import argparse import os import subprocess import sys from pathlib import Path def main(): parser = argparse.ArgumentParser(description="Azure ML Driver for CAFA Evaluator") parser.add_argument("--data_dir", type=str, required=True, help="Mount point for the data asset") parser.add_argument("--prediction_path", type=str, required=True, help="Relative path to prediction files inside data asset") parser.add_argument("--output_dir", type=str, default="./outputs", help="Output directory for results") args = parser.parse_args() # Define relative paths for assets within the mounted data directory # Updated based on user feedback: # ground truth: validation/validation_superset_term.tsv # obo: go_info/go-basic.obo # ia: IA.tsv gt_rel_path = "validation/validation_superset_term.tsv" obo_rel_path = "go_info/go-basic.obo" ia_rel_path = "IA.tsv" # Construct absolute paths data_dir = Path(args.data_dir) ground_truth_path = data_dir / gt_rel_path ontology_path = data_dir / obo_rel_path ia_path = data_dir / ia_rel_path prediction_dir = data_dir / args.prediction_path output_dir = Path(args.output_dir) # basic validation missing = [] if not ground_truth_path.exists(): missing.append(f"Ground truth: {ground_truth_path}") if not ontology_path.exists(): missing.append(f"Ontology: {ontology_path}") if not ia_path.exists(): missing.append(f"IA file: {ia_path}") if not prediction_dir.exists(): missing.append(f"Predictions: {prediction_dir}") if missing: print("="*60) print("❌ Critical Input Files Missing:") for m in missing: print(f" - {m}") print("Listing data dir contents for debugging:") try: for root, dirs, files in os.walk(data_dir): level = root.replace(str(data_dir), '').count(os.sep) if level < 2: indent = ' ' * 4 * (level) print(f'{indent}{os.path.basename(root)}/') for f in files: print(f'{indent} {f}') except: pass print("="*60) sys.exit(1) # Ensure output directory exists (though CAFA evaluator might create it, good practice) output_dir.mkdir(parents=True, exist_ok=True) # Resolve script path # We assume this script is running from the root of the source directory where CAFA-evaluator-PK is located. script_path = Path("CAFA-evaluator-PK/src/cafaeval/__main__.py") if not script_path.exists(): if Path("src/CAFA-evaluator-PK/src/cafaeval/__main__.py").exists(): script_path = Path("src/CAFA-evaluator-PK/src/cafaeval/__main__.py") else: print(f"❌ Error: CAFA evaluator script not found at {script_path}") sys.exit(1) # Set PYTHONPATH to include the CAFA-evaluator source # The module is in CAFA-evaluator-PK/src cafa_src_path = script_path.parent.parent.resolve() env = os.environ.copy() env["PYTHONPATH"] = str(cafa_src_path) + os.pathsep + env.get("PYTHONPATH", "") cmd = [ sys.executable, str(script_path), str(ontology_path), str(prediction_dir), str(ground_truth_path), "-ia", str(ia_path), "-out_dir", str(output_dir), "-no_orphans", # often good practice for stable evaluation, can remove if not desired "-th_step", "0.01" ] print("="*60) print("🚀 Starting CAFA Evaluator Wrapper") print(f"📂 Predictions: {prediction_dir}") print(f"📂 Outputs: {output_dir}") print(f"🔧 PYTHONPATH: {env['PYTHONPATH']}") print(f"📜 Command: {' '.join(cmd)}") print("="*60) try: # Run subprocess and stream output # Using check=True to raise exception on non-zero exit code process = subprocess.run( cmd, check=True, stdout=sys.stdout, stderr=sys.stderr, # Pipe stderr to sys.stderr so it shows up in AML logs text=True, env=env # Pass modified env ) print("="*60) print("✅ CAFA Evaluator completed successfully.") print("="*60) except subprocess.CalledProcessError as e: print("="*60) print("❌ CAFA EVALUATOR ERROR") print(f"Command failed with exit code {e.returncode}") print("See stderr above for details.") print("="*60) sys.exit(e.returncode) except Exception as e: print("="*60) print(f"❌ UNEXPECTED ERROR: {e}") print("="*60) sys.exit(1) if __name__ == "__main__": main()