fix: new approach

asr_dataset.py

@@ -22,6 +22,35 @@ _CITATION = """
 Use this repo info/link for citation.
 """
 
+_LICENSE = "MIT"
+
+_DATA_URL = [
+    "clips/clips_001.tar",
+    "clips/clips_002.tar",
+    "clips/clips_003.tar",
+    "clips/clips_004.tar",
+    "clips/clips_005.tar",
+    "clips/clips_006.tar",
+    "clips/clips_007.tar",
+    "clips/clips_008.tar",
+    "clips/clips_009.tar",
+    "clips/clips_010.tar",
+    "clips/clips_011.tar",
+    "clips/clips_012.tar",
+    "clips/clips_013.tar",
+    "clips/clips_014.tar",
+    "clips/clips_015.tar",
+    "clips/clips_016.tar",
+    "clips/clips_017.tar",
+    "clips/clips_018.tar",
+    "clips/clips_019.tar",
+    "clips/clips_020.tar",
+    "clips/clips_021.tar",
+]
+
+_PROMPTS_URLS = {
+    "train": "clips/metadata.csv"
+}
 
 class ASRDataset(datasets.GeneratorBasedBuilder):
     """ASR dataset with audio files stored in tar archives."""
@@ -35,7 +64,7 @@ class ASRDataset(datasets.GeneratorBasedBuilder):
                 "file_name": datasets.Value("string"),
                 "audio": datasets.Audio(sampling_rate=16000),
                 "sentence": datasets.Value("string"),
-                "tar_file": datasets.Value("string"),
+                #"tar_file": datasets.Value("string"),
             }),
             supervised_keys=None,
             citation=_CITATION,
@@ -43,13 +72,21 @@ class ASRDataset(datasets.GeneratorBasedBuilder):
 
     def _split_generators(self, dl_manager):
         """Returns SplitGenerators with added error handling."""
+
+        prompts_paths = dl_manager.download_and_extract(_PROMPTS_URLS)
+        archive = dl_manager.download(_DATA_URL)
+        train_dir = "clips"
+
         try:
             return [
                 datasets.SplitGenerator(
                     name=datasets.Split.TRAIN,
                     gen_kwargs={
-                        "split": "train",
-                        "data_dir": self.config.data_dir,
+                        #"split": "train",
+                        #"data_dir": self.config.data_dir,
+                        "prompts_path": prompts_paths["train"],
+                        "path_to_clips": train_dir,
+                        "audio_files": dl_manager.iter_archive(archive)
                     },
                 ),
             ]
@@ -58,102 +95,27 @@ class ASRDataset(datasets.GeneratorBasedBuilder):
             logger.error(traceback.format_exc())
             raise
 
-    def _prepare_metadata(self, data_dir: str) -> pd.DataFrame:
-        """Prepare metadata with comprehensive error handling."""
-        try:
-            logger.info("Preparing metadata with tar file information...")
-            
-            # Read metadata
-            metadata_path = os.path.join(data_dir, "metadata.csv")
-            
-            # Add error handling for metadata reading
-            try:
-                df = pd.read_csv(metadata_path, sep='\t', names=['file_name', 'sentence'], encoding="utf-8")
-            except Exception as read_error:
-                logger.error(f"Failed to read metadata file: {read_error}")
-                raise
-            
-            # Validate dataframe
-            if df.empty:
-                raise ValueError("Metadata file is empty")
-            
-            # Add tar_file column
-            clips_dir = os.path.join(data_dir, "clips")
-            tar_files = [f for f in os.listdir(clips_dir) if f.endswith('.tar')]
-            
-            # Initialize tar_file column
-            df['tar_file'] = None
-            
-            # Find which tar file contains each audio file
-            for tar_file in tar_files:
-                tar_path = os.path.join(clips_dir, tar_file)
-                try:
-                    with tarfile.open(tar_path, 'r') as tar:
-                        file_list = tar.getnames()
-                        mask = df['file_name'].isin(file_list)
-                        df.loc[mask, 'tar_file'] = tar_file
-                except Exception as tar_error:
-                    logger.warning(f"Error processing tar file {tar_file}: {tar_error}")
-            
-            # Remove entries where tar_file is None (file not found in any tar)
-            df = df.dropna(subset=['tar_file'])
-            
-            # Additional logging
-            logger.info(f"Total entries after tar file mapping: {len(df)}")
-            
-            return df
-        
-        except Exception as e:
-            logger.error(f"Unexpected error in _prepare_metadata: {e}")
-            logger.error(traceback.format_exc())
-            raise
-
-    def _generate_examples(self, split, data_dir):
-        """Yields examples with comprehensive error handling."""
-        try:
-            # Prepare metadata with tar file information
-            df = self._prepare_metadata(data_dir)
-            clips_dir = os.path.join(data_dir, "clips")
-            
-            idx = 0
-            # Group by tar_file for efficient processing
-            for tar_file, group in df.groupby('tar_file'):
-                tar_path = os.path.join(clips_dir, tar_file)
-                logger.info(f"Processing tar file: {tar_file}")
-                
-                try:
-                    with tarfile.open(tar_path, 'r') as tar:
-                        for _, row in group.iterrows():
-                            try:
-                                # More robust file extraction
-                                member = tar.getmember(row['file_name'])
-                                f = tar.extractfile(member)
-                                if f is None:
-                                    logger.warning(f"Could not extract file: {row['file_name']}")
-                                    continue
-                                    
-                                audio_bytes = f.read()
-                                f.close()
-                                
-                                yield idx, {
-                                    "file_name": row['file_name'],
-                                    "audio": {"path": f"{tar_path}::{row['file_name']}", "bytes": audio_bytes},
-                                    "sentence": row['sentence'],
-                                    "tar_file": tar_file,
-                                }
-                                idx += 1
-                                
-                            except Exception as file_error:
-                                logger.warning(f"Error processing file {row['file_name']}: {file_error}")
-                                continue
-                                
-                except Exception as tar_error:
-                    logger.error(f"Error processing tar file {tar_file}: {tar_error}")
-                    continue
-            
-            logger.info(f"Total examples generated: {idx}")
-        
-        except Exception as e:
-            logger.error(f"Unexpected error in _generate_examples: {e}")
-            logger.error(traceback.format_exc())
-            raise
+    def _generate_examples(self, prompts_path, path_to_clips, audio_files):
+        """Yields examples as (key, example) tuples."""
+        examples = {}
+        metadata
+        with open(prompts_path, encoding="utf-8") as f:
+            for row in f:
+                data = row.strip().split("\t", 1)
+                file_name = data[0].strip()
+                audio_path = "/".join([path_to_clips, file_name])
+                examples[audio_path] = {
+                    "path": audio_path,
+                    "sentence": data[1],
+                }
+        inside_clips_dir = False
+        id_ = 0
+        for path, f in audio_files:
+            if path.startswith(path_to_clips):
+                inside_clips_dir = True
+                if path in examples:
+                    audio = {"path": path, "bytes": f.read()}
+                    yield id_, {**examples[path], "audio": audio}
+                    id_ += 1
+            elif inside_clips_dir:
+                break