diff --git "a/Segmentation_Models/231029_1622_gengta2cs_daformer_s0_49f77/20231029_162300.log" "b/Segmentation_Models/231029_1622_gengta2cs_daformer_s0_49f77/20231029_162300.log"
new file mode 100644--- /dev/null
+++ "b/Segmentation_Models/231029_1622_gengta2cs_daformer_s0_49f77/20231029_162300.log"
@@ -0,0 +1,3755 @@
+2023-10-29 16:23:02,280 - mmseg - INFO - Environment info:
+------------------------------------------------------------
+sys.platform: linux
+Python: 3.8.5 (default, Oct  6 2020, 10:04:29) [GCC 6.3.0]
+CUDA available: True
+GPU 0: NVIDIA TITAN RTX
+CUDA_HOME: /cluster/apps/gcc-6.3.0/cuda-11.0.3-qdlibd2luz2fy7izfefao4c5yitxwjus
+NVCC: Build cuda_11.0_bu.TC445_37.28845127_0
+GCC: gcc (GCC) 6.3.0
+PyTorch: 1.7.1+cu110
+PyTorch compiling details: PyTorch built with:
+  - GCC 7.3
+  - C++ Version: 201402
+  - Intel(R) Math Kernel Library Version 2020.0.0 Product Build 20191122 for Intel(R) 64 architecture applications
+  - Intel(R) MKL-DNN v1.6.0 (Git Hash 5ef631a030a6f73131c77892041042805a06064f)
+  - OpenMP 201511 (a.k.a. OpenMP 4.5)
+  - NNPACK is enabled
+  - CPU capability usage: AVX2
+  - CUDA Runtime 11.0
+  - NVCC architecture flags: -gencode;arch=compute_37,code=sm_37;-gencode;arch=compute_50,code=sm_50;-gencode;arch=compute_60,code=sm_60;-gencode;arch=compute_70,code=sm_70;-gencode;arch=compute_75,code=sm_75;-gencode;arch=compute_80,code=sm_80
+  - CuDNN 8.0.5
+  - Magma 2.5.2
+  - Build settings: BLAS=MKL, BUILD_TYPE=Release, CXX_FLAGS= -Wno-deprecated -fvisibility-inlines-hidden -DUSE_PTHREADPOOL -fopenmp -DNDEBUG -DUSE_FBGEMM -DUSE_QNNPACK -DUSE_PYTORCH_QNNPACK -DUSE_XNNPACK -DUSE_VULKAN_WRAPPER -O2 -fPIC -Wno-narrowing -Wall -Wextra -Werror=return-type -Wno-missing-field-initializers -Wno-type-limits -Wno-array-bounds -Wno-unknown-pragmas -Wno-sign-compare -Wno-unused-parameter -Wno-unused-variable -Wno-unused-function -Wno-unused-result -Wno-unused-local-typedefs -Wno-strict-overflow -Wno-strict-aliasing -Wno-error=deprecated-declarations -Wno-stringop-overflow -Wno-psabi -Wno-error=pedantic -Wno-error=redundant-decls -Wno-error=old-style-cast -fdiagnostics-color=always -faligned-new -Wno-unused-but-set-variable -Wno-maybe-uninitialized -fno-math-errno -fno-trapping-math -Werror=format -Wno-stringop-overflow, PERF_WITH_AVX=1, PERF_WITH_AVX2=1, PERF_WITH_AVX512=1, USE_CUDA=ON, USE_EXCEPTION_PTR=1, USE_GFLAGS=OFF, USE_GLOG=OFF, USE_MKL=ON, USE_MKLDNN=ON, USE_MPI=OFF, USE_NCCL=ON, USE_NNPACK=ON, USE_OPENMP=ON, 
+
+TorchVision: 0.8.2+cu110
+OpenCV: 4.4.0
+MMCV: 1.3.7
+MMCV Compiler: GCC 6.3
+MMCV CUDA Compiler: 11.0
+MMSegmentation: 0.16.0+8eb19e7
+------------------------------------------------------------
+
+2023-10-29 16:23:02,283 - mmseg - INFO - Distributed training: False
+2023-10-29 16:23:03,351 - mmseg - INFO - Config:
+log_config = dict(
+    interval=50, hooks=[dict(type='TextLoggerHook', by_epoch=False)])
+dist_params = dict(backend='nccl')
+log_level = 'INFO'
+load_from = None
+resume_from = None
+workflow = [('train', 1)]
+cudnn_benchmark = True
+norm_cfg = dict(type='BN', requires_grad=True)
+find_unused_parameters = True
+model = dict(
+    type='EncoderDecoder',
+    pretrained='pretrained/mit_b5.pth',
+    backbone=dict(type='mit_b5', style='pytorch'),
+    decode_head=dict(
+        type='DAFormerHead',
+        in_channels=[64, 128, 320, 512],
+        in_index=[0, 1, 2, 3],
+        channels=256,
+        dropout_ratio=0.1,
+        num_classes=19,
+        norm_cfg=dict(type='BN', requires_grad=True),
+        align_corners=False,
+        decoder_params=dict(
+            embed_dims=256,
+            embed_cfg=dict(type='mlp', act_cfg=None, norm_cfg=None),
+            embed_neck_cfg=dict(type='mlp', act_cfg=None, norm_cfg=None),
+            fusion_cfg=dict(
+                type='aspp',
+                sep=True,
+                dilations=(1, 6, 12, 18),
+                pool=False,
+                act_cfg=dict(type='ReLU'),
+                norm_cfg=dict(type='BN', requires_grad=True))),
+        loss_decode=dict(
+            type='CrossEntropyLoss', use_sigmoid=False, loss_weight=1.0)),
+    train_cfg=dict(
+        work_dir=
+        'work_dirs/local-exp523/231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77'
+    ),
+    test_cfg=dict(
+        mode='slide',
+        batched_slide=True,
+        stride=[256, 256],
+        crop_size=[512, 512]))
+dataset_type = 'CityscapesDataset'
+data_root = 'data/cityscapes/'
+img_norm_cfg = dict(
+    mean=[123.675, 116.28, 103.53], std=[58.395, 57.12, 57.375], to_rgb=True)
+crop_size = (512, 512)
+gen_train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations'),
+    dict(type='RandomFlip', prob=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(
+        type='Normalize',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+]
+gta_train_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(type='LoadAnnotations'),
+    dict(type='Resize', img_scale=(1280, 720)),
+    dict(type='RandomCrop', crop_size=(512, 512), cat_max_ratio=0.75),
+    dict(type='RandomFlip', prob=0.5),
+    dict(type='PhotoMetricDistortion'),
+    dict(
+        type='Normalize',
+        mean=[123.675, 116.28, 103.53],
+        std=[58.395, 57.12, 57.375],
+        to_rgb=True),
+    dict(type='Pad', size=(512, 512), pad_val=0, seg_pad_val=255),
+    dict(type='DefaultFormatBundle'),
+    dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+]
+test_pipeline = [
+    dict(type='LoadImageFromFile'),
+    dict(
+        type='MultiScaleFlipAug',
+        img_scale=(1024, 512),
+        flip=False,
+        transforms=[
+            dict(type='Resize', keep_ratio=True),
+            dict(type='RandomFlip'),
+            dict(
+                type='Normalize',
+                mean=[123.675, 116.28, 103.53],
+                std=[58.395, 57.12, 57.375],
+                to_rgb=True),
+            dict(type='ImageToTensor', keys=['img']),
+            dict(type='Collect', keys=['img'])
+        ])
+]
+data = dict(
+    samples_per_gpu=2,
+    workers_per_gpu=1,
+    train=dict(
+        type='DGDataset',
+        source2=dict(
+            type='GTADataset',
+            data_root='data/gen1/',
+            img_dir='images',
+            ann_dir='labels',
+            pipeline=[
+                dict(type='LoadImageFromFile'),
+                dict(type='LoadAnnotations'),
+                dict(type='RandomFlip', prob=0.5),
+                dict(type='PhotoMetricDistortion'),
+                dict(
+                    type='Normalize',
+                    mean=[123.675, 116.28, 103.53],
+                    std=[58.395, 57.12, 57.375],
+                    to_rgb=True),
+                dict(type='DefaultFormatBundle'),
+                dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+            ]),
+        source=dict(
+            type='GTADataset',
+            data_root='data/dg/rcs1e-2_gta6000/',
+            img_dir='images',
+            ann_dir='labels',
+            pipeline=[
+                dict(type='LoadImageFromFile'),
+                dict(type='LoadAnnotations'),
+                dict(type='Resize', img_scale=(1280, 720)),
+                dict(
+                    type='RandomCrop',
+                    crop_size=(512, 512),
+                    cat_max_ratio=0.75),
+                dict(type='RandomFlip', prob=0.5),
+                dict(type='PhotoMetricDistortion'),
+                dict(
+                    type='Normalize',
+                    mean=[123.675, 116.28, 103.53],
+                    std=[58.395, 57.12, 57.375],
+                    to_rgb=True),
+                dict(type='Pad', size=(512, 512), pad_val=0, seg_pad_val=255),
+                dict(type='DefaultFormatBundle'),
+                dict(type='Collect', keys=['img', 'gt_semantic_seg'])
+            ])),
+    val=dict(
+        type='CityscapesDataset',
+        data_root='data/cityscapes/',
+        img_dir='leftImg8bit/val',
+        ann_dir='gtFine/val',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(
+                type='MultiScaleFlipAug',
+                img_scale=(1024, 512),
+                flip=False,
+                transforms=[
+                    dict(type='Resize', keep_ratio=True),
+                    dict(type='RandomFlip'),
+                    dict(
+                        type='Normalize',
+                        mean=[123.675, 116.28, 103.53],
+                        std=[58.395, 57.12, 57.375],
+                        to_rgb=True),
+                    dict(type='ImageToTensor', keys=['img']),
+                    dict(type='Collect', keys=['img'])
+                ])
+        ]),
+    test=dict(
+        type='CityscapesDataset',
+        data_root='data/cityscapes/',
+        img_dir='leftImg8bit/val',
+        ann_dir='gtFine/val',
+        pipeline=[
+            dict(type='LoadImageFromFile'),
+            dict(
+                type='MultiScaleFlipAug',
+                img_scale=(1024, 512),
+                flip=False,
+                transforms=[
+                    dict(type='Resize', keep_ratio=True),
+                    dict(type='RandomFlip'),
+                    dict(
+                        type='Normalize',
+                        mean=[123.675, 116.28, 103.53],
+                        std=[58.395, 57.12, 57.375],
+                        to_rgb=True),
+                    dict(type='ImageToTensor', keys=['img']),
+                    dict(type='Collect', keys=['img'])
+                ])
+        ]))
+uda = dict(
+    type='DACS',
+    source_only=True,
+    alpha=0.99,
+    pseudo_threshold=0.968,
+    pseudo_weight_ignore_top=0,
+    pseudo_weight_ignore_bottom=0,
+    share_src_backward=False,
+    imnet_feature_dist_lambda=0.005,
+    imnet_feature_dist_classes=[6, 7, 11, 12, 13, 14, 15, 16, 17, 18],
+    imnet_feature_dist_scale_min_ratio=0.75,
+    mix='class',
+    blur=True,
+    color_jitter_strength=0.2,
+    color_jitter_probability=0.2,
+    style_consistency_lambda=0,
+    svmin_lambda=0,
+    svmin_scale_ratio=(0.8, 1.2),
+    svmin_domain='mixed',
+    debug_img_interval=1000,
+    print_grad_magnitude=False,
+    imnet_feature_dist_scale_method='ratio')
+use_ddp_wrapper = True
+optimizer = dict(
+    type='AdamW',
+    lr=6e-05,
+    betas=(0.9, 0.999),
+    weight_decay=0.01,
+    paramwise_cfg=dict(
+        custom_keys=dict(
+            head=dict(lr_mult=10.0),
+            pos_block=dict(decay_mult=0.0),
+            norm=dict(decay_mult=0.0))))
+optimizer_config = None
+lr_config = dict(
+    policy='poly',
+    warmup='linear',
+    warmup_iters=1500,
+    warmup_ratio=1e-06,
+    power=1.0,
+    min_lr=0.0,
+    by_epoch=False)
+gpu_model = 'NVIDIAGeForceRTX2080Ti'
+n_gpus = 1
+seed = 0
+runner = dict(type='IterBasedRunner', max_iters=40000)
+checkpoint_config = dict(by_epoch=False, interval=40000, max_keep_ckpts=1)
+evaluation = dict(interval=40000, metric='mIoU')
+name = '231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77'
+exp = 523
+name_dataset = 'gengta3mix2cityscapes'
+name_architecture = 'daformer_sepaspp_sl_mitb5'
+name_encoder = 'mitb5'
+name_decoder = 'daformer_sepaspp_sl'
+name_uda = 'dgdacs_fdthings_srconly'
+name_opt = 'adamw_6e-05_pmTrue_poly10warm_1x2_40k'
+work_dir = 'work_dirs/local-exp523/231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77'
+git_rev = '8eb19e7d4501b621afe5f4f10d44d1df1f151ba8'
+gpu_ids = range(0, 1)
+
+2023-10-29 16:23:03,352 - mmseg - INFO - Set random seed to 0, deterministic: None
+2023-10-29 16:23:04,663 - mmseg - INFO - Load mit checkpoint.
+2023-10-29 16:23:04,663 - mmseg - INFO - Use load_from_local loader
+2023-10-29 16:23:05,214 - mmseg - INFO - Load mit checkpoint.
