class_docstr: BuilderConfig for C4-WSRS dataset.
class_docstr_tok: ["BuilderConfig","for","C4-WSRS","dataset","."]
docstr: Initializes the BuilderConfig for C4-WSRS.
  
  Args:
    name: The name for the config.
    max_sentences_per_snippet: The maximum number of sentences that can be
      combined into a single snippet. The number of sentences combined into
      each snippet will be a randomly sampled integer from 1 to
      max_sentences_per_snippet.
    max_snippet_char_len: The maximum number of characters an original snippet
      can be composed of.
    alpha_keep_no_rs: Alpha value used to compute the probability of keeping a
      snippet containing no reverse substitutions. The complete formula is p =
      (n+1)**-alpha where n is the count of previously kept snippets from the
      same document.
    alpha_keep_rs: Alpha value used to compute the probability of keeping a
      snippet containing a particular abbreviation-expansion reverse
      substitution candidate. The complete formula is p = (n+1)**-alpha where
      n is the count of previously kept snippets from the same document
      containing the same reverse substitution candidate.
    subsitution_rate: The rate at which expansions should be substituted for
      abbreviations.
    min_snippet_token_len: The minimum number of tokens an abbreviated snippet
      can be composed of.
    num_snippets_per_substitution: The number of snippets to sample for each
      unique abbreviation-expansion substitution.
    **kwargs: keyword arguments forwarded to super.
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code: def __init__(
      self,
      name: str,
      max_sentences_per_snippet: int,
      max_snippet_char_len: int,
      alpha_keep_no_rs: float,
      alpha_keep_rs: float,
      subsitution_rate: float,
      min_snippet_token_len: int,
      num_snippets_per_substitution: int,
      **kwargs,
  ):
      """Initializes the BuilderConfig for C4-WSRS.
  
      Args:
        name: The name for the config.
        max_sentences_per_snippet: The maximum number of sentences that can be
          combined into a single snippet. The number of sentences combined into
          each snippet will be a randomly sampled integer from 1 to
          max_sentences_per_snippet.
        max_snippet_char_len: The maximum number of characters an original snippet
          can be composed of.
        alpha_keep_no_rs: Alpha value used to compute the probability of keeping a
          snippet containing no reverse substitutions. The complete formula is p =
          (n+1)**-alpha where n is the count of previously kept snippets from the
          same document.
        alpha_keep_rs: Alpha value used to compute the probability of keeping a
          snippet containing a particular abbreviation-expansion reverse
          substitution candidate. The complete formula is p = (n+1)**-alpha where
          n is the count of previously kept snippets from the same document
          containing the same reverse substitution candidate.
        subsitution_rate: The rate at which expansions should be substituted for
          abbreviations.
        min_snippet_token_len: The minimum number of tokens an abbreviated snippet
          can be composed of.
        num_snippets_per_substitution: The number of snippets to sample for each
          unique abbreviation-expansion substitution.
        **kwargs: keyword arguments forwarded to super.
      """
      super().__init__(name=name, **kwargs)
      self.max_sentences_per_snippet = max_sentences_per_snippet
      self.max_snippet_char_len = max_snippet_char_len
      self.alpha_keep_no_rs = alpha_keep_no_rs
      self.alpha_keep_rs = alpha_keep_rs
      self.subsitution_rate = subsitution_rate
      self.min_snippet_token_len = min_snippet_token_len
      self.num_snippets_per_substitution = num_snippets_per_substitution
  
file_path: datasets/tensorflow_datasets/text/c4_wsrs/c4_wsrs.py
imports: from __future__ import annotations
  import collections
  import csv
  from typing import Mapping, Sequence
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
  from tensorflow_datasets.text.c4_wsrs import c4_wsrs_utils
label_desc: Use image node_id 1 to create a new C4WSRSConfig object from inherited base classes: tfds.core with example: obj = C4WSRSConfig(name, max_sentences_per_snippet, max_snippet_char_len, alpha_keep_no_rs, alpha_keep_rs, subsitution_rate, min_snippet_token_len, num_snippets_per_substitution)