'''upernet_swintiny_ade20k'''
import os
import copy
from .base_cfg import SEGMENTOR_CFG
from .._base_ import DATASET_CFG_ADE20k_512x512, DATALOADER_CFG_BS16


# deepcopy
SEGMENTOR_CFG = copy.deepcopy(SEGMENTOR_CFG)
# modify dataset config
SEGMENTOR_CFG['dataset'] = DATASET_CFG_ADE20k_512x512.copy()
# modify dataloader config
SEGMENTOR_CFG['dataloader'] = DATALOADER_CFG_BS16.copy()
# modify scheduler config
SEGMENTOR_CFG['scheduler']['max_epochs'] = 130
SEGMENTOR_CFG['scheduler']['min_lr'] = 0.0
SEGMENTOR_CFG['scheduler']['power'] = 1.0
SEGMENTOR_CFG['scheduler']['warmup_cfg'] = {'type': 'linear', 'ratio': 1e-6, 'iters': 1500}
# modify other segmentor configs
SEGMENTOR_CFG['num_classes'] = 150
SEGMENTOR_CFG['backbone'] = {
    'type': 'SwinTransformer', 'structure_type': 'swin_tiny_patch4_window7_224', 'pretrained': True, 
    'selected_indices': (0, 1, 2, 3), 'norm_cfg': {'type': 'LayerNorm'},
    'pretrain_img_size': 224, 'in_channels': 3, 'embed_dims': 96, 'patch_size': 4, 'window_size': 7, 'mlp_ratio': 4, 
    'depths': [2, 2, 6, 2], 'num_heads': [3, 6, 12, 24], 'qkv_bias': True, 'qk_scale': None, 'patch_norm': True, 
    'drop_rate': 0., 'attn_drop_rate': 0., 'drop_path_rate': 0.3, 'use_abs_pos_embed': False,
}
SEGMENTOR_CFG['head'] = {
    'in_channels_list': [96, 192, 384, 768], 'feats_channels': 512, 'pool_scales': [1, 2, 3, 6], 'dropout': 0.1,
}
SEGMENTOR_CFG['auxiliary'] = {
    'in_channels': 384, 'out_channels': 512, 'dropout': 0.1,
}
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")