+2023-10-29 16:23:05,215 - mmseg - INFO - Use load_from_local loader
+2023-10-29 16:23:05,583 - mmseg - INFO - DACS(
+  (model): EncoderDecoder(
+    (backbone): mit_b5(
+      (patch_embed1): OverlapPatchEmbed(
+        (proj): Conv2d(3, 64, kernel_size=(7, 7), stride=(4, 4), padding=(3, 3))
+        (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed2): OverlapPatchEmbed(
+        (proj): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed3): OverlapPatchEmbed(
+        (proj): Conv2d(128, 320, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed4): OverlapPatchEmbed(
+        (proj): Conv2d(320, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+      )
+      (block1): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): Identity()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+      (block2): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (3): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (4): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (5): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+      (block3): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (3): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (4): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (5): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (6): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (7): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (8): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (9): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (10): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (11): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (12): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (13): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (14): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (15): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (16): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (17): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (18): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (19): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (20): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (21): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (22): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (23): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (24): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (25): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (26): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (27): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (28): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (29): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (30): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (31): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (32): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (33): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (34): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (35): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (36): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (37): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (38): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (39): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm3): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+      (block4): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm4): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+    )
+    (decode_head): DAFormerHead(
+      input_transform=multiple_select, ignore_index=255, align_corners=False
+      (loss_decode): CrossEntropyLoss()
+      (conv_seg): Conv2d(256, 19, kernel_size=(1, 1), stride=(1, 1))
+      (dropout): Dropout2d(p=0.1, inplace=False)
+      (embed_layers): ModuleDict(
+        (0): MLP(
+          (proj): Linear(in_features=64, out_features=256, bias=True)
+        )
+        (1): MLP(
+          (proj): Linear(in_features=128, out_features=256, bias=True)
+        )
+        (2): MLP(
+          (proj): Linear(in_features=320, out_features=256, bias=True)
+        )
+        (3): MLP(
+          (proj): Linear(in_features=512, out_features=256, bias=True)
+        )
+      )
+      (fuse_layer): ASPPWrapper(
+        (aspp_modules): DepthwiseSeparableASPPModule(
+          (0): ConvModule(
+            (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (activate): ReLU(inplace=True)
+          )
+          (1): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(6, 6), dilation=(6, 6), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+          (2): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(12, 12), dilation=(12, 12), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+          (3): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(18, 18), dilation=(18, 18), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+        )
+        (bottleneck): ConvModule(
+          (conv): Conv2d(1024, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
+          (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (activate): ReLU(inplace=True)
+        )
+      )
+    )
+    init_cfg={'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
+  )
+  (imnet_model): EncoderDecoder(
+    (backbone): mit_b5(
+      (patch_embed1): OverlapPatchEmbed(
+        (proj): Conv2d(3, 64, kernel_size=(7, 7), stride=(4, 4), padding=(3, 3))
+        (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed2): OverlapPatchEmbed(
+        (proj): Conv2d(64, 128, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed3): OverlapPatchEmbed(
+        (proj): Conv2d(128, 320, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+      )
+      (patch_embed4): OverlapPatchEmbed(
+        (proj): Conv2d(320, 512, kernel_size=(3, 3), stride=(2, 2), padding=(1, 1))
+        (norm): LayerNorm((512,), eps=1e-05, elementwise_affine=True)
+      )
+      (block1): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): Identity()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=64, out_features=64, bias=True)
+            (kv): Linear(in_features=64, out_features=128, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=64, out_features=64, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(64, 64, kernel_size=(8, 8), stride=(8, 8))
+            (norm): LayerNorm((64,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=64, out_features=256, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(256, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=256)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=256, out_features=64, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm1): LayerNorm((64,), eps=1e-06, elementwise_affine=True)
+      (block2): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (3): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (4): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (5): Block(
+          (norm1): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=128, out_features=128, bias=True)
+            (kv): Linear(in_features=128, out_features=256, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=128, out_features=128, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(128, 128, kernel_size=(4, 4), stride=(4, 4))
+            (norm): LayerNorm((128,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=128, out_features=512, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(512, 512, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=512)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=512, out_features=128, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm2): LayerNorm((128,), eps=1e-06, elementwise_affine=True)
+      (block3): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (3): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (4): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (5): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (6): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (7): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (8): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (9): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (10): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (11): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (12): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (13): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (14): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (15): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (16): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (17): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (18): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (19): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (20): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (21): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (22): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (23): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (24): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (25): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (26): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (27): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (28): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (29): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (30): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (31): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (32): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (33): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (34): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (35): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (36): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (37): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (38): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (39): Block(
+          (norm1): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=320, out_features=320, bias=True)
+            (kv): Linear(in_features=320, out_features=640, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=320, out_features=320, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+            (sr): Conv2d(320, 320, kernel_size=(2, 2), stride=(2, 2))
+            (norm): LayerNorm((320,), eps=1e-05, elementwise_affine=True)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=320, out_features=1280, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(1280, 1280, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=1280)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=1280, out_features=320, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm3): LayerNorm((320,), eps=1e-06, elementwise_affine=True)
+      (block4): ModuleList(
+        (0): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (1): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+        (2): Block(
+          (norm1): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (attn): Attention(
+            (q): Linear(in_features=512, out_features=512, bias=True)
+            (kv): Linear(in_features=512, out_features=1024, bias=True)
+            (attn_drop): Dropout(p=0.0, inplace=False)
+            (proj): Linear(in_features=512, out_features=512, bias=True)
+            (proj_drop): Dropout(p=0.0, inplace=False)
+          )
+          (drop_path): DropPath()
+          (norm2): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+          (mlp): Mlp(
+            (fc1): Linear(in_features=512, out_features=2048, bias=True)
+            (dwconv): DWConv(
+              (dwconv): Conv2d(2048, 2048, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), groups=2048)
+            )
+            (act): GELU()
+            (fc2): Linear(in_features=2048, out_features=512, bias=True)
+            (drop): Dropout(p=0.0, inplace=False)
+          )
+        )
+      )
+      (norm4): LayerNorm((512,), eps=1e-06, elementwise_affine=True)
+    )
+    (decode_head): DAFormerHead(
+      input_transform=multiple_select, ignore_index=255, align_corners=False
+      (loss_decode): CrossEntropyLoss()
+      (conv_seg): Conv2d(256, 19, kernel_size=(1, 1), stride=(1, 1))
+      (dropout): Dropout2d(p=0.1, inplace=False)
+      (embed_layers): ModuleDict(
+        (0): MLP(
+          (proj): Linear(in_features=64, out_features=256, bias=True)
+        )
+        (1): MLP(
+          (proj): Linear(in_features=128, out_features=256, bias=True)
+        )
+        (2): MLP(
+          (proj): Linear(in_features=320, out_features=256, bias=True)
