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import json |
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from math import sqrt |
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import re |
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from nltk.translate.bleu_score import sentence_bleu |
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gold_fn = 'test.json' |
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pred_fn = 'llava-v1.5-13b.json' |
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gold = json.load(open(gold_fn)) |
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pred = json.load(open(pred_fn)) |
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sequence_match = 0 |
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action_score = 0 |
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total_click_penalty = 0 |
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total_press_penalty = 0 |
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total_write_penalty = 0 |
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ideal_score = 0 |
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max_click_penalty = 0 |
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max_press_penalty = 0 |
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max_write_penalty = 0 |
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def get_bounds(box: dict(), cx, cy): |
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for i in box: |
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tl = box[i]["top_left"] |
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br = box[i]["bottom_right"] |
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if (tl[0]+br[0])/2 == cx and (tl[1]+br[1])/2 == cy: |
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return (tl,br) |
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assert False |
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def dynamic_dirichlet_l2_penalty(tl, br, px, py): |
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len_x = br[0] - tl[0] |
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len_y = br[1] - tl[1] |
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cx = ( br[0] - tl[0] ) / 2 |
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cy = ( br[1] - tl[1] ) / 2 |
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dx = abs(cx - px) - (len_x * 0.5) |
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dy = abs(cy - py) - (len_y * 0.5) |
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dist = sqrt((dx * (dx > 0)) ** 2 + (dy * (dy > 0)) ** 2) |
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mu = sqrt( len_x ** 2 + len_y ** 2) |
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score = mu / (dist+mu) |
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penalty = 1 - score |
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return penalty |
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for idx in gold: |
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gold_script = open(gold[idx]['task']).read().strip().split('\n')[2:] |
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llm_script = pred[idx].strip().split() |
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llm_script = [x for x in llm_script if x.strip().startswith('pyautogui')] |
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sample_weight = (len(gold_script)-0.9) |
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ideal_score += sample_weight |
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for gold_line in gold_script: |
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action_type = gold_line.split("pyautogui.")[1].split("(")[0] |
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if action_type == 'click' or action_type == 'rightClick' or action_type == 'moveTo' or action_type == 'dragTo': |
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max_click_penalty += sample_weight/len(gold_script) |
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if action_type == 'press' or action_type == 'hotkey': |
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max_press_penalty += sample_weight/len(gold_script) |
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if action_type == 'write': |
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max_write_penalty += sample_weight/len(gold_script) |
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seq_match_flag = 1 |
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click_penalty = 0 |
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press_penalty = 0 |
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write_penalty = 0 |
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if len(llm_script) != len(gold_script): |
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seq_match_flag = 0 |
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if seq_match_flag == 1: |
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for i in range(len(gold_script)): |
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gold_line = gold_script[i].strip() |
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gold_action = gold_line.split('pyautogui.')[1].split('(')[0] |
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pred_line = llm_script[i] |
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if pred_line.startswith('pyautogui.') == False: |
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seq_match_flag = 0 |
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break |
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pred_action = pred_line.split('pyautogui.')[1].split('(')[0] |
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if pred_action != gold_action: |
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seq_match_flag = 0 |
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break |
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box_path = gold[idx]['box'] |
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box_num = box_path.split("_")[-1].split(".json")[0] |
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box_path = "_".join(box_path.split("_")[:-1])+box_num+"_boxes.json" |
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box = json.load(open(box_path)) |
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for i in range(len(gold_script)): |
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gold_line = gold_script[i].strip() |
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gold_action = gold_line.split('pyautogui.')[1].split('(')[0] |
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if seq_match_flag == 0: |
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if gold_action == 'click' or gold_action == 'rightClick' or gold_action == 'moveTo' or gold_action == 'dragTo': |
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click_penalty += 1/len(gold_script) |
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if gold_action == 'press' or gold_action == 'hotkey': |
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press_penalty += 1/len(gold_script) |
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if gold_action == 'write': |
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write_penalty += 1/len(gold_script) |
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continue |
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pred_line = llm_script[i] |
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pred_action = pred_line.split('pyautogui.')[1].split('(')[0] |
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if gold_action == 'click' or gold == 'rightClick': |
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gold_cx = gold_line.split("pyautogui.")[1].split('(')[1].split(',')[0] |
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gold_cy = gold_line.split("pyautogui.")[1].split('(')[1].split(',')[1].split(')')[0] |
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tl, br = get_bounds(box, float(gold_cx), float(gold_cy)) |
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pred_cx = gold_line.split("pyautogui.")[1].split('(')[1].split(',')[0] |
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pred_cy = gold_line.split("pyautogui.")[1].split('(')[1].split(',')[1].split(')')[0] |
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click_penalty += (1.0/len(gold_script)) * dynamic_dirichlet_l2_penalty(tl, br, float(pred_cx), float(pred_cy)) |
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if gold_action == 'press': |
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gold_key = gold_line.split("\"")[1] |
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pred_key = (re.split("\"|'", pred_line))[1] |
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if gold_key.strip() != pred_key.strip(): |
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press_penalty += 1/len(gold_script) |
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if gold_action == 'hotkey': |
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gold_keys = gold_line.split("(")[1].split(")")[0].split(",") |
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pred_keys = pred_line.split("(")[1].split(")")[0].split(",") |
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gold_key_set = set([x[1:-1] for x in gold_keys if len(x)>2]) |
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pred_key_set = set([x[1:-1] for x in pred_keys if len(x)>2]) |
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if gold_key_set != pred_key_set: |
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press_penalty += 1/len(gold_script) |
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if gold_action == 'write': |
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reference = [gold_line.split("\"")[1]] |
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candidate = re.split("\"|'", pred_line)[1] |
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write_penalty += (1-sentence_bleu(reference, candidate, weights=(0.5, 0.5))) / len(gold_script) |
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sequence_match += (seq_match_flag) * sample_weight |
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action_score += (max(seq_match_flag - click_penalty - press_penalty - write_penalty, 0)) * sample_weight |
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if seq_match_flag: |
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total_click_penalty += click_penalty * sample_weight |
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total_press_penalty += press_penalty * sample_weight |
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total_write_penalty += write_penalty * sample_weight |
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print(ideal_score) |
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print(f"Sequence match: {sequence_match/ideal_score}") |
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print(f"Action match: {action_score/ideal_score}") |
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print(total_click_penalty/ideal_score) |
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print(total_press_penalty/ideal_score) |
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print(total_write_penalty/ideal_score) |
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