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models/LLaVA/llava/eval/eval_science_qa_gpt4_requery.py
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149
models/LLaVA/llava/eval/eval_science_qa_gpt4_requery.py
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import argparse
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import json
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import os
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import re
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import random
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from collections import defaultdict
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def get_args():
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parser = argparse.ArgumentParser()
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parser.add_argument('--base-dir', type=str)
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parser.add_argument('--gpt4-result', type=str)
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parser.add_argument('--requery-result', type=str)
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parser.add_argument('--our-result', type=str)
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parser.add_argument('--output-result', type=str)
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parser.add_argument('--split', type=str, default='test')
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parser.add_argument('--options', type=list, default=["A", "B", "C", "D", "E"])
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return parser.parse_args()
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def convert_caps(results):
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fakecaps = []
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for result in results:
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image_id = result['question_id']
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caption = result['text']
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fakecaps.append({"image_id": int(image_id), "caption": caption})
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return fakecaps
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def get_pred_idx(prediction, choices, options):
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"""
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Get the index (e.g. 2) from the prediction (e.g. 'C')
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"""
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if prediction in options[:len(choices)]:
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return options.index(prediction)
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else:
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return random.choice(range(len(choices)))
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if __name__ == "__main__":
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args = get_args()
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base_dir = args.base_dir
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split_indices = json.load(open(os.path.join(base_dir, "pid_splits.json")))[args.split]
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problems = json.load(open(os.path.join(base_dir, "problems.json")))
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our_predictions = [json.loads(line) for line in open(args.our_result)]
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our_predictions = {pred['question_id']: pred for pred in our_predictions}
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split_problems = {idx: problems[idx] for idx in split_indices}
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requery_predictions = [json.loads(line) for line in open(args.requery_result)]
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requery_predictions = {pred['question_id']: pred for pred in requery_predictions}
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gpt4_predictions = json.load(open(args.gpt4_result))['outputs']
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results = defaultdict(lambda: 0)
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sqa_results = {}
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sqa_results['acc'] = None
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sqa_results['correct'] = None
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sqa_results['count'] = None
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sqa_results['results'] = {}
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sqa_results['outputs'] = {}
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for prob_id, prob in split_problems.items():
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if prob_id not in our_predictions:
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assert False
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if prob_id not in gpt4_predictions:
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assert False
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our_pred = our_predictions[prob_id]['text']
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gpt4_pred = gpt4_predictions[prob_id]
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if prob_id not in requery_predictions:
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results['missing_requery'] += 1
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requery_pred = "MISSING"
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else:
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requery_pred = requery_predictions[prob_id]['text']
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pattern = re.compile(r'The answer is ([A-Z]).')
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our_res = pattern.findall(our_pred)
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if len(our_res) == 1:
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our_answer = our_res[0] # 'A', 'B', ...
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else:
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our_answer = "FAILED"
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requery_res = pattern.findall(requery_pred)
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if len(requery_res) == 1:
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requery_answer = requery_res[0] # 'A', 'B', ...
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else:
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requery_answer = "FAILED"
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gpt4_res = pattern.findall(gpt4_pred)
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if len(gpt4_res) == 1:
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gpt4_answer = gpt4_res[0] # 'A', 'B', ...
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else:
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gpt4_answer = "FAILED"
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our_pred_idx = get_pred_idx(our_answer, prob['choices'], args.options)
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gpt4_pred_idx = get_pred_idx(gpt4_answer, prob['choices'], args.options)
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requery_pred_idx = get_pred_idx(requery_answer, prob['choices'], args.options)
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results['total'] += 1
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if gpt4_answer == 'FAILED':
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results['gpt4_failed'] += 1
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if gpt4_pred_idx == prob['answer']:
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results['gpt4_correct'] += 1
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if our_pred_idx == prob['answer']:
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results['gpt4_ourvisual_correct'] += 1
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elif gpt4_pred_idx == prob['answer']:
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results['gpt4_correct'] += 1
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results['gpt4_ourvisual_correct'] += 1
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if our_pred_idx == prob['answer']:
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results['our_correct'] += 1
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if requery_answer == 'FAILED':
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sqa_results['results'][prob_id] = our_pred_idx
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if our_pred_idx == prob['answer']:
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results['requery_correct'] += 1
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else:
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sqa_results['results'][prob_id] = requery_pred_idx
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if requery_pred_idx == prob['answer']:
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results['requery_correct'] += 1
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else:
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print(f"""
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Question ({args.options[prob['answer']]}): {our_predictions[prob_id]['prompt']}
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Our ({our_answer}): {our_pred}
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GPT-4 ({gpt4_answer}): {gpt4_pred}
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Requery ({requery_answer}): {requery_pred}
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print("=====================================")
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""")
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if gpt4_pred_idx == prob['answer'] or our_pred_idx == prob['answer']:
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results['correct_upperbound'] += 1
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total = results['total']
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print(f'Total: {total}, Our-Correct: {results["our_correct"]}, Accuracy: {results["our_correct"] / total * 100:.2f}%')
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print(f'Total: {total}, GPT-4-Correct: {results["gpt4_correct"]}, Accuracy: {results["gpt4_correct"] / total * 100:.2f}%')
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print(f'Total: {total}, GPT-4 NO-ANS (RANDOM): {results["gpt4_failed"]}, Percentage: {results["gpt4_failed"] / total * 100:.2f}%')
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print(f'Total: {total}, GPT-4-OursVisual-Correct: {results["gpt4_ourvisual_correct"]}, Accuracy: {results["gpt4_ourvisual_correct"] / total * 100:.2f}%')
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print(f'Total: {total}, Requery-Correct: {results["requery_correct"]}, Accuracy: {results["requery_correct"] / total * 100:.2f}%')
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print(f'Total: {total}, Correct upper: {results["correct_upperbound"]}, Accuracy: {results["correct_upperbound"] / total * 100:.2f}%')
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sqa_results['acc'] = results["requery_correct"] / total * 100
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sqa_results['correct'] = results["requery_correct"]
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sqa_results['count'] = total
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with open(args.output_result, 'w') as f:
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json.dump(sqa_results, f, indent=2)
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