+        )
+        (3): MLP(
+          (proj): Linear(in_features=512, out_features=256, bias=True)
+        )
+      )
+      (fuse_layer): ASPPWrapper(
+        (aspp_modules): DepthwiseSeparableASPPModule(
+          (0): ConvModule(
+            (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+            (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            (activate): ReLU(inplace=True)
+          )
+          (1): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(6, 6), dilation=(6, 6), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+          (2): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(12, 12), dilation=(12, 12), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+          (3): DepthwiseSeparableConvModule(
+            (depthwise_conv): ConvModule(
+              (conv): Conv2d(1024, 1024, kernel_size=(3, 3), stride=(1, 1), padding=(18, 18), dilation=(18, 18), groups=1024, bias=False)
+              (bn): BatchNorm2d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+            (pointwise_conv): ConvModule(
+              (conv): Conv2d(1024, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (activate): ReLU(inplace=True)
+            )
+          )
+        )
+        (bottleneck): ConvModule(
+          (conv): Conv2d(1024, 256, kernel_size=(3, 3), stride=(1, 1), padding=(1, 1), bias=False)
+          (bn): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (activate): ReLU(inplace=True)
+        )
+      )
+    )
+    init_cfg={'type': 'Normal', 'std': 0.01, 'override': {'name': 'conv_seg'}}
+  )
+)
+2023-10-29 16:23:05,768 - mmseg - INFO - Loaded 6000 images from data/dg/rcs1e-2_gta6000/images
+2023-10-29 16:23:05,942 - mmseg - INFO - Loaded 7000 images from data/gen1/images
+2023-10-29 16:23:18,641 - mmseg - INFO - Loaded 500 images from data/cityscapes/leftImg8bit/val
+2023-10-29 16:23:18,641 - mmseg - INFO - Start running, host: yurjia@eu-g3-068, work_dir: /cluster/scratch/yurjia/HRDA-Private/work_dirs/local-exp523/231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 16:23:18,641 - mmseg - INFO - workflow: [('train', 1)], max: 40000 iters
+2023-10-29 16:23:56,283 - mmseg - INFO - Iter [50/40000]	lr: 1.958e-06, eta: 8:20:23, time: 0.752, data_time: 0.036, memory: 9476, decode.loss_seg: 2.7758, decode.acc_seg: 5.7579, src.loss_imnet_feat_dist: 0.0584
+2023-10-29 16:24:31,836 - mmseg - INFO - Iter [100/40000]	lr: 3.950e-06, eta: 8:06:21, time: 0.711, data_time: 0.013, memory: 9476, decode.loss_seg: 2.6202, decode.acc_seg: 36.7117, src.loss_imnet_feat_dist: nan
+2023-10-29 16:25:07,474 - mmseg - INFO - Iter [150/40000]	lr: 5.938e-06, eta: 8:01:37, time: 0.713, data_time: 0.013, memory: 9476, decode.loss_seg: 2.2754, decode.acc_seg: 53.1605, src.loss_imnet_feat_dist: nan
+2023-10-29 16:25:43,166 - mmseg - INFO - Iter [200/40000]	lr: 7.920e-06, eta: 7:59:08, time: 0.714, data_time: 0.013, memory: 9476, decode.loss_seg: 1.9237, decode.acc_seg: 55.8836, src.loss_imnet_feat_dist: nan
+2023-10-29 16:26:19,155 - mmseg - INFO - Iter [250/40000]	lr: 9.898e-06, eta: 7:58:12, time: 0.720, data_time: 0.017, memory: 9476, decode.loss_seg: 1.5847, decode.acc_seg: 62.2218, src.loss_imnet_feat_dist: nan
+2023-10-29 16:26:55,000 - mmseg - INFO - Iter [300/40000]	lr: 1.187e-05, eta: 7:57:03, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 1.3885, decode.acc_seg: 63.8438, src.loss_imnet_feat_dist: nan
+2023-10-29 16:27:30,857 - mmseg - INFO - Iter [350/40000]	lr: 1.384e-05, eta: 7:56:05, time: 0.717, data_time: 0.014, memory: 9476, decode.loss_seg: 1.2493, decode.acc_seg: 64.0684, src.loss_imnet_feat_dist: nan
+2023-10-29 16:28:06,698 - mmseg - INFO - Iter [400/40000]	lr: 1.580e-05, eta: 7:55:11, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 1.1337, decode.acc_seg: 64.8724, src.loss_imnet_feat_dist: nan
+2023-10-29 16:28:42,557 - mmseg - INFO - Iter [450/40000]	lr: 1.776e-05, eta: 7:54:23, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.9617, decode.acc_seg: 67.7207, src.loss_imnet_feat_dist: nan
+2023-10-29 16:29:18,442 - mmseg - INFO - Iter [500/40000]	lr: 1.971e-05, eta: 7:53:39, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 1.0613, decode.acc_seg: 65.0620, src.loss_imnet_feat_dist: nan
+2023-10-29 16:29:54,727 - mmseg - INFO - Iter [550/40000]	lr: 2.166e-05, eta: 7:53:25, time: 0.726, data_time: 0.020, memory: 9476, decode.loss_seg: 0.8839, decode.acc_seg: 70.6168, src.loss_imnet_feat_dist: nan
+2023-10-29 16:30:30,709 - mmseg - INFO - Iter [600/40000]	lr: 2.360e-05, eta: 7:52:48, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.8694, decode.acc_seg: 70.0534, src.loss_imnet_feat_dist: nan
+2023-10-29 16:31:06,569 - mmseg - INFO - Iter [650/40000]	lr: 2.554e-05, eta: 7:52:04, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.8098, decode.acc_seg: 73.0486, src.loss_imnet_feat_dist: nan
+2023-10-29 16:31:42,467 - mmseg - INFO - Iter [700/40000]	lr: 2.747e-05, eta: 7:51:22, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.8102, decode.acc_seg: 71.6583, src.loss_imnet_feat_dist: nan
+2023-10-29 16:32:19,384 - mmseg - INFO - Iter [750/40000]	lr: 2.940e-05, eta: 7:51:35, time: 0.738, data_time: 0.032, memory: 9476, decode.loss_seg: 0.7713, decode.acc_seg: 72.5981, src.loss_imnet_feat_dist: nan
+2023-10-29 16:32:56,224 - mmseg - INFO - Iter [800/40000]	lr: 3.132e-05, eta: 7:51:38, time: 0.737, data_time: 0.029, memory: 9476, decode.loss_seg: 0.6442, decode.acc_seg: 74.4102, src.loss_imnet_feat_dist: nan
+2023-10-29 16:33:32,693 - mmseg - INFO - Iter [850/40000]	lr: 3.324e-05, eta: 7:51:19, time: 0.730, data_time: 0.023, memory: 9476, decode.loss_seg: 0.6803, decode.acc_seg: 74.0538, src.loss_imnet_feat_dist: nan
+2023-10-29 16:34:08,837 - mmseg - INFO - Iter [900/40000]	lr: 3.515e-05, eta: 7:50:44, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.6683, decode.acc_seg: 75.0580, src.loss_imnet_feat_dist: nan
+2023-10-29 16:34:44,731 - mmseg - INFO - Iter [950/40000]	lr: 3.706e-05, eta: 7:49:59, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6316, decode.acc_seg: 75.9140, src.loss_imnet_feat_dist: nan
+2023-10-29 16:35:20,726 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 16:35:20,727 - mmseg - INFO - Iter [1000/40000]	lr: 3.896e-05, eta: 7:49:18, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6936, decode.acc_seg: 73.8341, src.loss_imnet_feat_dist: nan
+2023-10-29 16:35:56,758 - mmseg - INFO - Iter [1050/40000]	lr: 4.086e-05, eta: 7:48:40, time: 0.721, data_time: 0.014, memory: 9476, decode.loss_seg: 0.5927, decode.acc_seg: 77.3139, src.loss_imnet_feat_dist: nan
+2023-10-29 16:36:32,761 - mmseg - INFO - Iter [1100/40000]	lr: 4.275e-05, eta: 7:48:00, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5850, decode.acc_seg: 78.7474, src.loss_imnet_feat_dist: nan
+2023-10-29 16:37:08,731 - mmseg - INFO - Iter [1150/40000]	lr: 4.464e-05, eta: 7:47:20, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6136, decode.acc_seg: 76.2474, src.loss_imnet_feat_dist: nan
+2023-10-29 16:37:44,662 - mmseg - INFO - Iter [1200/40000]	lr: 4.652e-05, eta: 7:46:39, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5637, decode.acc_seg: 78.7638, src.loss_imnet_feat_dist: nan
+2023-10-29 16:38:20,595 - mmseg - INFO - Iter [1250/40000]	lr: 4.840e-05, eta: 7:45:58, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5377, decode.acc_seg: 78.2073, src.loss_imnet_feat_dist: nan
+2023-10-29 16:38:56,502 - mmseg - INFO - Iter [1300/40000]	lr: 5.027e-05, eta: 7:45:17, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5375, decode.acc_seg: 77.5356, src.loss_imnet_feat_dist: nan
+2023-10-29 16:39:32,598 - mmseg - INFO - Iter [1350/40000]	lr: 5.214e-05, eta: 7:44:42, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.5994, decode.acc_seg: 77.3025, src.loss_imnet_feat_dist: nan
+2023-10-29 16:40:08,498 - mmseg - INFO - Iter [1400/40000]	lr: 5.400e-05, eta: 7:44:01, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6125, decode.acc_seg: 76.5923, src.loss_imnet_feat_dist: nan
+2023-10-29 16:40:44,455 - mmseg - INFO - Iter [1450/40000]	lr: 5.586e-05, eta: 7:43:22, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6111, decode.acc_seg: 78.0056, src.loss_imnet_feat_dist: nan
+2023-10-29 16:41:20,622 - mmseg - INFO - Iter [1500/40000]	lr: 5.771e-05, eta: 7:42:49, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.6675, decode.acc_seg: 76.1393, src.loss_imnet_feat_dist: 0.1185
+2023-10-29 16:41:56,600 - mmseg - INFO - Iter [1550/40000]	lr: 5.768e-05, eta: 7:42:11, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6637, decode.acc_seg: 75.0180, src.loss_imnet_feat_dist: nan
+2023-10-29 16:42:32,545 - mmseg - INFO - Iter [1600/40000]	lr: 5.760e-05, eta: 7:41:32, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5074, decode.acc_seg: 80.0385, src.loss_imnet_feat_dist: nan
+2023-10-29 16:43:08,503 - mmseg - INFO - Iter [1650/40000]	lr: 5.753e-05, eta: 7:40:53, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5081, decode.acc_seg: 78.4413, src.loss_imnet_feat_dist: nan
+2023-10-29 16:43:44,498 - mmseg - INFO - Iter [1700/40000]	lr: 5.745e-05, eta: 7:40:16, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.6289, decode.acc_seg: 75.8164, src.loss_imnet_feat_dist: nan
+2023-10-29 16:44:20,435 - mmseg - INFO - Iter [1750/40000]	lr: 5.738e-05, eta: 7:39:37, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5029, decode.acc_seg: 78.7446, src.loss_imnet_feat_dist: nan
+2023-10-29 16:44:56,365 - mmseg - INFO - Iter [1800/40000]	lr: 5.730e-05, eta: 7:38:59, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4908, decode.acc_seg: 78.9937, src.loss_imnet_feat_dist: 0.1179
+2023-10-29 16:45:32,296 - mmseg - INFO - Iter [1850/40000]	lr: 5.723e-05, eta: 7:38:20, time: 0.719, data_time: 0.012, memory: 9476, decode.loss_seg: 0.5007, decode.acc_seg: 80.3300, src.loss_imnet_feat_dist: nan
+2023-10-29 16:46:08,235 - mmseg - INFO - Iter [1900/40000]	lr: 5.715e-05, eta: 7:37:42, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4902, decode.acc_seg: 81.4509, src.loss_imnet_feat_dist: nan
+2023-10-29 16:46:44,567 - mmseg - INFO - Iter [1950/40000]	lr: 5.708e-05, eta: 7:37:12, time: 0.727, data_time: 0.020, memory: 9476, decode.loss_seg: 0.4165, decode.acc_seg: 81.5358, src.loss_imnet_feat_dist: nan
+2023-10-29 16:47:20,644 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 16:47:20,644 - mmseg - INFO - Iter [2000/40000]	lr: 5.700e-05, eta: 7:36:36, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.4944, decode.acc_seg: 80.7241, src.loss_imnet_feat_dist: nan
+2023-10-29 16:47:56,723 - mmseg - INFO - Iter [2050/40000]	lr: 5.693e-05, eta: 7:36:01, time: 0.722, data_time: 0.015, memory: 9476, decode.loss_seg: 0.4939, decode.acc_seg: 79.8053, src.loss_imnet_feat_dist: nan
+2023-10-29 16:48:32,617 - mmseg - INFO - Iter [2100/40000]	lr: 5.685e-05, eta: 7:35:22, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4754, decode.acc_seg: 79.6593, src.loss_imnet_feat_dist: nan
+2023-10-29 16:49:08,545 - mmseg - INFO - Iter [2150/40000]	lr: 5.678e-05, eta: 7:34:44, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4431, decode.acc_seg: 80.1216, src.loss_imnet_feat_dist: nan
+2023-10-29 16:49:44,437 - mmseg - INFO - Iter [2200/40000]	lr: 5.670e-05, eta: 7:34:05, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.5824, decode.acc_seg: 77.2297, src.loss_imnet_feat_dist: nan
+2023-10-29 16:50:20,364 - mmseg - INFO - Iter [2250/40000]	lr: 5.663e-05, eta: 7:33:27, time: 0.719, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4582, decode.acc_seg: 80.6184, src.loss_imnet_feat_dist: 0.1150
+2023-10-29 16:50:56,229 - mmseg - INFO - Iter [2300/40000]	lr: 5.655e-05, eta: 7:32:49, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4641, decode.acc_seg: 80.2975, src.loss_imnet_feat_dist: 0.1156
+2023-10-29 16:51:32,691 - mmseg - INFO - Iter [2350/40000]	lr: 5.648e-05, eta: 7:32:19, time: 0.729, data_time: 0.023, memory: 9476, decode.loss_seg: 0.4055, decode.acc_seg: 81.2685, src.loss_imnet_feat_dist: nan
+2023-10-29 16:52:08,501 - mmseg - INFO - Iter [2400/40000]	lr: 5.640e-05, eta: 7:31:40, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3955, decode.acc_seg: 83.4797, src.loss_imnet_feat_dist: nan
+2023-10-29 16:52:44,416 - mmseg - INFO - Iter [2450/40000]	lr: 5.633e-05, eta: 7:31:02, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4275, decode.acc_seg: 82.4224, src.loss_imnet_feat_dist: nan
