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.gitattributes

@@ -8,6 +8,8 @@
 *.h5 filter=lfs diff=lfs merge=lfs -text
 *.joblib filter=lfs diff=lfs merge=lfs -text
 *.lfs.* filter=lfs diff=lfs merge=lfs -text
+*.lz4 filter=lfs diff=lfs merge=lfs -text
+*.mds filter=lfs diff=lfs merge=lfs -text
 *.mlmodel filter=lfs diff=lfs merge=lfs -text
 *.model filter=lfs diff=lfs merge=lfs -text
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 *.zip filter=lfs diff=lfs merge=lfs -text
 *.zst filter=lfs diff=lfs merge=lfs -text
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+# Audio files - uncompressed
+*.pcm filter=lfs diff=lfs merge=lfs -text
+*.sam filter=lfs diff=lfs merge=lfs -text
+*.raw filter=lfs diff=lfs merge=lfs -text
+# Audio files - compressed
+*.aac filter=lfs diff=lfs merge=lfs -text
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+*.mp3 filter=lfs diff=lfs merge=lfs -text
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+*.wav filter=lfs diff=lfs merge=lfs -text
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+*.jpeg filter=lfs diff=lfs merge=lfs -text
+*.webp filter=lfs diff=lfs merge=lfs -text
+# Video files - compressed
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+*.webm filter=lfs diff=lfs merge=lfs -text
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cd5_train.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:f064279ca3b126c4ac630a80491db2ff64fc5fd89374f3c6fb12f7454f06f8de
+size 39831564

dataset_info.json

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+{
+  "cd4_train": {
+    "file_name": "cd4_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "cd4_test": {
+    "file_name": "cd4_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "cd5_train": {
+    "file_name": "cd5_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "cd5_test": {
+    "file_name": "cd5_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  
+  "cd3_train": {
+    "file_name": "cd3_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "cd3_test": {
+    "file_name": "cd3_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "cd4_tot24": {
+    "file_name": "cd4_tot24.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "sudoku_train": {
+    "file_name": "sudoku_train.csv",
+    "columns": {
+      "prompt": "quizzes",
+      "query": "",
+      "response": "solutions",
+      "history": ""
+    }
+  },
+  "sudoku_test": {
+    "file_name": "sudoku_test.csv",
+    "columns": {
+      "prompt": "quizzes",
+      "query": "",
+      "response": "solutions",
+      "history": ""
+    }
+  },
+  "sudoku_hard_train": {
+    "file_name": "hard_train.csv",
+    "columns": {
+      "prompt": "quizzes",
+      "query": "",
+      "response": "solutions",
+      "history": ""
+    }
+  },
+  "sudoku_hard_test": {
+    "file_name": "hard_test.csv",
+    "columns": {
+      "prompt": "quizzes",
+      "query": "",
+      "response": "solutions",
+      "history": ""
+    }
+  },
+  "path_train": {
+    "file_name": "path_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "path_test": {
+    "file_name": "path_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat5_train": {
+    "file_name": "3sat5_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat5_test": {
+    "file_name": "3sat5_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat7_train": {
+    "file_name": "3sat7_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat7_test": {
+    "file_name": "3sat7_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat9_train": {
+    "file_name": "3sat9_train.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  },
+  "3sat9_test": {
+    "file_name": "3sat9_test.jsonl",
+    "columns": {
+      "prompt": "input",
+      "query": "",
+      "response": "output",
+      "history": ""
+    }
+  }
+}

hard_train.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:ae0f0213c54b5156561732a1bd5baeadcd22f3734426d5de3d6c2c8619d82fd9
+size 16665079

path_train.jsonl

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+version https://git-lfs.github.com/spec/v1
+oid sha256:15c01304e7baae64a30c63678b969c562fdd94923e196f8b96122fcc079bffa6
+size 131998514

sudoku_train.csv

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+version https://git-lfs.github.com/spec/v1
+oid sha256:b9c13489f2a68af96074c12feccaf90bb9e87e0589df41bef4922b0ebe219a4e
+size 16500019

synthetic_graph.py

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+
+import json
+import random
+
+
+def save_jsonl(data, file):
+    with open(file, "w") as f:
+        for item in data:
+            json.dump(item, f)
+            f.write("\n")
+
+def path_stringfy(input_list, shuffle=True):
+    output_list = []
+    for i in range(len(input_list) - 1):
+        output_list.append(f'{input_list[i]},{input_list[i+1]}')
+    if shuffle:
+        random.shuffle(output_list)
+    return '/'.join(output_list)
+
+def paths_stringfy(input_lists, shuffle=True):
+    output_list = []
+    for input_list in input_lists:
+        for i in range(len(input_list) - 1):
+            output_list.append(f'{input_list[i]},{input_list[i+1]}')
+    if shuffle:
+        random.shuffle(output_list)
+    return '/'.join(output_list)
+
+def convert_to_jsonline(data_list):
+    res = []
+    for data in data_list:
+        answer_str = path_stringfy(data[0], shuffle=False)
+        reverse_answer_str = path_stringfy(data[0][::-1], shuffle=False)
+        path_str = paths_stringfy(data)
+        input_str = path_str + f'-{data[0][0]},{data[0][-1]}'
+        res.append({"input": input_str, "output": answer_str, "reversed": reverse_answer_str})
+    return res
+
+def generate_streams(num):
+    data = []
+    numbers = list(range(NODE_PER_STREAM*STREAM))
+    while len(data) < num:
+        sep_position = random.randint(0, NODE_PER_STREAM-1)
+        random.shuffle(numbers)
+        if str(numbers) in cache:
+            continue
+        else:
+            cache.add(str(numbers))
+
+        streams = [numbers[NODE_PER_STREAM*i:NODE_PER_STREAM*(i+1)] for i in range(STREAM)]
+        answer = streams[0]
+        for s in streams[1:]:
+            s[sep_position] = answer[sep_position]
+        data.append(streams)
+        print(len(data))
+    return data
+
+
+STREAM = 2
+NODE_PER_STREAM = 6
+NUM_TRAIN = 1000000
+NUM_TEST = 1000
+SEED = 1
+
+random.seed(SEED)
+cache = set()
+test_streams = generate_streams(NUM_TEST)
+train_streams = generate_streams(NUM_TRAIN)
+
+save_jsonl(convert_to_jsonline(test_streams), f"path_test-{STREAM}-{NODE_PER_STREAM}.jsonl")
+save_jsonl(convert_to_jsonline(train_streams), f"path_train-{STREAM}-{NODE_PER_STREAM}.jsonl")