class_docstr: Classification of 295K Wikipedia talk page comments for types of toxicity.
  
  This version of the Wikipedia Toxicity Subtypes dataset provides access to the
  primary toxicity label annotated by crowd workers, with five additional
  toxicity subtype labels in the main config. The toxicity and toxicity subtype
  labels are binary values (0 or 1) indicating whether the majority of
  annotators assigned that attributes to the comment text.
  
  While the main config is entirely in English, the
  WikipediaToxicityMultilingual config provides validation and test splits with
  data in several non-English languages (tr, it, es, pt, ru, fr). This config
  provides access only to the primary toxicity label for each comment.
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docstr: Yields examples.
  
  Each example contains a text input and then six annotation labels.
  
  Args:
    filename: the path of the file to be read for this split.
  
  Yields:
    A dictionary of features, all floating point except the input text.
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code: def _generate_examples(self, filename):
      """Yields examples.
  
      Each example contains a text input and then six annotation labels.
  
      Args:
        filename: the path of the file to be read for this split.
  
      Yields:
        A dictionary of features, all floating point except the input text.
      """
      with epath.Path(filename).open() as f:
          reader = csv.DictReader(f)
          for row in reader:
              example = {}
              example["text"] = row["comment_text"]
              example["id"] = row["id"]
              example["language"] = row["lang"]
              example["toxicity"] = float(row["toxic"])
  
              if not self.builder_config.multilingual:
                  example["severe_toxicity"] = float(
                      row["severe_toxic"]
                  )
                  example["identity_attack"] = float(
                      row["identity_hate"]
                  )
                  for label in ["obscene", "threat", "insult"]:
                      example[label] = float(row[label])
  
              yield row["id"], example
  
file_path: datasets/tensorflow_datasets/text/wikipedia_toxicity_subtypes.py
imports: import csv
  import os
  from etils import epath
  from tensorflow_datasets.core.utils.lazy_imports_utils import tensorflow
  import tensorflow_datasets.public_api
label_desc: Use image node_id 3 for calling the WikipediaToxicitySubtypes obj's underlying member method code with example usage: obj._generate_examples(filename) without return types