class_docstr: This is a `TextFieldEmbedder` that wraps a collection of
  [`TokenEmbedder`](../token_embedders/token_embedder.md) objects.  Each
  `TokenEmbedder` embeds or encodes the representation output from one
  [`allennlp.data.TokenIndexer`](../../data/token_indexers/token_indexer.md). As the data produced by a
  [`allennlp.data.fields.TextField`](../../data/fields/text_field.md) is a dictionary mapping names to these
  representations, we take `TokenEmbedders` with corresponding names.  Each `TokenEmbedders`
  embeds its input, and the result is concatenated in an arbitrary (but consistent) order.
  
  Registered as a `TextFieldEmbedder` with name "basic", which is also the default.
  
  # Parameters
  
  token_embedders : `Dict[str, TokenEmbedder]`, required.
      A dictionary mapping token embedder names to implementations.
      These names should match the corresponding indexer used to generate
      the tensor passed to the TokenEmbedder.
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code: def __init__(self, token_embedders: Dict[str, TokenEmbedder]) -> None:
      super().__init__()
      # NOTE(mattg): I'd prefer to just use ModuleDict(token_embedders) here, but that changes
      # weight locations in torch state dictionaries and invalidates all prior models, just for a
      # cosmetic change in the code.
      self._token_embedders = token_embedders
      for key, embedder in token_embedders.items():
          name = "token_embedder_%s" % key
          self.add_module(name, embedder)
      self._ordered_embedder_keys = sorted(self._token_embedders.keys())
  
file_path: allennlp/allennlp/modules/text_field_embedders/basic_text_field_embedder.py
imports: from typing import Dict
  import inspect
  import torch
  from allennlp.common.checks import ConfigurationError
  from allennlp.data.fields.text_field import TextFieldTensors
  from allennlp.modules.text_field_embedders.text_field_embedder import TextFieldEmbedder
  from allennlp.modules.time_distributed import TimeDistributed
  from allennlp.modules.token_embedders.token_embedder import TokenEmbedder
  from allennlp.modules.token_embedders import EmptyEmbedder
label_desc: Use image node_id 1 to create a new BasicTextFieldEmbedder object from inherited base classes: TextFieldEmbedder with example: obj = BasicTextFieldEmbedder(token_embedders)