# Obtained from: https://github.com/NVlabs/SegFormer
# Modifications: BN instead of SyncBN

# model settings
norm_cfg = dict(type='SyncBN', requires_grad=True)
find_unused_parameters = True
model = dict(
    type='EncoderDecoder',
    pretrained=None,
    backbone=dict(type='IMTRv21_5', style='pytorch'),
    decode_head=dict(type='SegFormerHead',
                     in_channels=[64, 128, 320, 512],
                     in_index=[0, 1, 2, 3],
                     channels=128,
                     dropout_ratio=0.1,
                     num_classes=9,
                     norm_cfg=norm_cfg,
                     align_corners=False,
                     decoder_params=dict(),
                     loss_decode=dict(type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
    # model training and testing settings
    train_cfg=dict(),
    test_cfg=dict(mode='whole'))
