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: See CNNCharacterEmbedding.forward() for details
docstr_tok: ["See","CNNCharacterEmbedding.forward","(",")","for","details"]
code: def forward(
      self,
      chars: torch.Tensor,
      precomputed_embeddings: Optional[torch.Tensor] = None,
  ) -> torch.Tensor:
      """See CNNCharacterEmbedding.forward() for details"""
      return self.embedding(
          chars, precomputed_embeddings=precomputed_embeddings
      )
  
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 3 for calling the CharacterEmbedding obj's underlying member method code with example usage: obj.forward(chars, precomputed_embeddings) and returns: self