'''mcibi_deeplabv3_resnet101os8_lip'''
import os
from .._base_ import REGISTERED_SEGMENTOR_CONFIGS, REGISTERED_DATASET_CONFIGS, REGISTERED_DATALOADER_CONFIGS


# deepcopy
SEGMENTOR_CFG = REGISTERED_SEGMENTOR_CONFIGS['MCIBI_SEGMENTOR_CFG'].copy()
# modify dataset config
SEGMENTOR_CFG['dataset'] = REGISTERED_DATASET_CONFIGS['DATASET_CFG_LIP_473x473'].copy()
# modify dataloader config
SEGMENTOR_CFG['dataloader'] = REGISTERED_DATALOADER_CONFIGS['DATALOADER_CFG_BS32'].copy()
# modify scheduler config
SEGMENTOR_CFG['scheduler']['max_epochs'] = 150
# modify other segmentor configs
SEGMENTOR_CFG['num_classes'] = 20
SEGMENTOR_CFG['act_cfg'] = {'type': 'LeakyReLU', 'negative_slope': 0.01, 'inplace': True}
SEGMENTOR_CFG['head']['use_loss'] = False
SEGMENTOR_CFG['work_dir'] = os.path.split(__file__)[-1].split('.')[0]
SEGMENTOR_CFG['logger_handle_cfg']['logfilepath'] = os.path.join(SEGMENTOR_CFG['work_dir'], f"{os.path.split(__file__)[-1].split('.')[0]}.log")


# modify inference config
# --single-scale
SEGMENTOR_CFG['inference'] = SEGMENTOR_CFG['inference'].copy()
# --single-scale with flipping
'''
SEGMENTOR_CFG['inference'] = {
    'forward': {'mode': 'whole', 'cropsize': None, 'stride': None},
    'tta': {'multiscale': [1], 'flip': True, 'use_probs_before_resize': False},
    'evaluate': {'metric_list': ['iou', 'miou']},
}
'''