+2023-10-29 16:53:20,358 - mmseg - INFO - Iter [2500/40000]	lr: 5.625e-05, eta: 7:30:24, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4566, decode.acc_seg: 82.4268, src.loss_imnet_feat_dist: nan
+2023-10-29 16:53:56,944 - mmseg - INFO - Iter [2550/40000]	lr: 5.618e-05, eta: 7:29:56, time: 0.732, data_time: 0.026, memory: 9476, decode.loss_seg: 0.4538, decode.acc_seg: 81.9533, src.loss_imnet_feat_dist: nan
+2023-10-29 16:54:32,904 - mmseg - INFO - Iter [2600/40000]	lr: 5.610e-05, eta: 7:29:19, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4692, decode.acc_seg: 81.0589, src.loss_imnet_feat_dist: 0.1231
+2023-10-29 16:55:08,961 - mmseg - INFO - Iter [2650/40000]	lr: 5.603e-05, eta: 7:28:43, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.4935, decode.acc_seg: 79.8519, src.loss_imnet_feat_dist: nan
+2023-10-29 16:55:45,176 - mmseg - INFO - Iter [2700/40000]	lr: 5.595e-05, eta: 7:28:10, time: 0.724, data_time: 0.020, memory: 9476, decode.loss_seg: 0.5306, decode.acc_seg: 80.9411, src.loss_imnet_feat_dist: nan
+2023-10-29 16:56:20,967 - mmseg - INFO - Iter [2750/40000]	lr: 5.588e-05, eta: 7:27:30, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3985, decode.acc_seg: 81.9045, src.loss_imnet_feat_dist: nan
+2023-10-29 16:56:56,797 - mmseg - INFO - Iter [2800/40000]	lr: 5.580e-05, eta: 7:26:51, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4982, decode.acc_seg: 80.5300, src.loss_imnet_feat_dist: nan
+2023-10-29 16:57:32,715 - mmseg - INFO - Iter [2850/40000]	lr: 5.573e-05, eta: 7:26:14, time: 0.718, data_time: 0.014, memory: 9476, decode.loss_seg: 0.4860, decode.acc_seg: 79.6105, src.loss_imnet_feat_dist: nan
+2023-10-29 16:58:08,753 - mmseg - INFO - Iter [2900/40000]	lr: 5.565e-05, eta: 7:25:37, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4088, decode.acc_seg: 81.8511, src.loss_imnet_feat_dist: nan
+2023-10-29 16:58:44,685 - mmseg - INFO - Iter [2950/40000]	lr: 5.558e-05, eta: 7:25:00, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.5127, decode.acc_seg: 79.8266, src.loss_imnet_feat_dist: nan
+2023-10-29 16:59:20,935 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 16:59:20,936 - mmseg - INFO - Iter [3000/40000]	lr: 5.550e-05, eta: 7:24:27, time: 0.725, data_time: 0.020, memory: 9476, decode.loss_seg: 0.4769, decode.acc_seg: 79.6561, src.loss_imnet_feat_dist: nan
+2023-10-29 16:59:57,482 - mmseg - INFO - Iter [3050/40000]	lr: 5.543e-05, eta: 7:23:57, time: 0.731, data_time: 0.025, memory: 9476, decode.loss_seg: 0.5391, decode.acc_seg: 77.9864, src.loss_imnet_feat_dist: 0.1236
+2023-10-29 17:00:33,488 - mmseg - INFO - Iter [3100/40000]	lr: 5.535e-05, eta: 7:23:21, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4608, decode.acc_seg: 81.5760, src.loss_imnet_feat_dist: nan
+2023-10-29 17:01:09,679 - mmseg - INFO - Iter [3150/40000]	lr: 5.528e-05, eta: 7:22:46, time: 0.724, data_time: 0.017, memory: 9476, decode.loss_seg: 0.4705, decode.acc_seg: 82.0654, src.loss_imnet_feat_dist: nan
+2023-10-29 17:01:45,678 - mmseg - INFO - Iter [3200/40000]	lr: 5.520e-05, eta: 7:22:10, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4478, decode.acc_seg: 82.8307, src.loss_imnet_feat_dist: nan
+2023-10-29 17:02:21,591 - mmseg - INFO - Iter [3250/40000]	lr: 5.513e-05, eta: 7:21:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4034, decode.acc_seg: 79.6909, src.loss_imnet_feat_dist: nan
+2023-10-29 17:02:57,440 - mmseg - INFO - Iter [3300/40000]	lr: 5.505e-05, eta: 7:20:54, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4044, decode.acc_seg: 82.5743, src.loss_imnet_feat_dist: 0.1225
+2023-10-29 17:03:33,312 - mmseg - INFO - Iter [3350/40000]	lr: 5.498e-05, eta: 7:20:16, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4006, decode.acc_seg: 82.9707, src.loss_imnet_feat_dist: nan
+2023-10-29 17:04:09,217 - mmseg - INFO - Iter [3400/40000]	lr: 5.490e-05, eta: 7:19:39, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3612, decode.acc_seg: 83.5554, src.loss_imnet_feat_dist: nan
+2023-10-29 17:04:45,265 - mmseg - INFO - Iter [3450/40000]	lr: 5.483e-05, eta: 7:19:03, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3969, decode.acc_seg: 82.2093, src.loss_imnet_feat_dist: nan
+2023-10-29 17:05:21,409 - mmseg - INFO - Iter [3500/40000]	lr: 5.475e-05, eta: 7:18:28, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.5040, decode.acc_seg: 81.6958, src.loss_imnet_feat_dist: nan
+2023-10-29 17:05:57,287 - mmseg - INFO - Iter [3550/40000]	lr: 5.468e-05, eta: 7:17:50, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4206, decode.acc_seg: 79.7547, src.loss_imnet_feat_dist: nan
+2023-10-29 17:06:33,226 - mmseg - INFO - Iter [3600/40000]	lr: 5.460e-05, eta: 7:17:13, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3947, decode.acc_seg: 82.6908, src.loss_imnet_feat_dist: nan
+2023-10-29 17:07:09,193 - mmseg - INFO - Iter [3650/40000]	lr: 5.453e-05, eta: 7:16:36, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.4115, decode.acc_seg: 82.2015, src.loss_imnet_feat_dist: nan
+2023-10-29 17:07:45,009 - mmseg - INFO - Iter [3700/40000]	lr: 5.445e-05, eta: 7:15:58, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3779, decode.acc_seg: 82.7062, src.loss_imnet_feat_dist: nan
+2023-10-29 17:08:21,094 - mmseg - INFO - Iter [3750/40000]	lr: 5.438e-05, eta: 7:15:23, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3943, decode.acc_seg: 83.4032, src.loss_imnet_feat_dist: nan
+2023-10-29 17:08:56,942 - mmseg - INFO - Iter [3800/40000]	lr: 5.430e-05, eta: 7:14:45, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4532, decode.acc_seg: 81.2252, src.loss_imnet_feat_dist: nan
+2023-10-29 17:09:32,836 - mmseg - INFO - Iter [3850/40000]	lr: 5.423e-05, eta: 7:14:07, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3690, decode.acc_seg: 82.6689, src.loss_imnet_feat_dist: nan
+2023-10-29 17:10:08,696 - mmseg - INFO - Iter [3900/40000]	lr: 5.415e-05, eta: 7:13:30, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4006, decode.acc_seg: 82.2296, src.loss_imnet_feat_dist: nan
+2023-10-29 17:10:44,535 - mmseg - INFO - Iter [3950/40000]	lr: 5.408e-05, eta: 7:12:52, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4414, decode.acc_seg: 81.1125, src.loss_imnet_feat_dist: nan
+2023-10-29 17:11:20,815 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 17:11:20,815 - mmseg - INFO - Iter [4000/40000]	lr: 5.400e-05, eta: 7:12:18, time: 0.726, data_time: 0.021, memory: 9476, decode.loss_seg: 0.4411, decode.acc_seg: 80.0407, src.loss_imnet_feat_dist: nan
+2023-10-29 17:11:56,751 - mmseg - INFO - Iter [4050/40000]	lr: 5.393e-05, eta: 7:11:42, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3924, decode.acc_seg: 81.9327, src.loss_imnet_feat_dist: nan
+2023-10-29 17:12:32,846 - mmseg - INFO - Iter [4100/40000]	lr: 5.385e-05, eta: 7:11:06, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3671, decode.acc_seg: 83.8677, src.loss_imnet_feat_dist: nan
+2023-10-29 17:13:08,925 - mmseg - INFO - Iter [4150/40000]	lr: 5.378e-05, eta: 7:10:31, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3549, decode.acc_seg: 83.1418, src.loss_imnet_feat_dist: nan
+2023-10-29 17:13:44,861 - mmseg - INFO - Iter [4200/40000]	lr: 5.370e-05, eta: 7:09:54, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4223, decode.acc_seg: 80.1872, src.loss_imnet_feat_dist: nan
+2023-10-29 17:14:20,647 - mmseg - INFO - Iter [4250/40000]	lr: 5.363e-05, eta: 7:09:16, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4122, decode.acc_seg: 82.1337, src.loss_imnet_feat_dist: nan
+2023-10-29 17:14:56,835 - mmseg - INFO - Iter [4300/40000]	lr: 5.355e-05, eta: 7:08:41, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.3687, decode.acc_seg: 82.3942, src.loss_imnet_feat_dist: nan
+2023-10-29 17:15:32,902 - mmseg - INFO - Iter [4350/40000]	lr: 5.348e-05, eta: 7:08:05, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3836, decode.acc_seg: 83.3992, src.loss_imnet_feat_dist: nan
+2023-10-29 17:16:08,772 - mmseg - INFO - Iter [4400/40000]	lr: 5.340e-05, eta: 7:07:28, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3928, decode.acc_seg: 83.4766, src.loss_imnet_feat_dist: nan
+2023-10-29 17:16:44,822 - mmseg - INFO - Iter [4450/40000]	lr: 5.333e-05, eta: 7:06:52, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3980, decode.acc_seg: 81.3535, src.loss_imnet_feat_dist: nan
+2023-10-29 17:17:20,624 - mmseg - INFO - Iter [4500/40000]	lr: 5.325e-05, eta: 7:06:15, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4481, decode.acc_seg: 81.5926, src.loss_imnet_feat_dist: nan
+2023-10-29 17:17:56,459 - mmseg - INFO - Iter [4550/40000]	lr: 5.318e-05, eta: 7:05:37, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3827, decode.acc_seg: 83.1657, src.loss_imnet_feat_dist: nan
+2023-10-29 17:18:32,305 - mmseg - INFO - Iter [4600/40000]	lr: 5.310e-05, eta: 7:05:00, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3742, decode.acc_seg: 82.8590, src.loss_imnet_feat_dist: 0.1210
+2023-10-29 17:19:08,855 - mmseg - INFO - Iter [4650/40000]	lr: 5.303e-05, eta: 7:04:28, time: 0.731, data_time: 0.027, memory: 9476, decode.loss_seg: 0.4253, decode.acc_seg: 80.8411, src.loss_imnet_feat_dist: nan
+2023-10-29 17:19:44,776 - mmseg - INFO - Iter [4700/40000]	lr: 5.295e-05, eta: 7:03:51, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3555, decode.acc_seg: 83.2455, src.loss_imnet_feat_dist: nan
+2023-10-29 17:20:20,690 - mmseg - INFO - Iter [4750/40000]	lr: 5.288e-05, eta: 7:03:14, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4715, decode.acc_seg: 80.8686, src.loss_imnet_feat_dist: 0.1139
+2023-10-29 17:20:56,524 - mmseg - INFO - Iter [4800/40000]	lr: 5.280e-05, eta: 7:02:37, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4062, decode.acc_seg: 81.7734, src.loss_imnet_feat_dist: nan
+2023-10-29 17:21:32,315 - mmseg - INFO - Iter [4850/40000]	lr: 5.273e-05, eta: 7:01:59, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3821, decode.acc_seg: 82.2829, src.loss_imnet_feat_dist: 0.1157
+2023-10-29 17:22:08,248 - mmseg - INFO - Iter [4900/40000]	lr: 5.265e-05, eta: 7:01:23, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3135, decode.acc_seg: 85.0834, src.loss_imnet_feat_dist: nan
+2023-10-29 17:22:44,165 - mmseg - INFO - Iter [4950/40000]	lr: 5.258e-05, eta: 7:00:46, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3667, decode.acc_seg: 83.2441, src.loss_imnet_feat_dist: nan
+2023-10-29 17:23:20,074 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 17:23:20,075 - mmseg - INFO - Iter [5000/40000]	lr: 5.250e-05, eta: 7:00:09, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3869, decode.acc_seg: 82.9046, src.loss_imnet_feat_dist: nan
+2023-10-29 17:23:55,994 - mmseg - INFO - Iter [5050/40000]	lr: 5.243e-05, eta: 6:59:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5009, decode.acc_seg: 79.7435, src.loss_imnet_feat_dist: nan
+2023-10-29 17:24:31,989 - mmseg - INFO - Iter [5100/40000]	lr: 5.235e-05, eta: 6:58:56, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.4313, decode.acc_seg: 82.5583, src.loss_imnet_feat_dist: nan
+2023-10-29 17:25:07,960 - mmseg - INFO - Iter [5150/40000]	lr: 5.228e-05, eta: 6:58:20, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4227, decode.acc_seg: 80.5074, src.loss_imnet_feat_dist: nan
+2023-10-29 17:25:43,892 - mmseg - INFO - Iter [5200/40000]	lr: 5.220e-05, eta: 6:57:43, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4162, decode.acc_seg: 82.9985, src.loss_imnet_feat_dist: nan
+2023-10-29 17:26:20,107 - mmseg - INFO - Iter [5250/40000]	lr: 5.213e-05, eta: 6:57:09, time: 0.724, data_time: 0.017, memory: 9476, decode.loss_seg: 0.4167, decode.acc_seg: 84.0013, src.loss_imnet_feat_dist: nan
+2023-10-29 17:26:56,031 - mmseg - INFO - Iter [5300/40000]	lr: 5.205e-05, eta: 6:56:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3895, decode.acc_seg: 83.2954, src.loss_imnet_feat_dist: nan
+2023-10-29 17:27:31,906 - mmseg - INFO - Iter [5350/40000]	lr: 5.198e-05, eta: 6:55:55, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.5066, decode.acc_seg: 80.0332, src.loss_imnet_feat_dist: nan
+2023-10-29 17:28:08,057 - mmseg - INFO - Iter [5400/40000]	lr: 5.190e-05, eta: 6:55:20, time: 0.723, data_time: 0.016, memory: 9476, decode.loss_seg: 0.4521, decode.acc_seg: 80.8388, src.loss_imnet_feat_dist: nan
+2023-10-29 17:28:43,975 - mmseg - INFO - Iter [5450/40000]	lr: 5.183e-05, eta: 6:54:43, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4755, decode.acc_seg: 81.5325, src.loss_imnet_feat_dist: nan
