Almost done extracting

olmocr/train/prepare_olmocrmix.py

@@ -4,10 +4,24 @@ from os import PathLike
 from pathlib import Path
 from typing import Optional
 import pandas as pd
+import tarfile
+from concurrent.futures import ProcessPoolExecutor, as_completed
+from tqdm import tqdm
 
 from huggingface_hub import snapshot_download
 
 
+def extract_tarball(tarball_path: Path, extract_dir: Path) -> int:
+    """Extract a single tarball and return the number of files extracted."""
+    try:
+        with tarfile.open(tarball_path, 'r') as tar:
+            tar.extractall(extract_dir)
+            return len(tar.getmembers())
+    except Exception as e:
+        print(f"Error extracting {tarball_path}: {e}")
+        return 0
+
+
 def prepare_olmocr_mix(dataset_path: str, subset: str, split: str, destination: str | PathLike, max_examples: Optional[int] = None) -> str:
     """
     Prepare OLMoCR mix dataset by downloading from HuggingFace and organizing into a folder structure.
@@ -52,8 +66,44 @@ def prepare_olmocr_mix(dataset_path: str, subset: str, split: str, destination:
     else:
         raise NotImplementedError()
 
+    # Step 3: Extract PDF tarballs
+    pdf_tarballs_dir = dest_path / "hugging_face" / "pdf_tarballs"
+    if pdf_tarballs_dir.exists():
+        extracted_dir = pdf_tarballs_dir / "extracted"
+        extracted_dir.mkdir(exist_ok=True)
+        
+        # Find all tarball files
+        tarball_files = list(pdf_tarballs_dir.glob("*.tar*")) + list(pdf_tarballs_dir.glob("*.tgz"))
+        
+        if tarball_files:
+            print(f"\nFound {len(tarball_files)} PDF tarballs to extract...")
+            
+            # Use ProcessPoolExecutor for parallel extraction
+            with ProcessPoolExecutor() as executor:
+                # Submit all tasks
+                future_to_tarball = {}
+                for tarball in tarball_files:
+                    future = executor.submit(extract_tarball, tarball, extracted_dir)
+                    future_to_tarball[future] = tarball
+                
+                # Process results as they complete with progress bar
+                total_files_extracted = 0
+                with tqdm(total=len(tarball_files), desc="Extracting tarballs") as pbar:
+                    for future in as_completed(future_to_tarball):
+                        tarball = future_to_tarball[future]
+                        try:
+                            files_extracted = future.result()
+                            total_files_extracted += files_extracted
+                            pbar.set_postfix({"files": total_files_extracted})
+                        except Exception as e:
+                            print(f"\nError with {tarball.name}: {e}")
+                        pbar.update(1)
+            
+            print(f"Extracted {total_files_extracted} files from tarballs to {extracted_dir}")
+    else:
+        print(f"No PDF tarballs directory found at {pdf_tarballs_dir}")
     
-    # Step 3: Process parquet files
+    # Step 4: Process parquet files
     total_processed = 0
     total_errors = 0
     
@@ -117,6 +167,9 @@ def prepare_olmocr_mix(dataset_path: str, subset: str, split: str, destination:
     
     print(f"Completed! Processed {total_processed} examples to {processed_dir}")
     print(f"Total errors: {total_errors}")
+    
+    
+    
     return str(processed_dir)