def validate_case_matches_checkpoint(do_lower_case, init_checkpoint):
    'Checks whether the casing config is consistent with the checkpoint name.'
    if (not init_checkpoint):
        return
    m = re.match('^.*?([A-Za-z0-9_-]+)/bert_model.ckpt', init_checkpoint)
    if (m is None):
        return
    model_name = m.group(1)
    lower_models = ['uncased_L-24_H-1024_A-16', 'uncased_L-12_H-768_A-12', 'multilingual_L-12_H-768_A-12', 'chinese_L-12_H-768_A-12']
    cased_models = ['cased_L-12_H-768_A-12', 'cased_L-24_H-1024_A-16', 'multi_cased_L-12_H-768_A-12']
    is_bad_config = False
    if ((model_name in lower_models) and (not do_lower_case)):
        is_bad_config = True
        actual_flag = 'False'
        case_name = 'lowercased'
        opposite_flag = 'True'
    if ((model_name in cased_models) and do_lower_case):
        is_bad_config = True
        actual_flag = 'True'
        case_name = 'cased'
        opposite_flag = 'False'
    if is_bad_config:
        raise ValueError(('You passed in `--do_lower_case=%s` with `--init_checkpoint=%s`. However, `%s` seems to be a %s model, so you should pass in `--do_lower_case=%s` so that the fine-tuning matches how the model was pre-training. If this error is wrong, please just comment out this check.' % (actual_flag, init_checkpoint, model_name, case_name, opposite_flag)))
Checks whether the casing config is consistent with the checkpoint name.
def validate_case_matches_checkpoint(do_lower_case, init_checkpoint):
    
    if (not init_checkpoint):
        return
    m = re.match('^.*?([A-Za-z0-9_-]+)/bert_model.ckpt', init_checkpoint)
    if (m is None):
        return
    model_name = m.group(1)
    lower_models = ['uncased_L-24_H-1024_A-16', 'uncased_L-12_H-768_A-12', 'multilingual_L-12_H-768_A-12', 'chinese_L-12_H-768_A-12']
    cased_models = ['cased_L-12_H-768_A-12', 'cased_L-24_H-1024_A-16', 'multi_cased_L-12_H-768_A-12']
    is_bad_config = False
    if ((model_name in lower_models) and (not do_lower_case)):
        is_bad_config = True
        actual_flag = 'False'
        case_name = 'lowercased'
        opposite_flag = 'True'
    if ((model_name in cased_models) and do_lower_case):
        is_bad_config = True
        actual_flag = 'True'
        case_name = 'cased'
        opposite_flag = 'False'
    if is_bad_config:
        raise ValueError(('You passed in `--do_lower_case=%s` with `--init_checkpoint=%s`. However, `%s` seems to be a %s model, so you should pass in `--do_lower_case=%s` so that the fine-tuning matches how the model was pre-training. If this error is wrong, please just comment out this check.' % (actual_flag, init_checkpoint, model_name, case_name, opposite_flag)))