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segnext_s.yaml
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segnext_s.yaml
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model:
class_path: otx.algo.segmentation.segnext.OTXSegNext
init_args:
label_info: 2
name_base_model: SegNextS
criterion_configuration:
- type: CrossEntropyLoss
params:
ignore_index: 255
backbone_configuration:
act_cfg:
type: GELU
attention_kernel_paddings:
- 2
- - 0
- 3
- - 0
- 5
- - 0
- 10
attention_kernel_sizes:
- 5
- - 1
- 7
- - 1
- 11
- - 1
- 21
depths:
- 2
- 2
- 4
- 2
drop_path_rate: 0.1
drop_rate: 0.0
embed_dims:
- 64
- 128
- 320
- 512
mlp_ratios:
- 8
- 8
- 4
- 4
norm_cfg:
requires_grad: true
type: BN
pretrained_weights: https://download.openmmlab.com/mmsegmentation/v0.5/pretrain/segnext/mscan_s_20230227-f33ccdf2.pth
decode_head_configuration:
norm_cfg:
num_groups: 32
requires_grad: true
type: GN
ham_kwargs:
md_r: 16
md_s: 1
eval_steps: 7
rand_init: true
train_steps: 6
in_channels:
- 128
- 320
- 512
in_index:
- 1
- 2
- 3
align_corners: false
channels: 256
dropout_ratio: 0.1
ham_channels: 256
optimizer:
class_path: torch.optim.AdamW
init_args:
lr: 0.00006
betas:
- 0.9
- 0.999
weight_decay: 0.01
scheduler:
class_path: otx.core.schedulers.LinearWarmupSchedulerCallable
init_args:
num_warmup_steps: 20
main_scheduler_callable:
class_path: torch.optim.lr_scheduler.PolynomialLR
init_args:
total_iters: 100
power: 0.9
last_epoch: -1
engine:
task: SEMANTIC_SEGMENTATION
device: auto
callback_monitor: val/Dice
overrides:
callbacks:
- class_path: otx.algo.callbacks.adaptive_early_stopping.EarlyStoppingWithWarmup
init_args:
warmup_iters: 100
data: ../_base_/data/mmseg_base.yaml