Create dataset.py

dataset.py

@@ -0,0 +1,94 @@
+# -*- 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=1bGzmCXre__7mY7DhGFTWH2tJS4ZtTm5L&export=download",
+    "VALIDATION_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=15xUzB1fj2U7eWDZIjEUWkgVKjv14r43_&export=download",
+    "TEST_DOWNLOAD_URL": "https://drive.google.com/u/0/uc?id=18r8dCsLazDyliRoEDtbt3aOcPh8d_baJ&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