+2023-10-29 17:29:20,073 - mmseg - INFO - Iter [5500/40000]	lr: 5.175e-05, eta: 6:54:08, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.4006, decode.acc_seg: 83.1246, src.loss_imnet_feat_dist: nan
+2023-10-29 17:29:57,255 - mmseg - INFO - Iter [5550/40000]	lr: 5.168e-05, eta: 6:53:39, time: 0.744, data_time: 0.039, memory: 9476, decode.loss_seg: 0.4262, decode.acc_seg: 81.9479, src.loss_imnet_feat_dist: nan
+2023-10-29 17:30:33,119 - mmseg - INFO - Iter [5600/40000]	lr: 5.160e-05, eta: 6:53:02, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3827, decode.acc_seg: 83.2387, src.loss_imnet_feat_dist: 0.1168
+2023-10-29 17:31:08,926 - mmseg - INFO - Iter [5650/40000]	lr: 5.153e-05, eta: 6:52:25, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4302, decode.acc_seg: 81.0985, src.loss_imnet_feat_dist: nan
+2023-10-29 17:31:45,274 - mmseg - INFO - Iter [5700/40000]	lr: 5.145e-05, eta: 6:51:51, time: 0.727, data_time: 0.022, memory: 9476, decode.loss_seg: 0.4818, decode.acc_seg: 79.7100, src.loss_imnet_feat_dist: 0.1197
+2023-10-29 17:32:21,115 - mmseg - INFO - Iter [5750/40000]	lr: 5.138e-05, eta: 6:51:14, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4217, decode.acc_seg: 81.3040, src.loss_imnet_feat_dist: nan
+2023-10-29 17:32:57,232 - mmseg - INFO - Iter [5800/40000]	lr: 5.130e-05, eta: 6:50:38, time: 0.722, data_time: 0.019, memory: 9476, decode.loss_seg: 0.3800, decode.acc_seg: 82.0009, src.loss_imnet_feat_dist: nan
+2023-10-29 17:33:33,416 - mmseg - INFO - Iter [5850/40000]	lr: 5.123e-05, eta: 6:50:03, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.4111, decode.acc_seg: 82.3910, src.loss_imnet_feat_dist: nan
+2023-10-29 17:34:09,242 - mmseg - INFO - Iter [5900/40000]	lr: 5.115e-05, eta: 6:49:26, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4615, decode.acc_seg: 80.6351, src.loss_imnet_feat_dist: nan
+2023-10-29 17:34:45,115 - mmseg - INFO - Iter [5950/40000]	lr: 5.108e-05, eta: 6:48:49, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4046, decode.acc_seg: 81.7836, src.loss_imnet_feat_dist: 0.1262
+2023-10-29 17:35:20,963 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 17:35:20,964 - mmseg - INFO - Iter [6000/40000]	lr: 5.100e-05, eta: 6:48:12, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3993, decode.acc_seg: 81.9488, src.loss_imnet_feat_dist: nan
+2023-10-29 17:35:56,797 - mmseg - INFO - Iter [6050/40000]	lr: 5.093e-05, eta: 6:47:35, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3295, decode.acc_seg: 84.7006, src.loss_imnet_feat_dist: nan
+2023-10-29 17:36:32,656 - mmseg - INFO - Iter [6100/40000]	lr: 5.085e-05, eta: 6:46:58, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3539, decode.acc_seg: 84.0661, src.loss_imnet_feat_dist: nan
+2023-10-29 17:37:09,003 - mmseg - INFO - Iter [6150/40000]	lr: 5.078e-05, eta: 6:46:24, time: 0.727, data_time: 0.023, memory: 9476, decode.loss_seg: 0.3500, decode.acc_seg: 85.3939, src.loss_imnet_feat_dist: nan
+2023-10-29 17:37:44,914 - mmseg - INFO - Iter [6200/40000]	lr: 5.070e-05, eta: 6:45:47, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3604, decode.acc_seg: 82.9414, src.loss_imnet_feat_dist: nan
+2023-10-29 17:38:20,761 - mmseg - INFO - Iter [6250/40000]	lr: 5.063e-05, eta: 6:45:11, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3473, decode.acc_seg: 85.1558, src.loss_imnet_feat_dist: nan
+2023-10-29 17:38:56,637 - mmseg - INFO - Iter [6300/40000]	lr: 5.055e-05, eta: 6:44:34, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4228, decode.acc_seg: 82.8161, src.loss_imnet_feat_dist: nan
+2023-10-29 17:39:32,487 - mmseg - INFO - Iter [6350/40000]	lr: 5.048e-05, eta: 6:43:57, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4350, decode.acc_seg: 80.6356, src.loss_imnet_feat_dist: nan
+2023-10-29 17:40:08,474 - mmseg - INFO - Iter [6400/40000]	lr: 5.040e-05, eta: 6:43:21, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.4560, decode.acc_seg: 81.0466, src.loss_imnet_feat_dist: nan
+2023-10-29 17:40:44,494 - mmseg - INFO - Iter [6450/40000]	lr: 5.033e-05, eta: 6:42:45, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2902, decode.acc_seg: 85.1959, src.loss_imnet_feat_dist: nan
+2023-10-29 17:41:20,296 - mmseg - INFO - Iter [6500/40000]	lr: 5.025e-05, eta: 6:42:08, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2687, decode.acc_seg: 86.6690, src.loss_imnet_feat_dist: nan
+2023-10-29 17:41:56,842 - mmseg - INFO - Iter [6550/40000]	lr: 5.018e-05, eta: 6:41:34, time: 0.731, data_time: 0.027, memory: 9476, decode.loss_seg: 0.3186, decode.acc_seg: 83.7837, src.loss_imnet_feat_dist: 0.1082
+2023-10-29 17:42:32,638 - mmseg - INFO - Iter [6600/40000]	lr: 5.010e-05, eta: 6:40:57, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3212, decode.acc_seg: 86.3945, src.loss_imnet_feat_dist: nan
+2023-10-29 17:43:08,474 - mmseg - INFO - Iter [6650/40000]	lr: 5.003e-05, eta: 6:40:20, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2878, decode.acc_seg: 84.8452, src.loss_imnet_feat_dist: nan
+2023-10-29 17:43:44,434 - mmseg - INFO - Iter [6700/40000]	lr: 4.995e-05, eta: 6:39:44, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3359, decode.acc_seg: 84.9342, src.loss_imnet_feat_dist: nan
+2023-10-29 17:44:20,298 - mmseg - INFO - Iter [6750/40000]	lr: 4.988e-05, eta: 6:39:07, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2980, decode.acc_seg: 85.8627, src.loss_imnet_feat_dist: 0.1157
+2023-10-29 17:44:56,380 - mmseg - INFO - Iter [6800/40000]	lr: 4.980e-05, eta: 6:38:32, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2923, decode.acc_seg: 85.9448, src.loss_imnet_feat_dist: nan
+2023-10-29 17:45:32,119 - mmseg - INFO - Iter [6850/40000]	lr: 4.973e-05, eta: 6:37:54, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3420, decode.acc_seg: 84.0831, src.loss_imnet_feat_dist: nan
+2023-10-29 17:46:07,892 - mmseg - INFO - Iter [6900/40000]	lr: 4.965e-05, eta: 6:37:17, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3620, decode.acc_seg: 82.4583, src.loss_imnet_feat_dist: nan
+2023-10-29 17:46:43,644 - mmseg - INFO - Iter [6950/40000]	lr: 4.958e-05, eta: 6:36:40, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3683, decode.acc_seg: 83.7107, src.loss_imnet_feat_dist: nan
+2023-10-29 17:47:19,467 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 17:47:19,468 - mmseg - INFO - Iter [7000/40000]	lr: 4.950e-05, eta: 6:36:03, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3563, decode.acc_seg: 83.9348, src.loss_imnet_feat_dist: nan
+2023-10-29 17:47:55,319 - mmseg - INFO - Iter [7050/40000]	lr: 4.943e-05, eta: 6:35:26, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4317, decode.acc_seg: 82.0275, src.loss_imnet_feat_dist: nan
+2023-10-29 17:48:31,255 - mmseg - INFO - Iter [7100/40000]	lr: 4.935e-05, eta: 6:34:50, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3938, decode.acc_seg: 81.3578, src.loss_imnet_feat_dist: nan
+2023-10-29 17:49:07,051 - mmseg - INFO - Iter [7150/40000]	lr: 4.928e-05, eta: 6:34:13, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3287, decode.acc_seg: 85.5599, src.loss_imnet_feat_dist: nan
+2023-10-29 17:49:43,204 - mmseg - INFO - Iter [7200/40000]	lr: 4.920e-05, eta: 6:33:38, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2840, decode.acc_seg: 85.2231, src.loss_imnet_feat_dist: nan
+2023-10-29 17:50:19,005 - mmseg - INFO - Iter [7250/40000]	lr: 4.913e-05, eta: 6:33:01, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3364, decode.acc_seg: 84.6481, src.loss_imnet_feat_dist: 0.1154
+2023-10-29 17:50:54,972 - mmseg - INFO - Iter [7300/40000]	lr: 4.905e-05, eta: 6:32:25, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3673, decode.acc_seg: 84.4293, src.loss_imnet_feat_dist: nan
+2023-10-29 17:51:30,857 - mmseg - INFO - Iter [7350/40000]	lr: 4.898e-05, eta: 6:31:48, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3529, decode.acc_seg: 83.2523, src.loss_imnet_feat_dist: nan
+2023-10-29 17:52:06,891 - mmseg - INFO - Iter [7400/40000]	lr: 4.890e-05, eta: 6:31:12, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3567, decode.acc_seg: 84.2931, src.loss_imnet_feat_dist: nan
+2023-10-29 17:52:43,554 - mmseg - INFO - Iter [7450/40000]	lr: 4.883e-05, eta: 6:30:39, time: 0.733, data_time: 0.027, memory: 9476, decode.loss_seg: 0.3100, decode.acc_seg: 84.6047, src.loss_imnet_feat_dist: nan
+2023-10-29 17:53:19,302 - mmseg - INFO - Iter [7500/40000]	lr: 4.875e-05, eta: 6:30:02, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3039, decode.acc_seg: 85.5122, src.loss_imnet_feat_dist: nan
+2023-10-29 17:53:55,374 - mmseg - INFO - Iter [7550/40000]	lr: 4.868e-05, eta: 6:29:26, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3750, decode.acc_seg: 84.4675, src.loss_imnet_feat_dist: nan
+2023-10-29 17:54:31,439 - mmseg - INFO - Iter [7600/40000]	lr: 4.860e-05, eta: 6:28:51, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3612, decode.acc_seg: 84.3031, src.loss_imnet_feat_dist: nan
+2023-10-29 17:55:07,628 - mmseg - INFO - Iter [7650/40000]	lr: 4.853e-05, eta: 6:28:15, time: 0.724, data_time: 0.020, memory: 9476, decode.loss_seg: 0.3815, decode.acc_seg: 83.1079, src.loss_imnet_feat_dist: nan
+2023-10-29 17:55:43,501 - mmseg - INFO - Iter [7700/40000]	lr: 4.845e-05, eta: 6:27:39, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4016, decode.acc_seg: 83.5762, src.loss_imnet_feat_dist: nan
+2023-10-29 17:56:19,332 - mmseg - INFO - Iter [7750/40000]	lr: 4.838e-05, eta: 6:27:02, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4722, decode.acc_seg: 80.3135, src.loss_imnet_feat_dist: nan
+2023-10-29 17:56:55,729 - mmseg - INFO - Iter [7800/40000]	lr: 4.830e-05, eta: 6:26:28, time: 0.728, data_time: 0.023, memory: 9476, decode.loss_seg: 0.3189, decode.acc_seg: 84.8795, src.loss_imnet_feat_dist: nan
+2023-10-29 17:57:31,517 - mmseg - INFO - Iter [7850/40000]	lr: 4.823e-05, eta: 6:25:51, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3557, decode.acc_seg: 84.9743, src.loss_imnet_feat_dist: nan
+2023-10-29 17:58:07,362 - mmseg - INFO - Iter [7900/40000]	lr: 4.815e-05, eta: 6:25:14, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3790, decode.acc_seg: 83.6293, src.loss_imnet_feat_dist: nan
+2023-10-29 17:58:43,210 - mmseg - INFO - Iter [7950/40000]	lr: 4.808e-05, eta: 6:24:37, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3188, decode.acc_seg: 84.9499, src.loss_imnet_feat_dist: nan
+2023-10-29 17:59:19,035 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 17:59:19,035 - mmseg - INFO - Iter [8000/40000]	lr: 4.800e-05, eta: 6:24:01, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3213, decode.acc_seg: 85.2631, src.loss_imnet_feat_dist: nan
+2023-10-29 17:59:54,852 - mmseg - INFO - Iter [8050/40000]	lr: 4.793e-05, eta: 6:23:24, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2988, decode.acc_seg: 85.5713, src.loss_imnet_feat_dist: nan
+2023-10-29 18:00:30,738 - mmseg - INFO - Iter [8100/40000]	lr: 4.785e-05, eta: 6:22:48, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3220, decode.acc_seg: 84.5406, src.loss_imnet_feat_dist: nan
+2023-10-29 18:01:06,589 - mmseg - INFO - Iter [8150/40000]	lr: 4.778e-05, eta: 6:22:11, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4024, decode.acc_seg: 84.5977, src.loss_imnet_feat_dist: nan
+2023-10-29 18:01:42,470 - mmseg - INFO - Iter [8200/40000]	lr: 4.770e-05, eta: 6:21:35, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3525, decode.acc_seg: 84.8580, src.loss_imnet_feat_dist: nan
+2023-10-29 18:02:18,434 - mmseg - INFO - Iter [8250/40000]	lr: 4.763e-05, eta: 6:20:58, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.3060, decode.acc_seg: 84.7956, src.loss_imnet_feat_dist: nan
+2023-10-29 18:02:54,242 - mmseg - INFO - Iter [8300/40000]	lr: 4.755e-05, eta: 6:20:22, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3249, decode.acc_seg: 84.3229, src.loss_imnet_feat_dist: nan
+2023-10-29 18:03:30,090 - mmseg - INFO - Iter [8350/40000]	lr: 4.748e-05, eta: 6:19:45, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3128, decode.acc_seg: 84.6636, src.loss_imnet_feat_dist: nan
+2023-10-29 18:04:05,924 - mmseg - INFO - Iter [8400/40000]	lr: 4.740e-05, eta: 6:19:09, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3427, decode.acc_seg: 85.2473, src.loss_imnet_feat_dist: nan
+2023-10-29 18:04:41,786 - mmseg - INFO - Iter [8450/40000]	lr: 4.733e-05, eta: 6:18:32, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2887, decode.acc_seg: 83.8854, src.loss_imnet_feat_dist: nan
