class_docstr: WMT '14 machine-translation data, via TFDS.
class_docstr_tok: ["WMT","'14","machine-translation","data",",","via","TFDS","."]
docstr: Loads the dataset from a CSV file.
  
  Args:
    path: The location of the CSV file.
    source_key: ISO 639-1 code for the source language.
    target_key: ISO 639-1 code for the target language.
    skiplines: The number of lines to skip in the input file(s).
  
  Returns:
    The list of exmaples loaded from the file.
  
  Raises:
    ValueError: invalid key passed for the source or target language.
docstr_tok: ["Loads","the","dataset","from","a","CSV","file",".","Args",":","path",":","The","location","of","the","CSV","file",".","source_key",":","ISO","639-1","code","for","the","source","language",".","target_key",":","ISO","639-1","code","for","the","target","language",".","skiplines",":","The","number","of","lines","to","skip","in","the","input","file","(","s",")",".","Returns",":","The","list","of","exmaples","loaded","from","the","file",".","Raises",":","ValueError",":","invalid","key","passed","for","the","source","or","target","language","."]
code: def _load_datapoints(
      self,
      path: str,
      source_key: str,
      target_key: str,
      skiplines: int = 0,
  ) -> list[JsonDict]:
      """Loads the dataset from a CSV file.
  
      Args:
        path: The location of the CSV file.
        source_key: ISO 639-1 code for the source language.
        target_key: ISO 639-1 code for the target language.
        skiplines: The number of lines to skip in the input file(s).
  
      Returns:
        The list of exmaples loaded from the file.
  
      Raises:
        ValueError: invalid key passed for the source or target language.
      """
      if source_key not in _VALID_WMT14_LANG_CODES:
          raise ValueError(
              f"Invalid source_key, {source_key}. Expected one of "
              f"{str(_VALID_WMT14_LANG_CODES)}."
          )
  
      if target_key not in _VALID_WMT14_LANG_CODES:
          raise ValueError(
              f"Invalid target_key, {target_key}. Expected one of "
              f"{str(_VALID_WMT14_LANG_CODES)}."
          )
  
      path = file_cache.cached_path(path)
      with open(path) as fd:
          df = pd.read_csv(fd, skiprows=skiplines)
      return [
          self._record_to_dict(row, source_key, target_key)
          for _, row in df.iterrows()
      ]
  
file_path: lit/lit_nlp/examples/datasets/mt.py
imports: from collections.abc import Mapping
  from typing import Any, Optional
  from lit_nlp.api import dataset
  from lit_nlp.api import types
  from lit_nlp.lib import file_cache
  import pandas
  import six
  import tensorflow_datasets
label_desc: Use image node_id 3 for calling the WMT14Data obj's underlying member method code with example usage: obj._load_datapoints(path, source_key, target_key, skiplines) and returns: unknown