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.gitattributes

@@ -56,3 +56,4 @@ saved_model/**/* filter=lfs diff=lfs merge=lfs -text
 # Video files - compressed
 *.mp4 filter=lfs diff=lfs merge=lfs -text
 *.webm filter=lfs diff=lfs merge=lfs -text
+senpos/train.jsonl filter=lfs diff=lfs merge=lfs -text

README.md

@@ -0,0 +1,30 @@
+---
+configs:
+- config_name: default
+  data_files:
+  - split: clozet_train
+    path: clozet/train*
+  - split: clozet_val
+    path: clozet/val*
+  - split: clozet_test
+    path: clozet/test*
+  - split: senpos_train
+    path: senpos/train*
+  - split: senpos_val
+    path: senpos/val*
+  - split: senpos_test
+    path: senpos/test*
+  - split: plotcom_train
+    path: plotcom/train*
+  - split: plotcom_val
+    path: plotcom/val*
+  - split: plotcom_test
+    path: plotcom/test*
+  - split: outgen_train
+    path: outgen/train*
+  - split: outgen_val
+    path: outgen/val*
+  - split: outgen_test
+    path: outgen/test*
+
+---

senpos/README.md

@@ -0,0 +1,37 @@
+# Sentence Position Prediction Dataset
+
+### Data Example
+
+```
+{
+	"story": 
+		"为了证明自己看见了这一切，路过银树林时，守望星折了一根小树枝。[MASK]丽娜听到树枝折断的声音时，回头问：“什么声音？”[MASK]“什么声音也没有。”[MASK]她的大姐说，“可能是哪座城堡的塔楼里，猫头鹰在叫唤。”[MASK]她讲话的时候，迈克悄悄地溜到前头，上了楼梯，第一个进了公主们的房间。[MASK]他推开窗户，顺着藤条滑了下去。[MASK]到花园的时候，太阳刚刚开始升起，他要开始工作了。[MASK]这一天，迈克捆扎鲜花的时候，故意把那根银色的树枝扎进了献给小公主的花里。[MASK]不过，她没有告诉姐姐们。", 
+	"sentence": 
+		"丽娜发现银树枝时，吃惊极了。", 
+	"label": 
+		8
+}
+```
+
+- "Story" (`str`)：input story，`<MASK>` means the candidate position
+- "sentence" (`str`)：the removed sentence
+- "label" (`int`): label=$l$ means the $l$-th position is correct.
+
+
+
+### Evaluation
+
+The prediction result should have the same format with `test.jsonl`
+
+```shell
+python eval.py prediction_file test.jsonl
+```
+
+
+
+We use accuracy as the evaluation metric. The output of the script `eval.py` is a dictionary as follows:
+
+```python
+{"accuracy": _}
+```
+

senpos/eval.py

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+import json
+import argparse
+import sys
+import numpy as np
+import jieba
+from nltk.translate.bleu_score import sentence_bleu, SmoothingFunction
+from nltk import ngrams
+
+
+
+def load_file(filename):
+    data = []
+    with open(filename, "r") as f:
+        for line in f.readlines():
+            data.append(json.loads(line))
+        f.close()
+    return data
+
+def proline(line):
+    return " ".join([w for w in jieba.cut("".join(line.strip().split()))])
+
+
+def compute(golden_file, pred_file, return_dict=True):
+    golden_data = load_file(golden_file)
+    pred_data = load_file(pred_file)
+
+    if len(golden_data) != len(pred_data):
+        raise RuntimeError("Wrong Predictions")
+
+    num = 0
+    for g, p in zip(golden_data, pred_data):
+        if isinstance(g["label"], str):
+            l = int(g["label"].strip())
+        elif isinstance(g["label"], int):
+            l = g["label"]
+        else:
+            raise Exception("Data type error")
+
+        if isinstance(p["label"], str):
+            p = int(p["label"].strip())            
+        elif isinstance(p["label"], int):
+            p = p["label"]            
+        else:
+            raise Exception("Data type error")
+        if l == p:
+            num += 1
+
+    return {'accuracy': float(num)/len(golden_data)}
+
+def main():
+    argv = sys.argv
+    print("预测结果：{}, 测试集: {}".format(argv[1], argv[2]))
+    print(compute(argv[2], argv[1]))
+
+
+if __name__ == '__main__':
+    main()

senpos/train.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ef2b2d8a7baac9680295329a666a1ca773495c6d8b195164564661c9c8ae08b4
+size 18810263