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+python/tasky_commits_python_296181_329090.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_4245261_4278170.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript/tasky_commits_javascript_296181_329090.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript/tasky_commits_javascript_4179443_4212352.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript/tasky_commits_javascript_4343988_4376897.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript/tasky_commits_javascript_888543_921452.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_5199622_5232531.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_5824893_5857802.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript_add/tasky_commits_javascript_263272_296181.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript_add/tasky_commits_javascript_361999_394908.jsonl filter=lfs diff=lfs merge=lfs -text
+python_add/tasky_commits_python_230363_263272.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_3488354_3521263.jsonl filter=lfs diff=lfs merge=lfs -text
+python_add/tasky_commits_python_329090_361999.jsonl filter=lfs diff=lfs merge=lfs -text
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+python/tasky_commits_python_4640169_4673078.jsonl filter=lfs diff=lfs merge=lfs -text
+javascript/tasky_commits_javascript_361999_394908.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_5002168_5035077.jsonl filter=lfs diff=lfs merge=lfs -text
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+javascript_add/tasky_commits_javascript_197454_230363.jsonl filter=lfs diff=lfs merge=lfs -text
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+python/tasky_commits_python_5561621_5594530.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_4673078_4705987.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_5100895_5133804.jsonl filter=lfs diff=lfs merge=lfs -text
+python/tasky_commits_python_5594530_5627439.jsonl filter=lfs diff=lfs merge=lfs -text
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+python/tasky_commits_python_5397076_5429985.jsonl filter=lfs diff=lfs merge=lfs -text

inference_java.py

@@ -0,0 +1,148 @@
+# !pip install -q transformers datasets sentencepiece
+import argparse
+import gc
+import json
+import os
+
+import datasets
+import pandas as pd
+import torch
+from tqdm import tqdm
+from transformers import AutoModelForSequenceClassification, AutoTokenizer
+
+TOTAL_NUM_FILES_C4_TRAIN = 1024
+
+
+def parse_args():
+    parser = argparse.ArgumentParser()
+
+    parser.add_argument(
+        "--start",
+        type=int,
+        required=True,
+        help="Starting file number to download. Valid values: 0 - 1023",
+    )
+    parser.add_argument(
+        "--end",
+        type=int,
+        required=True,
+        help="Ending file number to download. Valid values: 0 - 1023",
+    )
+    parser.add_argument("--batch_size", type=int, default=32, help="Batch size")
+    parser.add_argument(
+        "--model_name",
+        type=str,
+        default="taskydata/deberta-v3-base_10xp3nirstbbflanseuni_10xc4",
+        help="Model name",
+    )
+    parser.add_argument(
+        "--local_cache_location",
+        type=str,
+        default="c4_download",
+        help="local cache location from where the dataset will be loaded",
+    )
+    parser.add_argument(
+        "--use_local_cache_location",
+        type=bool,
+        default=True,
+        help="Set True if you want to load the dataset from local cache.",
+    )
+    parser.add_argument(
+        "--clear_dataset_cache",
+        type=bool,
+        default=False,
+        help="Set True if you want to delete the dataset files from the cache after inference.",
+    )
+    parser.add_argument(
+        "--release_memory",
+        type=bool,
+        default=True,
+        help="Set True if you want to release the memory of used variables.",
+    )
+
+    args = parser.parse_args()
+    return args
+
+
+def chunks(l, n):
+    for i in range(0, len(l), n):
+        yield l[i : i + n]
+
+
+def batch_tokenize(data, batch_size):
+    batches = list(chunks(data, batch_size))
+    tokenized_batches = []
+    for batch in batches:
+        # max_length will automatically be set to the max length of the model (512 for deberta)
+        tensor = tokenizer(
+            batch,
+            return_tensors="pt",
+            padding="max_length",
+            truncation=True,
+            max_length=512,
+        )
+        tokenized_batches.append(tensor)
+    return tokenized_batches, batches
+
+
+def batch_inference(data, batch_size=32):
+    preds = []
+    tokenized_batches, batches = batch_tokenize(data, batch_size)
+    for i in tqdm(range(len(batches))):
+        with torch.no_grad():
+            logits = model(**tokenized_batches[i].to(device)).logits.cpu()
+        preds.extend(logits)
+    return preds
+
+
+if __name__ == "__main__":
+    args = parse_args()
+
+    tasky_commits_path = f"tasky_commits_java_{args.start}_{args.end}.jsonl"
+    if os.path.exists(f"java_add/{tasky_commits_path}"):
+        print("Exists:", tasky_commits_path)
+        exit()
+
+    tokenizer = AutoTokenizer.from_pretrained(args.model_name)
+    model = AutoModelForSequenceClassification.from_pretrained(args.model_name)
+    device = torch.device("cuda") if torch.cuda.is_available() else torch.device("cpu")
+    model.to(device)
+    model.eval()
+
+    path = "java_add_messages.jsonl"
+    ds = datasets.load_dataset("json", data_files=[path], ignore_verifications=True)["train"]
+    ds = ds[range(args.start, min(args.end, len(ds)))]
+    df = pd.DataFrame(ds, index=None)
+    #tasky_commits_path = f"tasky_commits_javascript_{args.start}_{args.end}.jsonl"
+    #if os.path.exists(f"javascript/{tasky_commits_path}"):
+    #    print("Exists:", tasky_commits_path)
+    #    exit()
+
+    texts = df["message"].to_list()
+    commits = df["commit"].to_list()
+    preds = batch_inference(texts, batch_size=args.batch_size)
+
+    assert len(preds) == len(texts)
+
+    # Write two jsonl files:
+    # 1) Probas for all of C4
+    # 2) Probas + texts for samples predicted as tasky
+    tasky_commits_path = f"tasky_commits_java_{args.start}_{args.end}.jsonl"
+
+    with open(tasky_commits_path, "w") as f:
+        for i in range(len(preds)):
+            predicted_class_id = preds[i].argmax().item()
+            pred = model.config.id2label[predicted_class_id]
+            tasky_proba = torch.softmax(preds[i], dim=-1)[-1].item()
+
+            f.write(
+                json.dumps(
+                    {
+                        "commit": commits[i],
+                        "message": texts[i],
+                        "proba": tasky_proba,
+                    }
+                )
+                + "\n"
+            )
+

