class_docstr: A model that accepts strings and returns a single representation (embedding) for each one of them.
code: def __init__(
      self,
      *,
      token_splitting: Literal["token", "subtoken", "bpe", "char"],
      embedding_size: int = 128,
      dropout_rate: float = 0.2,
      # Vocabulary Options
      vocabulary_size: int = 10000,
      min_freq_threshold: int = 5,
      # BPE/Subtoken Options
      max_num_subtokens: Optional[int] = 5,
      subtoken_combination: Literal["sum", "mean", "max"] = "sum",
      # Char Models
      cnn_config: CnnConfig = CnnConfig(
          l1_filters=256,
          l1_window_size=3,
          l2_filters=128,
          l2_window_size=3,
          lout_window_size=3,
      ),
      max_num_chars: int = 15,
  ):
      super().__init__()
      self._splitting_kind: Final = token_splitting
      self.embedding_size: Final = embedding_size
      self.dropout_rate: Final = dropout_rate
      self.__vocabulary: Union[
          Vocabulary, BpeVocabulary, CharTensorizer
      ]
      if token_splitting in {"bpe", "subtoken"}:
          self.max_num_subtokens: Final = max_num_subtokens
          self.subtoken_combination: Final = subtoken_combination
      elif token_splitting == "char":
          self.cnn_config: Final = cnn_config
          self.max_num_chars: Final = max_num_chars
      if token_splitting != "char":
          self.max_vocabulary_size: Final = vocabulary_size
          self.min_freq_threshold: Final = min_freq_threshold
  
imports: from typing_extensions import Final, Literal
  import logging
  import math
  import numpy
  import torch
  import torch.nn
  from dpu_utils.codeutils import split_identifier_into_parts
  from dpu_utils.mlutils import BpeVocabulary, CharTensorizer, Vocabulary
  from typing import Any, Counter, Dict, List, NamedTuple, Optional, Union
  from ptgnn.baseneuralmodel import AbstractNeuralModel
  from ptgnn.neuralmodels.gnn.structs import AbstractNodeEmbedder
label_desc: Use image node_id 1 to create a new StrElementRepresentationModel object from inherited base classes: AbstractNeuralModel, AbstractNodeEmbedder with example: obj = StrElementRepresentationModel()