Create dataset.py
Browse files- dataset.py +94 -0
dataset.py
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# -*- coding: utf-8 -*-
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"""dataset.ipynb
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Automatically generated by Colaboratory.
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Original file is located at
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https://colab.research.google.com/drive/1sNXmgV-J4w6JSdtXK-0TckTP5SFkGPtz
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###Create a file.py
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"""
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import datasets
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import csv
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import pandas as pd
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_URLS = {
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"zh-en": {
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"TRAIN_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=1bGzmCXre__7mY7DhGFTWH2tJS4ZtTm5L&export=download",
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"VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=15xUzB1fj2U7eWDZIjEUWkgVKjv14r43_&export=download",
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"TEST_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=18r8dCsLazDyliRoEDtbt3aOcPh8d_baJ&export=download"
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}
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}
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class NewDataset(datasets.GeneratorBasedBuilder):
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VERSION = datasets.Version("1.0.0")
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BUILDER_CONFIGS = [
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datasets.BuilderConfig(
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name = "zh-en",
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version = VERSION,
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description = "The translation dataset between Traditional Chinese and English"
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)
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]
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def _info(self):
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if self.config.name == "zh-en": # This is the name of the configuration selected in BUILDER_CONFIGS above
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features = datasets.Features(
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{ "translation": datasets.features.Translation( languages=["en", "zh"] ) }
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)
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return datasets.DatasetInfo(
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# This is the description that will appear on the datasets page.
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# description=_DESCRIPTION,
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# This defines the different columns of the dataset and their types
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features=features, # Here we define them above because they are different between the two configurations
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# If there's a common (input, target) tuple from the features,
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# specify them here. They'll be used if as_supervised=True in
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# builder.as_dataset.
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supervised_keys=None,
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# Homepage of the dataset for documentation
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# homepage=_HOMEPAGE,
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# License for the dataset if available
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# license=_LICENSE,
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# Citation for the dataset
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# citation=_CITATION,
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)
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def _split_generators(self, dl_manager):
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""" Returns SplitGenerators"""
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my_urls = _URLS[self.config.name]
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train_path = dl_manager.download_and_extract(my_urls["TRAIN_DOWNLOAD_URL"])
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validation_path = dl_manager.download_and_extract(my_urls["VALIDATION_DOWNLOAD_URL"])
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test_path = dl_manager.download_and_extract(my_urls["TEST_DOWNLOAD_URL"])
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return [
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datasets.SplitGenerator(
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name=datasets.Split.TRAIN,
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gen_kwargs = { "filepath" : train_path, "split" : "train" }
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),
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datasets.SplitGenerator(
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name=datasets.Split.VALIDATION,
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gen_kwargs = { "filepath" : validation_path, "split" : "validation" }
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),
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datasets.SplitGenerator(
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name=datasets.Split.TEST,
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gen_kwargs = { "filepath" : test_path, "split" : "test"},
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)
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]
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def _generate_examples(self, filepath, split):
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""" Generate Dravidian MT examples"""
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with open(filepath, encoding="utf-8") as f:
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reader = csv.DictReader(f)
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for idx, row in enumerate(reader):
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if self.config.name == "zh-en":
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result = { "translation" : { "en" : row["en"], "zh" : row["zh"] } }
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yield idx, result
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