| """Runnable example: load the WOD-E2E Fast-dDrive SASD Parquet shards and reconstruct one | |
| sample, framework-free (numpy + pyarrow only). Works on a TPU host, GPU box, or CPU. | |
| python load_example.py # reads local ./train-*.parquet | |
| python load_example.py <dir> # reads <dir>/train-*.parquet | |
| """ | |
| import glob, json, os, sys | |
| import numpy as np | |
| import pyarrow.parquet as pq | |
| d = sys.argv[1] if len(sys.argv) > 1 else "." | |
| info = json.load(open(os.path.join(d, "dataset_info_train.json"))) | |
| ADT = info["array_dtypes"] | |
| paths = sorted(glob.glob(os.path.join(d, "train-*.parquet"))) | |
| row = pq.read_table(paths[0]).to_pylist()[0] | |
| def dec(name): | |
| return np.frombuffer(row[name], np.dtype(ADT[name])).reshape(tuple(row[name + "_shape"])) | |
| print(f"shards={len(paths)} num_samples={info['num_samples']} sample_id={row['sample_id']}") | |
| print(f"L={row['L']} n_blocks={row['n_blocks']}") | |
| for name in ADT: | |
| a = dec(name) | |
| print(f" {name:16s} {str(a.shape):14s} {a.dtype}") | |
| print("input_ids[:12] =", dec("input_ids")[:12].tolist()) | |