","load","the","checkpoint","."]
docstr: :param n_vocab: is the size of the vocabulary
  :param n_hidden: is the size of the embeddings
code: def __init__(self, n_vocab: int = 50_432, n_hidden: int = 6_144):
      """
      :param n_vocab: is the size of the vocabulary
      :param n_hidden: is the size of the embeddings
      """
      super().__init__()
  
      self.emb = nn.Embedding(n_vocab, n_hidden)
  
imports: import copy
  import math
  from typing import Dict, Optional, Set, Callable, Any, Generator, Tuple
  import torch
  from torch import nn
  from torch.cuda.amp import autocast
  from labml import monit, logger
  from labml.logger import Text
  from labml_nn.neox import checkpoint
  from labml_nn.neox.utils.cache import get_cache
label_desc: Use image node_id 1 to create a new Embedding object from inherited base classes: NeoXModule with example: obj = Embedding(n_vocab, n_hidden)