run.py

#!/usr/bin/env python3
"""Standalone script: download dataset, train model, generate music."""
import subprocess
import sys
import os
import glob

BASE = os.path.dirname(os.path.abspath(__file__))
DATA_DIR = os.path.join(BASE, "data")
MIDI_DIR = os.path.join(DATA_DIR, "midi_files")

def download_dataset():
    if os.path.exists(MIDI_DIR) and glob.glob(os.path.join(MIDI_DIR, "**", "*.mid"), recursive=True):
        print(f"Dataset already exists at {MIDI_DIR}")
        return
    
    os.makedirs(DATA_DIR, exist_ok=True)
    
    print("Downloading MIDI dataset via git clone...")
    env = os.environ.copy()
    env["GIT_LFS_SKIP_SMUDGE"] = "1"
    
    result = subprocess.run(
        ["git", "clone", "--depth", "1",
         "https://huggingface.co/datasets/drengskapur/midi-classical-music",
         MIDI_DIR],
        env=env,
        capture_output=True,
        text=True,
    )
    
    if result.returncode != 0:
        print(f"Git clone failed: {result.stderr}")
        # Fallback: use Python to download
        print("Trying Python download fallback...")
        from huggingface_hub import snapshot_download
        snapshot_download(
            repo_id="drengskapur/midi-classical-music",
            repo_type="dataset",
            local_dir=MIDI_DIR,
            allow_patterns=["*.mid"],
        )
    
    midi_files = glob.glob(os.path.join(MIDI_DIR, "**", "*.mid"), recursive=True)
    print(f"Downloaded {len(midi_files)} MIDI files")

def main():
    # Step 1: Download
    download_dataset()
    
    # Remove stale cache
    cache = os.path.join(DATA_DIR, "tokenized_cache.pkl")
    if os.path.exists(cache):
        os.remove(cache)
        print("Removed stale cache")
    
    # Step 2: Train + Generate
    sys.path.insert(0, BASE)
    os.chdir(BASE)
    
    args = sys.argv[1:] if len(sys.argv) > 1 else ["train+generate", "--epochs", "20", "--batch-size", "4", "--seq-len", "512"]
    sys.argv = ["s00_main"] + args
    
    from src.s00_main import main as run_main
    run_main()

if __name__ == "__main__":
    main()