Datasets:

ZhankuiHe
/

inspired_cikm

+""" Extract the prediction samples from the raw prediction file.
+    i.e., ${data}/test_raw.jsonl to ${data}/test.jsonl
+"""
+import json
+from jsonargparse import CLI
+def context2input(l, start=0):
+    """ Given a list of context, just following UniCRS to format the context.
+    """
+    context = ''
+    for i, utt in enumerate(l):
+        if utt == '' or utt == ' ':
+            continue
+        if i % 2 == start:
+            context += '\nUser: '
+        else:
+            context += '\nSystem: '
+        context += utt
+    return context + '\nSystem: '
+def main(from_json: str = None, to_json: str = None, start: int = 0):
+    with open(from_json) as fr, open(to_json, 'w') as fw:
+        for l in fr:
+            l = json.loads(l)
+            if l['is_user'] == 0 and len(l['rec']) > 0:
+                l['input'] = context2input(l['context'], start=start)
+                fw.write(json.dumps(l) + '\n')
+if __name__ == '__main__':
+    # python extract_prediction.py --from_json=inspired/test_raw.jsonl --to_json=inspired/test.jsonl --start 0
+    # python extract_prediction.py --from_json=redial/test_raw.jsonl --to_json=redial/test.jsonl --start 1
+    # python extract_prediction.py --from_json=reddit/test_raw.jsonl --to_json=reddit/test.jsonl --start 1
+    CLI(main)

gen_itemname.py ADDED Viewed

	@@ -0,0 +1,13 @@

+import json
+entity2id = "entity2id.json"
+entity2id = json.load(open(entity2id, "r"))
+itemids = "item_ids.json"
+itemids = json.load(open(itemids, "r"))
+itemnames = [k for k, v in entity2id.items() if v in itemids]
+with open("itemnames.json", "w") as f:
+    json.dump(itemnames, f)

item_global2local.json ADDED Viewed

	@@ -0,0 +1 @@

+ {"@0": 0, "@100": 1, "@10006": 2, "@10035": 3, "@10036": 4, "@10038": 5, "@1004": 6, "@10056": 7, "@1007": 8, "@10088": 9, "@10092": 10, "@10093": 11, "@10108": 12, "@10109": 13, "@10126": 14, "@10139": 15, "@10148": 16, "@10149": 17, "@10158": 18, "@10161": 19, "@1017": 20, "@1018": 21, "@10189": 22, "@10192": 23, "@10209": 24, "@10211": 25, "@10220": 26, "@10233": 27, "@10244": 28, "@1027": 29, "@10272": 30, "@10291": 31, "@10300": 32, "@10302": 33, "@10307": 34, "@10320": 35, "@10323": 36, "@10357": 37, "@10358": 38, "@10369": 39, "@10397": 40, "@10415": 41, "@10426": 42, "@10439": 43, "@10445": 44, "@10468": 45, "@10473": 46, "@10495": 47, "@10504": 48, "@10505": 49, "@10510": 50, "@10515": 51, "@10519": 52, "@10550": 53, "@10553": 54, "@10572": 55, "@10592": 56, "@10594": 57, "@10601": 58, "@10606": 59, "@10608": 60, "@10618": 61, "@10622": 62, "@10632": 63, "@10643": 64, "@10664": 65, "@10678": 66, "@10680": 67, "@10686": 68, "@1069": 69, "@10698": 70, "@10713": 71, "@10720": 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