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"""
Convert the json data to a parquet file
"""
import json
import random
import pandas as pd
def load_domains_map():
"""
Load the domain mapping from the json file
"""
with open("oos-eval-master/data/domains.json", "r", encoding="utf8") as f:
domains = json.loads(f.read())
domain_map = []
label_map = []
label2domain = {"oos": ("oos", 0, 0)} # domain, domain_id, label_id
domain_map.append((0, "oos"))
label_map.append((0, "oos"))
domain_id = 1
label_id = 1
for domain, labels in domains.items():
for label in labels:
label2domain[label] = (domain, domain_id, label_id)
label_map.append((label_id, label))
label_id += 1
domain_map.append((domain_id, domain))
domain_id += 1
with open("domain_map.txt", "w", encoding="utf8") as f:
for domain_id, domain in domain_map:
f.write(f"{domain_id}\t{domain}\n")
with open("label_map.txt", "w", encoding="utf8") as f:
for label_id, label in label_map:
f.write(f"{label_id}\t{label2domain[label][0]}:{label}\n")
return label2domain
LABEL_2_DOMAIN = load_domains_map()
def run():
"""
Convert the json data to a parquet file
"""
rows = []
with open("oos-eval-master/data/data_full.json", "r", encoding="utf8") as f:
data = json.loads(f.read())
for split in data:
for text, label in data[split]:
rows.append(
{
"text": text,
"domain": LABEL_2_DOMAIN[label][1],
"intent": LABEL_2_DOMAIN[label][2],
"split": split,
}
)
random.shuffle(rows)
df = pd.DataFrame(rows)
df.to_csv("data_full.csv", index=False)
if __name__ == "__main__":
run()
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