fix: error handling

asr_dataset.py

@@ -39,92 +39,121 @@ class ASRDataset(datasets.GeneratorBasedBuilder):
             }),
             supervised_keys=None,
             citation=_CITATION,
-            # Explicitly specify columns to show in the data viewer
-            homepage="https://huggingface.co/datasets/your-dataset",
-            license="",
-            task_templates=[
-                datasets.AutomaticSpeechRecognition(
-                    audio_column="audio",
-                    transcription_column="sentence",
-                )
-            ],
         )
 
     def _split_generators(self, dl_manager):
-        return [
-            datasets.SplitGenerator(
-                name=datasets.Split.TRAIN,
-                gen_kwargs={
-                    "split": "train",
-                    "data_dir": self.config.data_dir,
-                },
-            ),
-        ]
+        """Returns SplitGenerators with added error handling."""
+        try:
+            return [
+                datasets.SplitGenerator(
+                    name=datasets.Split.TRAIN,
+                    gen_kwargs={
+                        "split": "train",
+                        "data_dir": self.config.data_dir,
+                    },
+                ),
+            ]
+        except Exception as e:
+            logger.error(f"Error in _split_generators: {e}")
+            logger.error(traceback.format_exc())
+            raise
 
     def _prepare_metadata(self, data_dir: str) -> pd.DataFrame:
-        """Prepare metadata by adding tar file information."""
-        logger.info("Preparing metadata with tar file information...")
-        
-        # Read metadata
-        metadata_path = os.path.join(data_dir, "metadata.csv")
-        df = pd.read_csv(metadata_path, sep='\t', names=['file_name', 'sentence'], encoding="utf-8")
-        
-        # 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)
-            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
-        
-        # Remove entries where tar_file is None (file not found in any tar)
-        df = df.dropna(subset=['tar_file'])
+        """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
         
-        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."""
-        # 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}...")
+        """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")
             
-            try:
-                with tarfile.open(tar_path, 'r') as tar:
-                    for _, row in group.iterrows():
-                        try:
-                            member = tar.getmember(row['file_name'])
-                            f = tar.extractfile(member)
-                            if f is None:
+            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
                                 
-                            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 e:
-                            logger.warning(f"Error processing file {row['file_name']}: {str(e)}")
-                            continue
-                            
-            except Exception as e:
-                logger.error(f"Error processing tar file {tar_file}: {str(e)}")
-                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