dataset.py

# -*- coding: utf-8 -*-
"""dataset.ipynb

Automatically generated by Colaboratory.

Original file is located at
    https://colab.research.google.com/drive/1sNXmgV-J4w6JSdtXK-0TckTP5SFkGPtz

###Create a file.py
"""

import datasets
import csv
import pandas as pd

_URLS = {
  "zh-en": {
    "TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1z-reeSB_pAcZEJicRpBJWzrhuwdtJ-d1&export=download",
    "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1f1izEby8pfXZWG7htvcky_FL2iTMnoD5&export=download",
    "TEST_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1VGM96MZvMuAPJoFzBeSpyC16IDSiu0vC&export=download"
  }
}

class NewDataset(datasets.GeneratorBasedBuilder):

  VERSION = datasets.Version("1.0.0")

  BUILDER_CONFIGS = [
    datasets.BuilderConfig(
      name = "zh-en",
      version = VERSION,
      description = "The translation dataset between Traditional Chinese and English"
    )
  ]

  def _info(self):

    if self.config.name == "zh-en":  # This is the name of the configuration selected in BUILDER_CONFIGS above
      features = datasets.Features(
        { "translation": datasets.features.Translation( languages=["en", "zh"] ) }
      )

    return datasets.DatasetInfo(
            # This is the description that will appear on the datasets page.
#      description=_DESCRIPTION,
            # This defines the different columns of the dataset and their types
      features=features,  # Here we define them above because they are different between the two configurations
            # If there's a common (input, target) tuple from the features,
            # specify them here. They'll be used if as_supervised=True in
            # builder.as_dataset.
      supervised_keys=None,
            # Homepage of the dataset for documentation
#      homepage=_HOMEPAGE,
            # License for the dataset if available
#      license=_LICENSE,
            # Citation for the dataset
#      citation=_CITATION,
    )

  def _split_generators(self, dl_manager):
    """ Returns SplitGenerators"""

    my_urls = _URLS[self.config.name]

    train_path = dl_manager.download_and_extract(my_urls["TRAIN_DOWNLOAD_URL"])
    validation_path = dl_manager.download_and_extract(my_urls["VALIDATION_DOWNLOAD_URL"])
    test_path = dl_manager.download_and_extract(my_urls["TEST_DOWNLOAD_URL"])

    return [
      datasets.SplitGenerator(
        name=datasets.Split.TRAIN,
        gen_kwargs = { "filepath" : train_path, "split" : "train" }
      ),
      datasets.SplitGenerator(
        name=datasets.Split.VALIDATION,
        gen_kwargs = { "filepath" : validation_path, "split" : "validation" }
      ),
      datasets.SplitGenerator(
        name=datasets.Split.TEST,
        gen_kwargs = {  "filepath" : test_path, "split" : "test"},
      )
    ]

  def _generate_examples(self, filepath, split):
    """ Generate Dravidian MT examples"""

    with open(filepath, encoding="utf-8") as f:
      reader = csv.DictReader(f)
      for idx, row in enumerate(reader):

        if self.config.name == "zh-en":
          result = { "translation" : { "en" : row["en"], "zh" : row["zh"] } }

        yield idx, result