| import ast, hashlib, json, random |
| from collections import Counter, defaultdict |
| from datasets import load_dataset |
|
|
| random.seed(42) |
| MAX_PER_SOURCE = 200 |
| MAX_ROWS = 90000 |
| MAX_OPT = 12 |
|
|
|
|
| def load_side(ds, rows, per_source, group_ids, fingerprints): |
| for r in ds: |
| src = r["source"] |
| if per_source[src] >= MAX_PER_SOURCE: |
| continue |
| try: |
| opts = ast.literal_eval(r["options"]) if isinstance(r["options"], str) else r["options"] |
| tgt = ast.literal_eval(r["target"]) if isinstance(r["target"], str) else r["target"] |
| except Exception: |
| continue |
| if not isinstance(opts, list) or not (2 <= len(opts) <= MAX_OPT): |
| continue |
| if not isinstance(tgt, list) or len(tgt) != len(opts): |
| continue |
| if sum(1 for t in tgt if t and t > 0) != 1: |
| continue |
| try: |
| tgt = [float(t) for t in tgt] |
| except Exception: |
| continue |
| st = r["state"] if isinstance(r["state"], str) else json.dumps(r["state"], sort_keys=True) |
| fp = hashlib.sha256(f"{st}|{r['question']}|{opts}".encode()).hexdigest() |
| if fp in fingerprints: |
| continue |
| fingerprints.add(fp) |
| group_ids.add(r["group_id"]) |
| rows.append({"state": st, "id": r["id"], "kind": r["kind"], |
| "options": [str(o) for o in opts], "target": tgt, |
| "question": r["question"], "source": f"tasksource:{src}", |
| "group_id": r["group_id"]}) |
| per_source[src] += 1 |
| if len(rows) >= MAX_ROWS: |
| return True |
| return False |
|
|
|
|
| rows, per_source, group_ids, fps = [], Counter(), set(), set() |
| print("streaming train...") |
| done = load_side(load_dataset("tasksource/tasksource-jev-typed-decisions", split="train", streaming=True), |
| rows, per_source, group_ids, fps) |
| random.shuffle(rows) |
| train = [r for r in rows if not r["source"].startswith("DEVMARK")] |
| dev = [r for r in rows if r["source"].startswith("DEVMARK")] |
| train, dev = [r for r in rows if hashlib.md5(r["group_id"].encode()).hexdigest()[0] != "0"], \ |
| [r for r in rows if hashlib.md5(r["group_id"].encode()).hexdigest()[0] == "0"] |
| train, dev = train[:76000], dev[:6000] |
| used_groups = {r["group_id"] for r in train} |
| dev = [r for r in dev if r["group_id"] not in used_groups] |
| with open("/root/alea/data/tasksource_train.jsonl", "w") as f: |
| for r in train: |
| f.write(json.dumps(r) + "\n") |
| with open("/root/alea/data/tasksource_dev.jsonl", "w") as f: |
| for r in dev: |
| f.write(json.dumps(r) + "\n") |
| rep = {"train": len(train), "dev": len(dev), "sources": len(per_source), |
| "kinds": Counter(r["kind"] for r in train + dev), |
| "top_sources": per_source.most_common(20)} |
| open("/root/alea/data/tasksource_conversion_report.json", "w").write(json.dumps(rep, indent=2, default=str)) |
| print(rep) |
|
|