inference.sh → inference_java.sh

@@ -22,4 +22,4 @@ TASK_START=$((($SLURM_ARRAY_TASK_ID) * $NUM_SAMPLES_PER_JOB))
 TASK_END=$(($TASK_START + $NUM_SAMPLES_PER_JOB))
 
 echo "Starting task $SLURM_ARRAY_TASK_ID with start $TASK_START and end $TASK_END"
-python inference.py --start $TASK_START --end $TASK_END
+python inference_java.py --start $TASK_START --end $TASK_END

inference.py → inference_javascript.py

@@ -99,7 +99,7 @@ if __name__ == "__main__":
     args = parse_args()
 
     tasky_commits_path = f"tasky_commits_javascript_{args.start}_{args.end}.jsonl"
-    if os.path.exists(f"javascript/{tasky_commits_path}"):
+    if os.path.exists(f"javascript_add/{tasky_commits_path}"):
         print("Exists:", tasky_commits_path)
         exit()
 
@@ -109,7 +109,7 @@ if __name__ == "__main__":
     model.to(device)
     model.eval()
 
-    path = "javascript_messages.jsonl"
+    path = "javascript_add_messages.jsonl"
     ds = datasets.load_dataset("json", data_files=[path], ignore_verifications=True)["train"]
     ds = ds[range(args.start, min(args.end, len(ds)))]
     df = pd.DataFrame(ds, index=None)

inference_javascript.sh

@@ -14,7 +14,7 @@ set -x -e
 source $six_ALL_CCFRWORK/start-tr13f-6B3-ml-t0
 echo "START TIME: $(date)"
 
-NUM_SAMPLES=4766203
+NUM_SAMPLES=3290900
 NUM_SAMPLES_PER_JOB=32909
 #NUM_SAMPLES_PER_JOB=128
 
@@ -22,4 +22,4 @@ TASK_START=$((($SLURM_ARRAY_TASK_ID) * $NUM_SAMPLES_PER_JOB))
 TASK_END=$(($TASK_START + $NUM_SAMPLES_PER_JOB))
 
 echo "Starting task $SLURM_ARRAY_TASK_ID with start $TASK_START and end $TASK_END"
-python inference.py --start $TASK_START --end $TASK_END
+python inference_javascript.py --start $TASK_START --end $TASK_END

inference_python.py

@@ -99,7 +99,7 @@ if __name__ == "__main__":
     args = parse_args()
 
     tasky_commits_path = f"tasky_commits_python_{args.start}_{args.end}.jsonl"
-    if os.path.exists(f"python/{tasky_commits_path}"):
+    if os.path.exists(f"python_add/{tasky_commits_path}"):
         print("Exists:", tasky_commits_path)
         exit()
 
@@ -109,7 +109,7 @@ if __name__ == "__main__":
     model.to(device)
     model.eval()
 
-    path = "python_messages.jsonl"
+    path = "python_add_messages.jsonl"
     ds = datasets.load_dataset("json", data_files=[path], ignore_verifications=True)["train"]
     ds = ds[range(args.start, min(args.end, len(ds)))]
     df = pd.DataFrame(ds, index=None)

java_add/tasky_commits_java_0_32909.jsonl

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+oid sha256:8abbe89263a7b460a82e70acc9be2c36181eeb4b209637f69f4b716b7db915fb
+size 6172691

java_add/tasky_commits_java_131636_164545.jsonl

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+oid sha256:b042c07d0707fa3f3509a9dc03e81b7d5a1c34518d5b17026f4f5a00d90ce5f0
+size 6208658

java_add/tasky_commits_java_164545_197454.jsonl

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+oid sha256:6d43dd366f76c0c856e532dbd38428cb87dff364a33e37ea999a7aded5135382
+size 6184881

java_add/tasky_commits_java_197454_230363.jsonl

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+oid sha256:6d6762759fd046f34b89087748025271dcd7913d190755992b81c2914a015812
+size 6114571

java_add/tasky_commits_java_230363_263272.jsonl

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+oid sha256:436fe13c365c8682d0adde45ee6d1a7c01424049e599244ab7cc578809ce040f
+size 6093075

java_add/tasky_commits_java_263272_296181.jsonl

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+oid sha256:ebcca770155994fc16268ca24f956e4dc66e05ee9b9bfcd3dc74500f258c9f4e
+size 6186736

java_add/tasky_commits_java_296181_329090.jsonl

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+oid sha256:f80541a91138f702d3daf1b115a66d9f9f39308671dfbc48cb5011fa0f27c779
+size 6134757

java_add/tasky_commits_java_329090_361999.jsonl

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+size 6129030

java_add/tasky_commits_java_32909_65818.jsonl

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+oid sha256:94e495dbeb2839a79056009f58cbb12312c8d22aedb9500e4b89fafb2267401e
+size 6148934

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+size 6159824

java_add/tasky_commits_java_427817_460726.jsonl

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+size 4805399

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java_add/tasky_commits_java_98727_131636.jsonl

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