import jsonlines if __name__=="__main__": total_lines = 460729 num_img_lines = 64860 first_split_index = int(num_img_lines * 0.9) second_split_index = first_split_index + int((num_img_lines) * 0.05) print("Sizes of datasets:") print("Train:", first_split_index, "\n90%") print("Test:", second_split_index - first_split_index, "\n5%") print("Val:", num_img_lines - second_split_index, "\n5%") # with jsonlines.open("dataset.jsonl", mode='r') as reader: # with jsonlines.open("mse_text_img_QA_dataset.jsonl", mode='w') as writer1: # with jsonlines.open("mse_llemma_dataset.jsonl", mode='w') as writer2: # count = 0 # for obj in reader: # if count < num_img_lines: # writer1.write(obj) # else: # writer2.write(obj) # count = count + 1 # print(count) # with jsonlines.open("mse_text_img_QA_dataset.jsonl", mode='r') as reader: # with jsonlines.open("mse_text_img_QA_ds_train.jsonl", mode='w') as writer1: # with jsonlines.open("mse_text_img_QA_ds_test.jsonl", mode='w') as writer2: # with jsonlines.open("mse_text_img_QA_ds_val.jsonl", mode='w') as writer3: # count = 0 # for obj in reader: # if count < first_split_index: # writer1.write(obj) # elif count < second_split_index: # writer2.write(obj) # else: # writer3.write(obj) # count = count + 1 with jsonlines.open("mse_llemma_dataset.jsonl", mode='r') as reader: with jsonlines.open("mse_llemma_text_dataset.jsonl", mode='w') as writer: for obj in reader: qa = "Question: " + obj["body"] + "\nAnswer: " is_accepted = False best_score = float('-inf') output_text = "" for i in range(len(obj["answers"])): if bool(obj["answers"][i]["accepted"]) == True: if is_accepted == False: is_accepted = True best_score = int(obj["answers"][i]["score"]) output_text = obj["answers"][i]["body"] elif int(obj["answers"][i]["score"]) > best_score: best_score = int(obj["answers"][i]["score"]) output_text = obj["answers"][i]["body"] elif int(obj["answers"][i]["score"]) > best_score: best_score = int(obj["answers"][i]["score"]) output_text = obj["answers"][i]["body"] qa = qa + output_text text_dict = {} text_dict["text"] = qa text_dict["meta"] = None writer.write(text_dict)