def write_evaluation_json()

in scripts/adapet/ADAPET/utilcode.py [0:0]

• 47 lines of code
• 6 McCabe index (conditional complexity)

def write_evaluation_json(accs, mics, macs, avg_pres, logit_aps, num_labs, sample_size, task_name, configs, english, prompt):
    if sample_size in ["full", 500]:
        assert len(accs) == len(mics) == len(macs) == len(avg_pres) == len(logit_aps) == len(ADAPET_SEEDS)
    else:
        assert len(accs) == len(mics) == len(macs) == len(avg_pres) == len(logit_aps) == len(SEEDS)
    
    round_to = 10
    mean_acc = round(np.mean(accs), round_to)
    acc_std = round(np.std(accs), round_to)

    mean_micro = round(np.mean(mics), round_to)
    micro_std = round(np.std(mics), round_to)

    mean_macro = round(np.mean(macs), round_to)
    macro_std = round(np.std(macs), round_to)
    
    mean_avg_pre = round(np.mean(avg_pres), round_to)
    avg_pre_std = round(np.std(avg_pres), round_to)
    
    mean_logit_ap = round(np.mean(logit_aps), round_to)
    logit_ap_std = round(np.std(logit_aps), round_to)
    
    #in the multiclass scenario, average precision is not defined
    if num_labs > 2:
        mean_avg_pre = 'NA'
        avg_pre_std = 'NA' 
        mean_logit_ap = 'NA'
        logit_ap_std = 'NA'

    json_dict = {
        "mean_acc": mean_acc,
        "acc_std": acc_std,
        "mean_f1_mic": mean_micro,
        "f1_mic_std": micro_std,
        "mean_f1_mac": mean_macro,
        "f1_mac_std": macro_std,
        "mean_avg_pre": mean_avg_pre,
        "avg_pre_std": avg_pre_std,
        "mean_logit_ap": mean_logit_ap,
        "logit_ap_std": logit_ap_std,
    }
    write_dir = 'results/'+ configs["pretrained_weight"] + '/' + task_name.lower()[7:]
    
    if english:
        write_dir = write_dir + '_eng'
    else:
        write_dir = write_dir + '_lang'
    if prompt:
        write_dir = write_dir + '_prompt'
    else:
        write_dir = write_dir + '_no_prompt'

    if not os.path.exists(write_dir):
        os.makedirs(write_dir)
    writefile = write_dir + "/" + str(sample_size) + "_split_results.json"
    with open(writefile, "w") as f:
        f.write(json.dumps(json_dict) + "\n")