Create test-cefr.py

test-cefr.py

@@ -0,0 +1,89 @@
+import csv
+import json
+import os
+
+import datasets
+
+_CITATION = """\
+@InProceedings{huggingface:dataset,
+title = {A great new dataset},
+author={huggingface, Inc.
+},
+year={2020}
+}
+"""
+
+# You can copy an official description
+_DESCRIPTION = """\
+This new dataset is designed to solve this great NLP task and is crafted with a lot of care.
+"""
+_HOMEPAGE = ""
+_LICENSE = ""
+
+
+_URLS = {
+      "train": "train_split.csv",
+      "test":  "test_split.csv",
+      "val": "val_split.csv",
+  }
+
+
+class CefrDataset(datasets.GeneratorBasedBuilder):
+
+    VERSION = datasets.Version("1.1.0")
+
+    def _info(self):
+          features = datasets.Features(
+              {
+                  "prompt": datasets.Value("string"),
+                  "label": datasets.Value("string")
+              }
+          )
+
+        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."""
+
+
+        return [
+            datasets.SplitGenerator(
+                name=datasets.Split.TRAIN,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": "train_split.csv",
+                    "split": "train",
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.TEST,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": "test_split.csv",
+                    "split": "test"
+                },
+            ),
+            datasets.SplitGenerator(
+                name=datasets.Split.VALIDATION,
+                # These kwargs will be passed to _generate_examples
+                gen_kwargs={
+                    "filepath": "val_split.csv",
+                    "split": "val",
+                },
+            ),
+        ]