+2023-10-29 18:05:17,995 - mmseg - INFO - Iter [8500/40000]	lr: 4.725e-05, eta: 6:17:57, time: 0.724, data_time: 0.019, memory: 9476, decode.loss_seg: 0.3064, decode.acc_seg: 84.9583, src.loss_imnet_feat_dist: nan
+2023-10-29 18:05:54,132 - mmseg - INFO - Iter [8550/40000]	lr: 4.718e-05, eta: 6:17:21, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.3092, decode.acc_seg: 85.4524, src.loss_imnet_feat_dist: nan
+2023-10-29 18:06:31,818 - mmseg - INFO - Iter [8600/40000]	lr: 4.710e-05, eta: 6:16:52, time: 0.754, data_time: 0.047, memory: 9476, decode.loss_seg: 0.2797, decode.acc_seg: 85.4002, src.loss_imnet_feat_dist: nan
+2023-10-29 18:07:07,712 - mmseg - INFO - Iter [8650/40000]	lr: 4.703e-05, eta: 6:16:15, time: 0.718, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3413, decode.acc_seg: 84.9602, src.loss_imnet_feat_dist: 0.1031
+2023-10-29 18:07:43,507 - mmseg - INFO - Iter [8700/40000]	lr: 4.695e-05, eta: 6:15:38, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3429, decode.acc_seg: 82.8102, src.loss_imnet_feat_dist: nan
+2023-10-29 18:08:19,362 - mmseg - INFO - Iter [8750/40000]	lr: 4.688e-05, eta: 6:15:02, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3436, decode.acc_seg: 82.5926, src.loss_imnet_feat_dist: nan
+2023-10-29 18:08:55,373 - mmseg - INFO - Iter [8800/40000]	lr: 4.680e-05, eta: 6:14:26, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3067, decode.acc_seg: 84.1073, src.loss_imnet_feat_dist: nan
+2023-10-29 18:09:31,199 - mmseg - INFO - Iter [8850/40000]	lr: 4.673e-05, eta: 6:13:49, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3163, decode.acc_seg: 84.6730, src.loss_imnet_feat_dist: nan
+2023-10-29 18:10:07,040 - mmseg - INFO - Iter [8900/40000]	lr: 4.665e-05, eta: 6:13:13, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3341, decode.acc_seg: 83.9035, src.loss_imnet_feat_dist: nan
+2023-10-29 18:10:42,853 - mmseg - INFO - Iter [8950/40000]	lr: 4.658e-05, eta: 6:12:36, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3195, decode.acc_seg: 84.8192, src.loss_imnet_feat_dist: nan
+2023-10-29 18:11:18,835 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 18:11:18,836 - mmseg - INFO - Iter [9000/40000]	lr: 4.650e-05, eta: 6:12:00, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3287, decode.acc_seg: 84.6013, src.loss_imnet_feat_dist: nan
+2023-10-29 18:11:54,692 - mmseg - INFO - Iter [9050/40000]	lr: 4.643e-05, eta: 6:11:23, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2828, decode.acc_seg: 86.1594, src.loss_imnet_feat_dist: nan
+2023-10-29 18:12:30,509 - mmseg - INFO - Iter [9100/40000]	lr: 4.635e-05, eta: 6:10:47, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3167, decode.acc_seg: 85.4825, src.loss_imnet_feat_dist: nan
+2023-10-29 18:13:06,448 - mmseg - INFO - Iter [9150/40000]	lr: 4.628e-05, eta: 6:10:11, time: 0.719, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2904, decode.acc_seg: 85.1247, src.loss_imnet_feat_dist: nan
+2023-10-29 18:13:42,353 - mmseg - INFO - Iter [9200/40000]	lr: 4.620e-05, eta: 6:09:34, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4147, decode.acc_seg: 81.2770, src.loss_imnet_feat_dist: nan
+2023-10-29 18:14:18,840 - mmseg - INFO - Iter [9250/40000]	lr: 4.613e-05, eta: 6:09:00, time: 0.730, data_time: 0.023, memory: 9476, decode.loss_seg: 0.3170, decode.acc_seg: 85.5121, src.loss_imnet_feat_dist: nan
+2023-10-29 18:14:54,686 - mmseg - INFO - Iter [9300/40000]	lr: 4.605e-05, eta: 6:08:23, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3292, decode.acc_seg: 82.0190, src.loss_imnet_feat_dist: nan
+2023-10-29 18:15:30,678 - mmseg - INFO - Iter [9350/40000]	lr: 4.598e-05, eta: 6:07:47, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3244, decode.acc_seg: 85.3548, src.loss_imnet_feat_dist: nan
+2023-10-29 18:16:06,781 - mmseg - INFO - Iter [9400/40000]	lr: 4.590e-05, eta: 6:07:12, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3021, decode.acc_seg: 85.8770, src.loss_imnet_feat_dist: nan
+2023-10-29 18:16:42,719 - mmseg - INFO - Iter [9450/40000]	lr: 4.583e-05, eta: 6:06:35, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3806, decode.acc_seg: 81.8102, src.loss_imnet_feat_dist: 0.1116
+2023-10-29 18:17:18,610 - mmseg - INFO - Iter [9500/40000]	lr: 4.575e-05, eta: 6:05:59, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3809, decode.acc_seg: 83.6484, src.loss_imnet_feat_dist: nan
+2023-10-29 18:17:54,625 - mmseg - INFO - Iter [9550/40000]	lr: 4.568e-05, eta: 6:05:23, time: 0.720, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2828, decode.acc_seg: 86.2244, src.loss_imnet_feat_dist: nan
+2023-10-29 18:18:30,635 - mmseg - INFO - Iter [9600/40000]	lr: 4.560e-05, eta: 6:04:47, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3057, decode.acc_seg: 86.3356, src.loss_imnet_feat_dist: nan
+2023-10-29 18:19:06,665 - mmseg - INFO - Iter [9650/40000]	lr: 4.553e-05, eta: 6:04:11, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3271, decode.acc_seg: 83.8447, src.loss_imnet_feat_dist: nan
+2023-10-29 18:19:42,482 - mmseg - INFO - Iter [9700/40000]	lr: 4.545e-05, eta: 6:03:35, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3078, decode.acc_seg: 85.5058, src.loss_imnet_feat_dist: 0.1098
+2023-10-29 18:20:18,346 - mmseg - INFO - Iter [9750/40000]	lr: 4.538e-05, eta: 6:02:58, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3244, decode.acc_seg: 84.5532, src.loss_imnet_feat_dist: nan
+2023-10-29 18:20:54,197 - mmseg - INFO - Iter [9800/40000]	lr: 4.530e-05, eta: 6:02:22, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3704, decode.acc_seg: 83.6489, src.loss_imnet_feat_dist: nan
+2023-10-29 18:21:30,055 - mmseg - INFO - Iter [9850/40000]	lr: 4.523e-05, eta: 6:01:45, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3916, decode.acc_seg: 82.7379, src.loss_imnet_feat_dist: nan
+2023-10-29 18:22:06,136 - mmseg - INFO - Iter [9900/40000]	lr: 4.515e-05, eta: 6:01:10, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3332, decode.acc_seg: 84.5941, src.loss_imnet_feat_dist: nan
+2023-10-29 18:22:42,001 - mmseg - INFO - Iter [9950/40000]	lr: 4.508e-05, eta: 6:00:33, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3271, decode.acc_seg: 84.7793, src.loss_imnet_feat_dist: nan
+2023-10-29 18:23:17,984 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 18:23:17,984 - mmseg - INFO - Iter [10000/40000]	lr: 4.500e-05, eta: 5:59:57, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2952, decode.acc_seg: 84.9138, src.loss_imnet_feat_dist: nan
+2023-10-29 18:23:54,427 - mmseg - INFO - Iter [10050/40000]	lr: 4.493e-05, eta: 5:59:23, time: 0.729, data_time: 0.023, memory: 9476, decode.loss_seg: 0.3188, decode.acc_seg: 85.1356, src.loss_imnet_feat_dist: nan
+2023-10-29 18:24:30,460 - mmseg - INFO - Iter [10100/40000]	lr: 4.485e-05, eta: 5:58:47, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3086, decode.acc_seg: 86.0937, src.loss_imnet_feat_dist: nan
+2023-10-29 18:25:06,325 - mmseg - INFO - Iter [10150/40000]	lr: 4.478e-05, eta: 5:58:10, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3524, decode.acc_seg: 84.4420, src.loss_imnet_feat_dist: nan
+2023-10-29 18:25:42,338 - mmseg - INFO - Iter [10200/40000]	lr: 4.470e-05, eta: 5:57:34, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3292, decode.acc_seg: 83.5517, src.loss_imnet_feat_dist: 0.1147
+2023-10-29 18:26:18,401 - mmseg - INFO - Iter [10250/40000]	lr: 4.463e-05, eta: 5:56:59, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3077, decode.acc_seg: 84.9859, src.loss_imnet_feat_dist: nan
+2023-10-29 18:26:54,288 - mmseg - INFO - Iter [10300/40000]	lr: 4.455e-05, eta: 5:56:22, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3693, decode.acc_seg: 83.7002, src.loss_imnet_feat_dist: nan
+2023-10-29 18:27:30,145 - mmseg - INFO - Iter [10350/40000]	lr: 4.448e-05, eta: 5:55:46, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3380, decode.acc_seg: 85.5733, src.loss_imnet_feat_dist: nan
+2023-10-29 18:28:06,097 - mmseg - INFO - Iter [10400/40000]	lr: 4.440e-05, eta: 5:55:10, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2879, decode.acc_seg: 86.9607, src.loss_imnet_feat_dist: nan
+2023-10-29 18:28:42,010 - mmseg - INFO - Iter [10450/40000]	lr: 4.433e-05, eta: 5:54:33, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3539, decode.acc_seg: 85.3740, src.loss_imnet_feat_dist: nan
+2023-10-29 18:29:18,097 - mmseg - INFO - Iter [10500/40000]	lr: 4.425e-05, eta: 5:53:58, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3175, decode.acc_seg: 84.4027, src.loss_imnet_feat_dist: nan
+2023-10-29 18:29:53,958 - mmseg - INFO - Iter [10550/40000]	lr: 4.418e-05, eta: 5:53:21, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3149, decode.acc_seg: 85.7619, src.loss_imnet_feat_dist: nan
+2023-10-29 18:30:29,813 - mmseg - INFO - Iter [10600/40000]	lr: 4.410e-05, eta: 5:52:45, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3693, decode.acc_seg: 83.6903, src.loss_imnet_feat_dist: nan
+2023-10-29 18:31:05,644 - mmseg - INFO - Iter [10650/40000]	lr: 4.403e-05, eta: 5:52:09, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3158, decode.acc_seg: 84.6256, src.loss_imnet_feat_dist: 0.1140
+2023-10-29 18:31:41,727 - mmseg - INFO - Iter [10700/40000]	lr: 4.395e-05, eta: 5:51:33, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3309, decode.acc_seg: 85.1369, src.loss_imnet_feat_dist: nan
+2023-10-29 18:32:18,184 - mmseg - INFO - Iter [10750/40000]	lr: 4.388e-05, eta: 5:50:58, time: 0.729, data_time: 0.024, memory: 9476, decode.loss_seg: 0.2610, decode.acc_seg: 86.3264, src.loss_imnet_feat_dist: nan
+2023-10-29 18:32:54,405 - mmseg - INFO - Iter [10800/40000]	lr: 4.380e-05, eta: 5:50:23, time: 0.724, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2746, decode.acc_seg: 84.9640, src.loss_imnet_feat_dist: nan
+2023-10-29 18:33:30,170 - mmseg - INFO - Iter [10850/40000]	lr: 4.373e-05, eta: 5:49:46, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3864, decode.acc_seg: 84.0790, src.loss_imnet_feat_dist: nan
+2023-10-29 18:34:06,047 - mmseg - INFO - Iter [10900/40000]	lr: 4.365e-05, eta: 5:49:10, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3205, decode.acc_seg: 83.9985, src.loss_imnet_feat_dist: nan
+2023-10-29 18:34:42,311 - mmseg - INFO - Iter [10950/40000]	lr: 4.358e-05, eta: 5:48:34, time: 0.725, data_time: 0.021, memory: 9476, decode.loss_seg: 0.3109, decode.acc_seg: 83.9115, src.loss_imnet_feat_dist: nan
+2023-10-29 18:35:18,443 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 18:35:18,444 - mmseg - INFO - Iter [11000/40000]	lr: 4.350e-05, eta: 5:47:59, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2853, decode.acc_seg: 85.4689, src.loss_imnet_feat_dist: nan
+2023-10-29 18:35:54,316 - mmseg - INFO - Iter [11050/40000]	lr: 4.343e-05, eta: 5:47:22, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3523, decode.acc_seg: 84.8172, src.loss_imnet_feat_dist: nan
+2023-10-29 18:36:30,136 - mmseg - INFO - Iter [11100/40000]	lr: 4.335e-05, eta: 5:46:46, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2722, decode.acc_seg: 85.7546, src.loss_imnet_feat_dist: nan
+2023-10-29 18:37:05,931 - mmseg - INFO - Iter [11150/40000]	lr: 4.328e-05, eta: 5:46:09, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3528, decode.acc_seg: 84.4897, src.loss_imnet_feat_dist: nan
+2023-10-29 18:37:41,798 - mmseg - INFO - Iter [11200/40000]	lr: 4.320e-05, eta: 5:45:33, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2990, decode.acc_seg: 86.0168, src.loss_imnet_feat_dist: nan
+2023-10-29 18:38:17,597 - mmseg - INFO - Iter [11250/40000]	lr: 4.313e-05, eta: 5:44:57, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3390, decode.acc_seg: 82.6481, src.loss_imnet_feat_dist: nan
+2023-10-29 18:38:53,915 - mmseg - INFO - Iter [11300/40000]	lr: 4.305e-05, eta: 5:44:21, time: 0.726, data_time: 0.022, memory: 9476, decode.loss_seg: 0.3106, decode.acc_seg: 84.6728, src.loss_imnet_feat_dist: nan
+2023-10-29 18:39:29,837 - mmseg - INFO - Iter [11350/40000]	lr: 4.298e-05, eta: 5:43:45, time: 0.718, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3364, decode.acc_seg: 84.5540, src.loss_imnet_feat_dist: nan
+2023-10-29 18:40:07,257 - mmseg - INFO - Iter [11400/40000]	lr: 4.290e-05, eta: 5:43:13, time: 0.748, data_time: 0.044, memory: 9476, decode.loss_seg: 0.3338, decode.acc_seg: 84.3198, src.loss_imnet_feat_dist: 0.1173
+2023-10-29 18:40:43,220 - mmseg - INFO - Iter [11450/40000]	lr: 4.283e-05, eta: 5:42:37, time: 0.719, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2966, decode.acc_seg: 86.1169, src.loss_imnet_feat_dist: 0.1156
