| """Example script to unpack one shard of the 1xGPT Compression Challenge Test dataset.""" |
|
|
| import pathlib |
| import numpy as np |
|
|
| dir_path = pathlib.Path("test_v2.0") |
| rank = 0 |
|
|
| maps = [ |
| ("videos", "video", np.int32, [3, 32, 32]), |
| ("robot_states", "states", np.float32,[64, 25]), |
| ] |
|
|
| for sub_dir, name, dtype, shape_tail in maps: |
| fn = dir_path / sub_dir / f"{name}_{rank}.bin" |
| print(f"Reading {fn} shape={shape_tail} dtype={dtype.__name__}") |
| arr_size = np.prod(shape_tail) |
| arr_bytes = arr_size * np.dtype(dtype).itemsize |
| on_disk = fn.stat().st_size if fn.exists() else -1 |
| if on_disk != arr_bytes: |
| print(f" mismatch => on_disk={on_disk}, need={arr_bytes}") |
| if on_disk < 0: |
| continue |
| arr = np.memmap(fn, dtype=dtype, mode="r", shape=tuple(shape_tail)) |
| print(f" shape={arr.shape}, first row:", arr[0]) |
| print() |
|
|
