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import os |
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import json |
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import time |
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import re |
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from tqdm import tqdm |
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import numpy as np |
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import torch |
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import string |
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from typing import Optional, Tuple, List, Dict |
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import argparse |
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def load_json(file_path): |
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with open(file_path, "r", encoding="utf-8") as file: |
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data = json.load(file) |
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print(f"Loaded {len(data)} items from {file_path}") |
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return data |
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def save_json(data, file_path): |
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with open(file_path, "w", encoding="utf-8") as file: |
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json.dump(data, file, ensure_ascii=False, indent=4) |
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print(f"Saved {len(data)} items to {file_path}") |
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file_1 = "/share/project/sunshuang/deep_search/data_syn/data/mixed_data/splits/final_dataset_new/final_selected_dataset.json" |
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file_2 = "/share/project/sunshuang/deep_search/data_syn/data/mixed_data/splits/merged_tagged_domain_keypoints_keywords_count_hop_remove_2k_data/final_selected_dataset.json" |
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output_file = "/share/project/sunshuang/deep_search/data_syn/data/mixed_data/splits/merged_tagged_domain_keypoints_keywords_count_hop_remove_2k_data.json" |
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data_1 = load_json(file_1) |
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data_2 = load_json(file_2) |
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id_1 = [item["idx"] for item in data_1] |
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in_id_1 = 0 |
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not_in_id_1 = 0 |
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in_id_1_id = [] |
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dup_id = [] |
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remain_data = [] |
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for item in data_2: |
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if item["idx"] not in id_1: |
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remain_data.append(item) |
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not_in_id_1 += 1 |
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else: |
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if item["idx"] in in_id_1_id: |
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dup_id.append(item["idx"]) |
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else: |
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in_id_1_id.append(item["idx"]) |
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in_id_1 += 1 |
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print(f"in_id_1: {in_id_1}, not_in_id_1: {not_in_id_1}") |
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print(f"dup_id: {len(dup_id)}") |
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