+2023-10-29 18:41:19,028 - mmseg - INFO - Iter [11500/40000]	lr: 4.275e-05, eta: 5:42:00, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3520, decode.acc_seg: 82.8841, src.loss_imnet_feat_dist: nan
+2023-10-29 18:41:55,867 - mmseg - INFO - Iter [11550/40000]	lr: 4.268e-05, eta: 5:41:26, time: 0.737, data_time: 0.030, memory: 9476, decode.loss_seg: 0.3229, decode.acc_seg: 85.3609, src.loss_imnet_feat_dist: nan
+2023-10-29 18:42:31,730 - mmseg - INFO - Iter [11600/40000]	lr: 4.260e-05, eta: 5:40:50, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2966, decode.acc_seg: 86.6470, src.loss_imnet_feat_dist: nan
+2023-10-29 18:43:07,704 - mmseg - INFO - Iter [11650/40000]	lr: 4.253e-05, eta: 5:40:14, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.3521, decode.acc_seg: 83.5174, src.loss_imnet_feat_dist: 0.1076
+2023-10-29 18:43:43,586 - mmseg - INFO - Iter [11700/40000]	lr: 4.245e-05, eta: 5:39:38, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2949, decode.acc_seg: 85.5507, src.loss_imnet_feat_dist: nan
+2023-10-29 18:44:19,513 - mmseg - INFO - Iter [11750/40000]	lr: 4.238e-05, eta: 5:39:01, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3113, decode.acc_seg: 85.4186, src.loss_imnet_feat_dist: nan
+2023-10-29 18:44:55,381 - mmseg - INFO - Iter [11800/40000]	lr: 4.230e-05, eta: 5:38:25, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.4003, decode.acc_seg: 83.3434, src.loss_imnet_feat_dist: nan
+2023-10-29 18:45:31,397 - mmseg - INFO - Iter [11850/40000]	lr: 4.223e-05, eta: 5:37:49, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3121, decode.acc_seg: 85.9631, src.loss_imnet_feat_dist: nan
+2023-10-29 18:46:07,315 - mmseg - INFO - Iter [11900/40000]	lr: 4.215e-05, eta: 5:37:13, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3716, decode.acc_seg: 83.5961, src.loss_imnet_feat_dist: nan
+2023-10-29 18:46:43,452 - mmseg - INFO - Iter [11950/40000]	lr: 4.208e-05, eta: 5:36:37, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3226, decode.acc_seg: 85.2580, src.loss_imnet_feat_dist: nan
+2023-10-29 18:47:19,343 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 18:47:19,344 - mmseg - INFO - Iter [12000/40000]	lr: 4.200e-05, eta: 5:36:01, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2669, decode.acc_seg: 86.2552, src.loss_imnet_feat_dist: nan
+2023-10-29 18:47:55,224 - mmseg - INFO - Iter [12050/40000]	lr: 4.193e-05, eta: 5:35:25, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2916, decode.acc_seg: 85.0013, src.loss_imnet_feat_dist: nan
+2023-10-29 18:48:31,089 - mmseg - INFO - Iter [12100/40000]	lr: 4.185e-05, eta: 5:34:48, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3735, decode.acc_seg: 83.9570, src.loss_imnet_feat_dist: nan
+2023-10-29 18:49:06,936 - mmseg - INFO - Iter [12150/40000]	lr: 4.178e-05, eta: 5:34:12, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3176, decode.acc_seg: 84.6183, src.loss_imnet_feat_dist: nan
+2023-10-29 18:49:42,760 - mmseg - INFO - Iter [12200/40000]	lr: 4.170e-05, eta: 5:33:36, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3683, decode.acc_seg: 83.0257, src.loss_imnet_feat_dist: nan
+2023-10-29 18:50:18,662 - mmseg - INFO - Iter [12250/40000]	lr: 4.163e-05, eta: 5:32:59, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3274, decode.acc_seg: 84.0129, src.loss_imnet_feat_dist: nan
+2023-10-29 18:50:54,519 - mmseg - INFO - Iter [12300/40000]	lr: 4.155e-05, eta: 5:32:23, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3362, decode.acc_seg: 84.5310, src.loss_imnet_feat_dist: nan
+2023-10-29 18:51:30,417 - mmseg - INFO - Iter [12350/40000]	lr: 4.148e-05, eta: 5:31:47, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3147, decode.acc_seg: 85.4804, src.loss_imnet_feat_dist: nan
+2023-10-29 18:52:06,289 - mmseg - INFO - Iter [12400/40000]	lr: 4.140e-05, eta: 5:31:11, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2578, decode.acc_seg: 86.8118, src.loss_imnet_feat_dist: nan
+2023-10-29 18:52:42,307 - mmseg - INFO - Iter [12450/40000]	lr: 4.133e-05, eta: 5:30:35, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3695, decode.acc_seg: 85.0506, src.loss_imnet_feat_dist: nan
+2023-10-29 18:53:18,192 - mmseg - INFO - Iter [12500/40000]	lr: 4.125e-05, eta: 5:29:58, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3292, decode.acc_seg: 84.9309, src.loss_imnet_feat_dist: nan
+2023-10-29 18:53:54,011 - mmseg - INFO - Iter [12550/40000]	lr: 4.118e-05, eta: 5:29:22, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3076, decode.acc_seg: 86.0221, src.loss_imnet_feat_dist: 0.1093
+2023-10-29 18:54:29,868 - mmseg - INFO - Iter [12600/40000]	lr: 4.110e-05, eta: 5:28:46, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.4050, decode.acc_seg: 83.5386, src.loss_imnet_feat_dist: nan
+2023-10-29 18:55:05,762 - mmseg - INFO - Iter [12650/40000]	lr: 4.103e-05, eta: 5:28:09, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3324, decode.acc_seg: 85.6116, src.loss_imnet_feat_dist: nan
+2023-10-29 18:55:41,616 - mmseg - INFO - Iter [12700/40000]	lr: 4.095e-05, eta: 5:27:33, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3438, decode.acc_seg: 84.3981, src.loss_imnet_feat_dist: nan
+2023-10-29 18:56:17,676 - mmseg - INFO - Iter [12750/40000]	lr: 4.088e-05, eta: 5:26:57, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3369, decode.acc_seg: 85.8950, src.loss_imnet_feat_dist: 0.1156
+2023-10-29 18:56:53,891 - mmseg - INFO - Iter [12800/40000]	lr: 4.080e-05, eta: 5:26:22, time: 0.724, data_time: 0.020, memory: 9476, decode.loss_seg: 0.3068, decode.acc_seg: 85.1099, src.loss_imnet_feat_dist: nan
+2023-10-29 18:57:30,210 - mmseg - INFO - Iter [12850/40000]	lr: 4.073e-05, eta: 5:25:46, time: 0.726, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2581, decode.acc_seg: 85.5258, src.loss_imnet_feat_dist: nan
+2023-10-29 18:58:06,184 - mmseg - INFO - Iter [12900/40000]	lr: 4.065e-05, eta: 5:25:10, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2950, decode.acc_seg: 84.2801, src.loss_imnet_feat_dist: nan
+2023-10-29 18:58:42,249 - mmseg - INFO - Iter [12950/40000]	lr: 4.058e-05, eta: 5:24:34, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2843, decode.acc_seg: 84.5761, src.loss_imnet_feat_dist: nan
+2023-10-29 18:59:18,065 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 18:59:18,065 - mmseg - INFO - Iter [13000/40000]	lr: 4.050e-05, eta: 5:23:58, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3045, decode.acc_seg: 84.4719, src.loss_imnet_feat_dist: nan
+2023-10-29 18:59:54,799 - mmseg - INFO - Iter [13050/40000]	lr: 4.043e-05, eta: 5:23:24, time: 0.735, data_time: 0.030, memory: 9476, decode.loss_seg: 0.2923, decode.acc_seg: 85.4449, src.loss_imnet_feat_dist: nan
+2023-10-29 19:00:30,667 - mmseg - INFO - Iter [13100/40000]	lr: 4.035e-05, eta: 5:22:47, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3987, decode.acc_seg: 85.2464, src.loss_imnet_feat_dist: nan
+2023-10-29 19:01:06,436 - mmseg - INFO - Iter [13150/40000]	lr: 4.028e-05, eta: 5:22:11, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3192, decode.acc_seg: 84.1974, src.loss_imnet_feat_dist: nan
+2023-10-29 19:01:42,200 - mmseg - INFO - Iter [13200/40000]	lr: 4.020e-05, eta: 5:21:34, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3263, decode.acc_seg: 84.2629, src.loss_imnet_feat_dist: nan
+2023-10-29 19:02:18,351 - mmseg - INFO - Iter [13250/40000]	lr: 4.013e-05, eta: 5:20:59, time: 0.723, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2754, decode.acc_seg: 84.4966, src.loss_imnet_feat_dist: nan
+2023-10-29 19:02:54,108 - mmseg - INFO - Iter [13300/40000]	lr: 4.005e-05, eta: 5:20:22, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2539, decode.acc_seg: 84.5782, src.loss_imnet_feat_dist: nan
+2023-10-29 19:03:29,873 - mmseg - INFO - Iter [13350/40000]	lr: 3.998e-05, eta: 5:19:46, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2486, decode.acc_seg: 88.2538, src.loss_imnet_feat_dist: nan
+2023-10-29 19:04:05,824 - mmseg - INFO - Iter [13400/40000]	lr: 3.990e-05, eta: 5:19:10, time: 0.719, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3451, decode.acc_seg: 84.5541, src.loss_imnet_feat_dist: nan
+2023-10-29 19:04:41,605 - mmseg - INFO - Iter [13450/40000]	lr: 3.983e-05, eta: 5:18:33, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3158, decode.acc_seg: 85.5564, src.loss_imnet_feat_dist: nan
+2023-10-29 19:05:17,802 - mmseg - INFO - Iter [13500/40000]	lr: 3.975e-05, eta: 5:17:58, time: 0.724, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2632, decode.acc_seg: 87.8394, src.loss_imnet_feat_dist: nan
+2023-10-29 19:05:53,592 - mmseg - INFO - Iter [13550/40000]	lr: 3.968e-05, eta: 5:17:21, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2131, decode.acc_seg: 87.8626, src.loss_imnet_feat_dist: nan
+2023-10-29 19:06:29,613 - mmseg - INFO - Iter [13600/40000]	lr: 3.960e-05, eta: 5:16:45, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2618, decode.acc_seg: 86.1334, src.loss_imnet_feat_dist: nan
+2023-10-29 19:07:05,804 - mmseg - INFO - Iter [13650/40000]	lr: 3.953e-05, eta: 5:16:10, time: 0.724, data_time: 0.021, memory: 9476, decode.loss_seg: 0.3033, decode.acc_seg: 84.6052, src.loss_imnet_feat_dist: nan
+2023-10-29 19:07:41,621 - mmseg - INFO - Iter [13700/40000]	lr: 3.945e-05, eta: 5:15:33, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2980, decode.acc_seg: 85.4080, src.loss_imnet_feat_dist: nan
+2023-10-29 19:08:17,855 - mmseg - INFO - Iter [13750/40000]	lr: 3.938e-05, eta: 5:14:58, time: 0.725, data_time: 0.020, memory: 9476, decode.loss_seg: 0.2468, decode.acc_seg: 86.2686, src.loss_imnet_feat_dist: nan
+2023-10-29 19:08:53,730 - mmseg - INFO - Iter [13800/40000]	lr: 3.930e-05, eta: 5:14:22, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2670, decode.acc_seg: 86.4562, src.loss_imnet_feat_dist: nan
+2023-10-29 19:09:29,756 - mmseg - INFO - Iter [13850/40000]	lr: 3.923e-05, eta: 5:13:46, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3002, decode.acc_seg: 86.2830, src.loss_imnet_feat_dist: nan
+2023-10-29 19:10:05,598 - mmseg - INFO - Iter [13900/40000]	lr: 3.915e-05, eta: 5:13:09, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2726, decode.acc_seg: 84.8693, src.loss_imnet_feat_dist: nan
+2023-10-29 19:10:41,474 - mmseg - INFO - Iter [13950/40000]	lr: 3.908e-05, eta: 5:12:33, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2375, decode.acc_seg: 86.6996, src.loss_imnet_feat_dist: nan
+2023-10-29 19:11:17,315 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 19:11:17,316 - mmseg - INFO - Iter [14000/40000]	lr: 3.900e-05, eta: 5:11:57, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2877, decode.acc_seg: 83.7504, src.loss_imnet_feat_dist: 0.1035
+2023-10-29 19:11:53,500 - mmseg - INFO - Iter [14050/40000]	lr: 3.893e-05, eta: 5:11:21, time: 0.724, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2566, decode.acc_seg: 86.0245, src.loss_imnet_feat_dist: 0.1061
+2023-10-29 19:12:29,447 - mmseg - INFO - Iter [14100/40000]	lr: 3.885e-05, eta: 5:10:45, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2478, decode.acc_seg: 87.0238, src.loss_imnet_feat_dist: nan
+2023-10-29 19:13:05,302 - mmseg - INFO - Iter [14150/40000]	lr: 3.878e-05, eta: 5:10:09, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3087, decode.acc_seg: 84.0007, src.loss_imnet_feat_dist: nan
+2023-10-29 19:13:41,172 - mmseg - INFO - Iter [14200/40000]	lr: 3.870e-05, eta: 5:09:33, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3142, decode.acc_seg: 86.5432, src.loss_imnet_feat_dist: nan
+2023-10-29 19:14:17,007 - mmseg - INFO - Iter [14250/40000]	lr: 3.863e-05, eta: 5:08:56, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3311, decode.acc_seg: 83.7929, src.loss_imnet_feat_dist: nan
+2023-10-29 19:14:53,088 - mmseg - INFO - Iter [14300/40000]	lr: 3.855e-05, eta: 5:08:21, time: 0.722, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2603, decode.acc_seg: 87.3009, src.loss_imnet_feat_dist: nan
+2023-10-29 19:15:28,936 - mmseg - INFO - Iter [14350/40000]	lr: 3.848e-05, eta: 5:07:44, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3126, decode.acc_seg: 84.7311, src.loss_imnet_feat_dist: 0.1050
+2023-10-29 19:16:05,054 - mmseg - INFO - Iter [14400/40000]	lr: 3.840e-05, eta: 5:07:09, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2762, decode.acc_seg: 86.7926, src.loss_imnet_feat_dist: nan
