Delete extract_shards.py

extract_shards.py

@@ -1,101 +0,0 @@
-
-"""
-Extract tar shards back to original structure
-"""
-import argparse
-import tarfile
-import csv
-from pathlib import Path
-from tqdm import tqdm
-from collections import defaultdict
-import shutil
-
-def parse_args():
-    parser = argparse.ArgumentParser(
-        description="Extract tar shards to recreate dataset"
-    )
-    parser.add_argument(
-        "--sharded-dir",
-        type=Path,
-        default=".",
-        help="Directory containing audio/ and metadata/ folders"
-    )
-    parser.add_argument(
-        "--output-dir",
-        type=Path,
-        default="extracted",
-        help="Output directory for extracted dataset"
-    )
-    return parser.parse_args()
-
-
-def main():
-    args = parse_args()
-    
-    audio_dir = args.sharded_dir / "audio"
-    metadata_file = args.sharded_dir / "metadata" / "metadata.csv"
-    
-    if not audio_dir.exists():
-        raise FileNotFoundError(f"Audio directory not found: {audio_dir}")
-    if not metadata_file.exists():
-        raise FileNotFoundError(f"Metadata not found: {metadata_file}")
-    
-    # Read metadata to understand structure
-    print("Reading metadata...")
-    with open(metadata_file, 'r', encoding='utf-8') as f:
-        reader = csv.DictReader(f)
-        rows = list(reader)
-    
-    # Group by subset and shard
-    shards_by_subset = defaultdict(set)
-    for row in rows:
-        subset = row['subset']
-        shard = row['shard']
-        shards_by_subset[subset].add(shard)
-    
-    print(f"Found {len(rows):,} samples across {len(shards_by_subset)} subsets")
-    
-    
-        # Extract all shards
-    for subset in sorted(shards_by_subset.keys()):
-        print(f"\nExtracting {subset}...")
-        subset_output = args.output_dir / subset / "audio"
-        subset_output.mkdir(parents=True, exist_ok=True)
-        
-        shards = sorted(shards_by_subset[subset])
-        
-        for shard_name in tqdm(shards, desc=f"  {subset}"):
-            shard_path = audio_dir / subset / shard_name
-            
-            if not shard_path.exists():
-                print(f"Warning: {shard_path} not found, skipping")
-                continue
-            
-            # Extract tar
-            with tarfile.open(shard_path, 'r') as tar:
-                tar.extractall(path=subset_output)
-
-    metadata_dir = Path(args.sharded_dir) / "metadata"
-    output_dir = Path(args.output_dir)
-
-    # Create the output directory if it does not exist
-    output_dir.mkdir(parents=True, exist_ok=True)
-
-    # Copy every CSV file
-    for csv_file in metadata_dir.glob("*.csv"):
-        destination = output_dir / csv_file.name
-        shutil.copy2(csv_file, destination)
-    
-    print("\n" + "="*60)
-    print("Extraction complete!")
-    print("="*60)
-    print(f"Output directory: {args.output_dir}")
-    print(f"\nTo process the dataset:")
-    print(f"python process_dataset.py \\")
-    print(f"  --taskmaster-root-dir {args.output_dir} \\")
-    print(f"  --aug-dataset-save-dir ./processed \\")
-    print(f"  --normalize-text")
-
-
-if __name__ == "__main__":
-    main()