def write_seed_output()

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

• 29 lines of code
• 9 McCabe index (conditional complexity)

def write_seed_output(pretrained_weight, task_name, sample_size, ds_seed, metric, english, prompt):
    dataset = task_name[7:] #remove setfit/
    if dataset in ["toxic_conversations"]:
        json_dict = {"measure": "ap", "score": metric}
    
    elif dataset in ["amazon_counterfactual_en"]:
        json_dict = {"measure": "matthews_correlation", "score": metric}
    
    elif 'SetFit/' + dataset in AMZ_MULTI_LING:
        json_dict = {"measure": "mean_absolute_error", "score": metric}        
    
    else:
        json_dict = {"measure": "acc", "score": metric}
    
    if 'microsoft/' in pretrained_weight:
        pretrained_weight = pretrained_weight.replace('microsoft/', '')
    
    if task_name in SINGLE_SENT_DATASETS:
        writefile = 'seed_output/' + pretrained_weight +'/'+ dataset +'/'+ 'train-'+str(sample_size)+'-'+str(ds_seed)+ '/'
    else:
        if english:
            lang = 'eng'
        else:
            lang = 'lang'
        if prompt:
            prompting = 'prompt'
        else:
            prompting = 'no-prompt'
        writefile = 'seed_output/' + pretrained_weight + "__"+lang+'_'+prompting +'/'+ dataset +'/'+ 'train-'+str(sample_size)+'-'+str(ds_seed)+ '/'
    if not os.path.exists(writefile):
        os.makedirs(writefile)
    writefile = writefile+'results.json'
    with open(writefile, "a") as f:
        f.write(json.dumps(json_dict))