File size: 2,431 Bytes
d819851 | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 | #!/usr/bin/env python3
"""
Regenerate JSONL splits from dataset.csv
Useful if you lost the original JSONL files
"""
import pandas as pd
import json
def csv_to_jsonl(csv_path="dataset.csv", output_dir="."):
df = pd.read_csv(csv_path)
# Convert structure
records = []
for _, row in df.iterrows():
record = {
"id": row["id"],
"translation": {
"en": row["english"],
"kab": row["kabyle"]
},
"category": row["category"],
"subcategory": row["subcategory"],
"domain": "road_traffic",
"complexity": row["complexity"],
"tokens_en": int(row["tokens_en"]),
"tokens_kab": int(row["tokens_kab"])
}
records.append(record)
# Stratified split logic (same as original)
train, val, test = [], [], []
for r in records:
idx = int(r["id"].split("_")[-1])
cat = r["category"]
# Dangers: 70/15/15
if cat == "dangers":
if idx % 10 < 7:
train.append(r)
elif idx % 10 < 8:
val.append(r)
else:
test.append(r)
# Prohibitions: 60/20/20
elif cat == "prohibitions":
if idx % 10 < 6:
train.append(r)
elif idx % 10 < 8:
val.append(r)
else:
test.append(r)
# Obligations: 50/25/25
elif cat == "obligations":
if idx % 10 < 5:
train.append(r)
elif idx % 10 < 7:
val.append(r)
else:
test.append(r)
# End of restrictions: 40/30/30
else:
if idx % 10 < 4:
train.append(r)
elif idx % 10 < 7:
val.append(r)
else:
test.append(r)
# Save JSONL files
for name, data in [("train.jsonl", train), ("validation.jsonl", val), ("test.jsonl", test)]:
filepath = f"{output_dir}/{name}"
with open(filepath, 'w', encoding='utf-8') as f:
for item in data:
f.write(json.dumps(item, ensure_ascii=False) + '\n')
print(f"✓ {name}: {len(data)} entries")
return train, val, test
if __name__ == "__main__":
print("Regeneration des fichiers JSONL depuis dataset.csv...")
csv_to_jsonl()
print("\nDone!")
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