chore: import upstream snapshot with attribution

PFPO/scripts/apps/pp_solution_gen_inputs.py

@@ -0,0 +1,54 @@
+import json
+import sys
+from argparse import ArgumentParser
+
+from datasets import load_dataset
+from tqdm import tqdm
+
+sys.set_int_max_str_digits(0)
+
+_vanilla_prompt = """You are an expert programmer. Here is a programming problem:
+--------
+{}
+--------
+Please carefully comprehend the requirements in the problem, and write down the solution program to pass it under the given time and memory constraints.
+
+**REMEMBER** to strictly follow the steps below to help reduce the potential flaws:
+(1) According to the input scale and the time/memory constraints, think about the time complexity and space complexity of your solution.
+(2) Think **step-by-step** to design the algorithm.
+(3) Translate your thoughts into Python program to solve it.
+
+Besides, your Python solution program should be located between <BEGIN> and <END> tags. For example:
+<BEGIN>
+t = int(input())
+...
+print(ans)
+<END>
+
+Now, remember my instruction and let's get started:
+"""
+
+PROMPTS = {
+    "vanilla": _vanilla_prompt,
+}
+
+
+def main():
+    parser = ArgumentParser()
+    parser.add_argument("--split", type=str, default="train")
+    parser.add_argument("--prompt_type", type=str, default="vanilla")
+    parser.add_argument("--output_file", type=str, required=True)
+    args = parser.parse_args()
+
+    data = load_dataset("codeparrot/apps", split="train").to_list()
+    print(len(data))
+
+    with open(args.output_file, "w") as f:
+        for item in tqdm(data, desc="Writing prompts"):
+            prompt = PROMPTS[args.prompt_type].format(item["question"])
+            item["prompt"] = prompt
+            f.write(json.dumps(item) + "\n")
+
+
+if __name__ == '__main__':
+    main()