class_docstr: Wrapper for character aware CNN embeddings for tokens.
  Attributes:
      embedding (CNNCharacterEmbedding): Character embedding
class_docstr_tok: ["Wrapper","for","character","aware","CNN","embeddings","for","tokens",".","Attributes",":","embedding","(","CNNCharacterEmbedding",")",":","Character","embedding"]
docstr: Returns the embedding weights of size (num_embeddings, embed_dim).
docstr_tok: ["Returns","the","embedding","weights","of","size","(","num_embeddings",",","embed_dim",")","."]
code: def get_embedding_weights(self):
      """
      Returns the embedding weights of size (num_embeddings, embed_dim).
      """
  
      return self.embedding.char_embed.weight
  
file_path: pytext/pytext/models/embeddings/char_embedding.py
imports: import warnings
  from typing import List, Optional
  import torch
  import torch.nn
  import torch.nn.functional
  from pytext.config.field_config import CharFeatConfig
  from pytext.fields import FieldMeta
  from pytext.utils.usage import log_class_usage
  from pytorch.text.fb.nn.modules.cnn_char_embedding import CNNCharacterEmbedding
  from .embedding_base import EmbeddingBase
label_desc: Use image node_id 5 for calling the CharacterEmbedding obj's underlying member method code with example usage: obj.get_embedding_weights() and returns: self