Delete swahili_test_samples.py

swahili_test_samples.py

@@ -1,66 +0,0 @@
-import os
-import csv
-import datasets
-
-_CITATION = """\
-Add any citation or reference here.
-"""
-
-_DESCRIPTION = """\
-Swahili test samples dataset with audio, predicted text, and reference text.
-"""
-
-
-class SwahiliTestSamplesConfig(datasets.BuilderConfig):
-    """BuilderConfig for SwahiliTestSamples."""
-
-
-class SwahiliTestSamples(datasets.GeneratorBasedBuilder):
-    BUILDER_CONFIGS = [
-        SwahiliTestSamplesConfig(
-            name="default",
-            version=datasets.Version("1.0.0"),
-            description="Swahili test samples default config",
-        ),
-    ]
-
-    def _info(self):
-        return datasets.DatasetInfo(
-            description=_DESCRIPTION,
-            features=datasets.Features(
-                {
-                    "audio": datasets.Audio(sampling_rate=None),
-                    "predicted_text": datasets.Value("string"),
-                    "reference_text": datasets.Value("string"),
-                    "expert_comment": datasets.Value("string"),
-                }
-            ),
-            citation=_CITATION,
-        )
-
-    def _split_generators(self, dl_manager):
-        """Download or retrieve data; in this case, we assume it's local."""
-        # "data_dir" is the local path of the dataset repo. Inside it, we expect
-        # `metadata.csv` and the `audios/` folder.
-        csv_path = os.path.join(self.config.data_dir, "metadata.csv")
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "csv_path": csv_path,
-                },
-            ),
-        ]
-
-    def _generate_examples(self, csv_path):
-        """Yields examples from metadata.csv."""
-        with open(csv_path, mode="r", encoding="utf-8") as f:
-            reader = csv.DictReader(f)
-            for i, row in enumerate(reader):
-                yield i, {
-                    # The "audio" column is what `datasets.Audio` will use.
-                    "audio": row["path"],  # e.g. 'audios/SWH-15-20101115_16k-…wav'
-                    "predicted_text": row["Predicted Text"],
-                    "reference_text": row["Reference Text"],
-                    "expert_comment": row.get("Expert's Comment", ""),
-                }