snnetv2-semantic-segmentation / configs /fastfcn /fastfcn_r50-d32_jpu_enc_4xb4-160k_ade20k-512x512.py
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# model settings
_base_ = './fastfcn_r50-d32_jpu_psp_4xb4-160k_ade20k-512x512.py'
norm_cfg = dict(type='SyncBN', requires_grad=True)
model = dict(
decode_head=dict(
_delete_=True,
type='EncHead',
in_channels=[512, 1024, 2048],
in_index=(0, 1, 2),
channels=512,
num_codes=32,
use_se_loss=True,
add_lateral=False,
dropout_ratio=0.1,
num_classes=150,
norm_cfg=norm_cfg,
align_corners=False,
loss_decode=dict(
type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0),
loss_se_decode=dict(
type='CrossEntropyLoss', use_sigmoid=True, loss_weight=0.2)),
# model training and testing settings
train_cfg=dict(),
test_cfg=dict(mode='whole'))