Snap

vps_clustering_benchmark.py

@@ -81,44 +81,20 @@ class VPClusteringBenchmark(datasets.GeneratorBasedBuilder):
                 gen_kwargs={"file_path": downloaded_file, "split": "files"},
             ),
         ]
-
-    def _generate_examples(self, file_path, split):
+    def _generate_examples(self, file_path):
         """Yields examples."""
         df = pd.read_pickle(file_path)
 
-        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
+        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)
+            }