search.py 1.4 KB

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  1. import argparse
  2. from extra.optimization.helpers import ast_str_to_lin
  3. from tinygrad import dtypes
  4. from tinygrad.helpers import BEAM, getenv
  5. from tinygrad.device import Device, Compiled
  6. from tinygrad.codegen.kernel import Kernel
  7. from tinygrad.engine.search import time_linearizer, beam_search, bufs_from_lin
  8. if __name__ == '__main__':
  9. parser = argparse.ArgumentParser(description="Run a search for the optimal opts for a kernel", formatter_class=argparse.ArgumentDefaultsHelpFormatter)
  10. parser.add_argument("--ast", type=str, default=None, help="the ast for the kernel to be optimized")
  11. parser.add_argument("--file", type=str, default=None, help="a file containing asts to be optimized, one per line")
  12. args = parser.parse_args()
  13. device: Compiled = Device[Device.DEFAULT]
  14. print(f"optimizing for {Device.DEFAULT}")
  15. if args.ast is not None:
  16. ast_strs = [args.ast]
  17. elif args.file is not None:
  18. with open(args.file, 'r') as file:
  19. ast_strs = file.readlines()
  20. for i, ast_str in enumerate(ast_strs):
  21. print(f"optimizing {i}/{len(ast_strs)}\nast={ast_str}")
  22. lin = ast_str_to_lin(ast_str, opts=device.renderer)
  23. rawbufs = bufs_from_lin(lin)
  24. lin = beam_search(lin, rawbufs, getenv("BEAM", 8), bool(getenv("BEAM_ESTIMATE", 1)))
  25. tm = time_linearizer(lin, rawbufs, allow_test_size=False, cnt=10)
  26. print(f"final time {tm*1e6:9.0f} us: {lin.colored_shape()}")
  27. print(lin.applied_opts)