Snap

vps_clustering_benchmark.py

@@ -73,25 +73,52 @@ class VPClusteringBenchmark(datasets.GeneratorBasedBuilder):
         downloaded_file = dl_manager.download_and_extract(data_url)
         return [
             datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={"file_path": downloaded_file},
+                name="segments",
+                gen_kwargs={"file_path": downloaded_file, "split": "segments"},
+            ),
+            datasets.SplitGenerator(
+                name="files",
+                gen_kwargs={"file_path": downloaded_file, "split": "files"},
             ),
         ]
 
-    def _generate_examples(self, file_path):
+    def _generate_examples(self, file_path, split):
         """Yields examples."""
         df = pd.read_pickle(file_path)
 
-        for idx, row in df.iterrows():
-            yield idx, {
-                "segment_id": row["segment_id"],
-                "filename": row["filename"],
-                "speaker": row["speaker"],
-                "duration": row["duration"],
-                "segment_clean": row["segment_clean"],
-                "start": row['start'],
-                "end": row['end'],
-                "readable_start": row['readable_start'],
-                "readable_end": row['readable_end'],
-                "vp": np.asarray(row["vp"], dtype=np.float32)
-            }
+        if split == "segments":
+            for idx, row in df.iterrows():
+                yield idx, {
+                    "segment_id": row["segment_id"],
+                    "filename": row["filename"],
+                    "speaker": row["speaker"],
+                    "duration": row["duration"],
+                    "segment_clean": row["segment_clean"],
+                    "start": row['start'],
+                    "end": row['end'],
+                    "readable_start": row['readable_start'],
+                    "readable_end": row['readable_end'],
+                    "vp": np.asarray(row["vp"], dtype=np.float32)
+                }
+        elif split == "files":
+            files = {}
+            for idx, row in df.iterrows():
+                if row["filename"] not in files:
+                    files[row["filename"]] = {
+                        "filename": row["filename"],
+                        "segments": []
+                    }
+                files[row["filename"]]["segments"].append({
+                    "segment_id": row["segment_id"],
+                    "speaker": row["speaker"],
+                    "duration": row["duration"],
+                    "segment_clean": row["segment_clean"],
+                    "start": row['start'],
+                    "end": row['end'],
+                    "readable_start": row['readable_start'],
+                    "readable_end": row['readable_end'],
+                    "vp": np.asarray(row["vp"], dtype=np.float32)
+                })
+            
+            for idx, file_data in enumerate(files.values()):
+                yield idx, file_data