+2023-10-29 19:16:40,896 - mmseg - INFO - Iter [14450/40000]	lr: 3.833e-05, eta: 5:06:32, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2378, decode.acc_seg: 87.6007, src.loss_imnet_feat_dist: 0.1028
+2023-10-29 19:17:16,918 - mmseg - INFO - Iter [14500/40000]	lr: 3.825e-05, eta: 5:05:56, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2499, decode.acc_seg: 87.7154, src.loss_imnet_feat_dist: nan
+2023-10-29 19:17:53,175 - mmseg - INFO - Iter [14550/40000]	lr: 3.818e-05, eta: 5:05:21, time: 0.725, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2265, decode.acc_seg: 86.7366, src.loss_imnet_feat_dist: nan
+2023-10-29 19:18:29,202 - mmseg - INFO - Iter [14600/40000]	lr: 3.810e-05, eta: 5:04:45, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2420, decode.acc_seg: 86.3075, src.loss_imnet_feat_dist: nan
+2023-10-29 19:19:05,080 - mmseg - INFO - Iter [14650/40000]	lr: 3.803e-05, eta: 5:04:09, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2768, decode.acc_seg: 86.3303, src.loss_imnet_feat_dist: 0.1068
+2023-10-29 19:19:40,953 - mmseg - INFO - Iter [14700/40000]	lr: 3.795e-05, eta: 5:03:32, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2800, decode.acc_seg: 85.9600, src.loss_imnet_feat_dist: 0.1017
+2023-10-29 19:20:16,939 - mmseg - INFO - Iter [14750/40000]	lr: 3.788e-05, eta: 5:02:56, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2798, decode.acc_seg: 86.7529, src.loss_imnet_feat_dist: nan
+2023-10-29 19:20:52,773 - mmseg - INFO - Iter [14800/40000]	lr: 3.780e-05, eta: 5:02:20, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.3064, decode.acc_seg: 86.0586, src.loss_imnet_feat_dist: nan
+2023-10-29 19:21:28,610 - mmseg - INFO - Iter [14850/40000]	lr: 3.773e-05, eta: 5:01:44, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3225, decode.acc_seg: 84.9277, src.loss_imnet_feat_dist: nan
+2023-10-29 19:22:04,415 - mmseg - INFO - Iter [14900/40000]	lr: 3.765e-05, eta: 5:01:08, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2618, decode.acc_seg: 85.2928, src.loss_imnet_feat_dist: nan
+2023-10-29 19:22:40,330 - mmseg - INFO - Iter [14950/40000]	lr: 3.758e-05, eta: 5:00:31, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2718, decode.acc_seg: 85.8477, src.loss_imnet_feat_dist: nan
+2023-10-29 19:23:16,328 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 19:23:16,329 - mmseg - INFO - Iter [15000/40000]	lr: 3.750e-05, eta: 4:59:55, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2942, decode.acc_seg: 84.9415, src.loss_imnet_feat_dist: 0.1116
+2023-10-29 19:23:52,180 - mmseg - INFO - Iter [15050/40000]	lr: 3.743e-05, eta: 4:59:19, time: 0.717, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2576, decode.acc_seg: 88.5119, src.loss_imnet_feat_dist: nan
+2023-10-29 19:24:28,342 - mmseg - INFO - Iter [15100/40000]	lr: 3.735e-05, eta: 4:58:44, time: 0.723, data_time: 0.020, memory: 9476, decode.loss_seg: 0.3148, decode.acc_seg: 85.8566, src.loss_imnet_feat_dist: nan
+2023-10-29 19:25:04,480 - mmseg - INFO - Iter [15150/40000]	lr: 3.728e-05, eta: 4:58:08, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2772, decode.acc_seg: 87.8791, src.loss_imnet_feat_dist: 0.1024
+2023-10-29 19:25:40,295 - mmseg - INFO - Iter [15200/40000]	lr: 3.720e-05, eta: 4:57:32, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3120, decode.acc_seg: 85.6566, src.loss_imnet_feat_dist: nan
+2023-10-29 19:26:16,559 - mmseg - INFO - Iter [15250/40000]	lr: 3.713e-05, eta: 4:56:56, time: 0.725, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2484, decode.acc_seg: 86.4707, src.loss_imnet_feat_dist: nan
+2023-10-29 19:26:52,361 - mmseg - INFO - Iter [15300/40000]	lr: 3.705e-05, eta: 4:56:20, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2820, decode.acc_seg: 85.6771, src.loss_imnet_feat_dist: nan
+2023-10-29 19:27:28,127 - mmseg - INFO - Iter [15350/40000]	lr: 3.698e-05, eta: 4:55:43, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2458, decode.acc_seg: 86.4908, src.loss_imnet_feat_dist: nan
+2023-10-29 19:28:03,946 - mmseg - INFO - Iter [15400/40000]	lr: 3.690e-05, eta: 4:55:07, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2887, decode.acc_seg: 84.7543, src.loss_imnet_feat_dist: 0.1120
+2023-10-29 19:28:39,747 - mmseg - INFO - Iter [15450/40000]	lr: 3.683e-05, eta: 4:54:31, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2622, decode.acc_seg: 86.7133, src.loss_imnet_feat_dist: nan
+2023-10-29 19:29:15,545 - mmseg - INFO - Iter [15500/40000]	lr: 3.675e-05, eta: 4:53:54, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2560, decode.acc_seg: 86.6640, src.loss_imnet_feat_dist: nan
+2023-10-29 19:29:51,602 - mmseg - INFO - Iter [15550/40000]	lr: 3.668e-05, eta: 4:53:19, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2877, decode.acc_seg: 86.3095, src.loss_imnet_feat_dist: nan
+2023-10-29 19:30:27,349 - mmseg - INFO - Iter [15600/40000]	lr: 3.660e-05, eta: 4:52:42, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2639, decode.acc_seg: 86.0245, src.loss_imnet_feat_dist: nan
+2023-10-29 19:31:03,295 - mmseg - INFO - Iter [15650/40000]	lr: 3.653e-05, eta: 4:52:06, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3403, decode.acc_seg: 84.6176, src.loss_imnet_feat_dist: nan
+2023-10-29 19:31:39,559 - mmseg - INFO - Iter [15700/40000]	lr: 3.645e-05, eta: 4:51:31, time: 0.725, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2950, decode.acc_seg: 85.9451, src.loss_imnet_feat_dist: nan
+2023-10-29 19:32:15,435 - mmseg - INFO - Iter [15750/40000]	lr: 3.638e-05, eta: 4:50:54, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2593, decode.acc_seg: 84.4263, src.loss_imnet_feat_dist: 0.1114
+2023-10-29 19:32:51,205 - mmseg - INFO - Iter [15800/40000]	lr: 3.630e-05, eta: 4:50:18, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2953, decode.acc_seg: 85.9988, src.loss_imnet_feat_dist: nan
+2023-10-29 19:33:27,213 - mmseg - INFO - Iter [15850/40000]	lr: 3.623e-05, eta: 4:49:42, time: 0.720, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3022, decode.acc_seg: 84.6741, src.loss_imnet_feat_dist: nan
+2023-10-29 19:34:03,076 - mmseg - INFO - Iter [15900/40000]	lr: 3.615e-05, eta: 4:49:06, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2407, decode.acc_seg: 87.5397, src.loss_imnet_feat_dist: nan
+2023-10-29 19:34:38,882 - mmseg - INFO - Iter [15950/40000]	lr: 3.608e-05, eta: 4:48:30, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2999, decode.acc_seg: 85.4385, src.loss_imnet_feat_dist: nan
+2023-10-29 19:35:14,696 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 19:35:14,696 - mmseg - INFO - Iter [16000/40000]	lr: 3.600e-05, eta: 4:47:53, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2942, decode.acc_seg: 84.3910, src.loss_imnet_feat_dist: nan
+2023-10-29 19:35:50,785 - mmseg - INFO - Iter [16050/40000]	lr: 3.593e-05, eta: 4:47:18, time: 0.722, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2570, decode.acc_seg: 87.0983, src.loss_imnet_feat_dist: nan
+2023-10-29 19:36:26,556 - mmseg - INFO - Iter [16100/40000]	lr: 3.585e-05, eta: 4:46:41, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2497, decode.acc_seg: 86.7752, src.loss_imnet_feat_dist: nan
+2023-10-29 19:37:02,548 - mmseg - INFO - Iter [16150/40000]	lr: 3.578e-05, eta: 4:46:05, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2615, decode.acc_seg: 85.5877, src.loss_imnet_feat_dist: nan
+2023-10-29 19:37:38,548 - mmseg - INFO - Iter [16200/40000]	lr: 3.570e-05, eta: 4:45:29, time: 0.720, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2603, decode.acc_seg: 87.0474, src.loss_imnet_feat_dist: 0.1069
+2023-10-29 19:38:14,388 - mmseg - INFO - Iter [16250/40000]	lr: 3.563e-05, eta: 4:44:53, time: 0.717, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2876, decode.acc_seg: 87.0076, src.loss_imnet_feat_dist: nan
+2023-10-29 19:38:50,229 - mmseg - INFO - Iter [16300/40000]	lr: 3.555e-05, eta: 4:44:17, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3036, decode.acc_seg: 86.7999, src.loss_imnet_feat_dist: 0.1149
+2023-10-29 19:39:26,056 - mmseg - INFO - Iter [16350/40000]	lr: 3.548e-05, eta: 4:43:41, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2608, decode.acc_seg: 85.0923, src.loss_imnet_feat_dist: nan
+2023-10-29 19:40:01,889 - mmseg - INFO - Iter [16400/40000]	lr: 3.540e-05, eta: 4:43:05, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2508, decode.acc_seg: 87.8408, src.loss_imnet_feat_dist: nan
+2023-10-29 19:40:37,729 - mmseg - INFO - Iter [16450/40000]	lr: 3.533e-05, eta: 4:42:28, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2552, decode.acc_seg: 86.9759, src.loss_imnet_feat_dist: nan
+2023-10-29 19:41:13,681 - mmseg - INFO - Iter [16500/40000]	lr: 3.525e-05, eta: 4:41:52, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.3101, decode.acc_seg: 84.3048, src.loss_imnet_feat_dist: nan
+2023-10-29 19:41:49,456 - mmseg - INFO - Iter [16550/40000]	lr: 3.518e-05, eta: 4:41:16, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2363, decode.acc_seg: 85.6048, src.loss_imnet_feat_dist: 0.1110
+2023-10-29 19:42:25,314 - mmseg - INFO - Iter [16600/40000]	lr: 3.510e-05, eta: 4:40:40, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2639, decode.acc_seg: 85.7582, src.loss_imnet_feat_dist: nan
+2023-10-29 19:43:01,185 - mmseg - INFO - Iter [16650/40000]	lr: 3.503e-05, eta: 4:40:04, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2735, decode.acc_seg: 85.4727, src.loss_imnet_feat_dist: nan
+2023-10-29 19:43:36,959 - mmseg - INFO - Iter [16700/40000]	lr: 3.495e-05, eta: 4:39:27, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3069, decode.acc_seg: 85.3613, src.loss_imnet_feat_dist: nan
+2023-10-29 19:44:12,846 - mmseg - INFO - Iter [16750/40000]	lr: 3.488e-05, eta: 4:38:51, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2596, decode.acc_seg: 84.6157, src.loss_imnet_feat_dist: nan
+2023-10-29 19:44:48,663 - mmseg - INFO - Iter [16800/40000]	lr: 3.480e-05, eta: 4:38:15, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2380, decode.acc_seg: 86.8915, src.loss_imnet_feat_dist: nan
+2023-10-29 19:45:24,550 - mmseg - INFO - Iter [16850/40000]	lr: 3.473e-05, eta: 4:37:39, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2593, decode.acc_seg: 86.0181, src.loss_imnet_feat_dist: nan
+2023-10-29 19:46:00,605 - mmseg - INFO - Iter [16900/40000]	lr: 3.465e-05, eta: 4:37:03, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2614, decode.acc_seg: 85.4599, src.loss_imnet_feat_dist: nan
+2023-10-29 19:46:36,521 - mmseg - INFO - Iter [16950/40000]	lr: 3.458e-05, eta: 4:36:27, time: 0.718, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2560, decode.acc_seg: 87.5842, src.loss_imnet_feat_dist: nan
+2023-10-29 19:47:12,279 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 19:47:12,279 - mmseg - INFO - Iter [17000/40000]	lr: 3.450e-05, eta: 4:35:51, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2541, decode.acc_seg: 86.9739, src.loss_imnet_feat_dist: 0.1095
+2023-10-29 19:47:48,308 - mmseg - INFO - Iter [17050/40000]	lr: 3.443e-05, eta: 4:35:15, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.3239, decode.acc_seg: 85.7609, src.loss_imnet_feat_dist: nan
+2023-10-29 19:48:24,054 - mmseg - INFO - Iter [17100/40000]	lr: 3.435e-05, eta: 4:34:39, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3239, decode.acc_seg: 86.3372, src.loss_imnet_feat_dist: nan
+2023-10-29 19:48:59,811 - mmseg - INFO - Iter [17150/40000]	lr: 3.428e-05, eta: 4:34:02, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2286, decode.acc_seg: 88.0518, src.loss_imnet_feat_dist: nan
+2023-10-29 19:49:35,621 - mmseg - INFO - Iter [17200/40000]	lr: 3.420e-05, eta: 4:33:26, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3235, decode.acc_seg: 83.7368, src.loss_imnet_feat_dist: nan
+2023-10-29 19:50:11,761 - mmseg - INFO - Iter [17250/40000]	lr: 3.413e-05, eta: 4:32:50, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.3857, decode.acc_seg: 83.5870, src.loss_imnet_feat_dist: nan
+2023-10-29 19:50:48,189 - mmseg - INFO - Iter [17300/40000]	lr: 3.405e-05, eta: 4:32:15, time: 0.729, data_time: 0.024, memory: 9476, decode.loss_seg: 0.2808, decode.acc_seg: 87.1002, src.loss_imnet_feat_dist: nan
+2023-10-29 19:51:24,010 - mmseg - INFO - Iter [17350/40000]	lr: 3.398e-05, eta: 4:31:39, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2645, decode.acc_seg: 87.1895, src.loss_imnet_feat_dist: nan
+2023-10-29 19:51:59,987 - mmseg - INFO - Iter [17400/40000]	lr: 3.390e-05, eta: 4:31:03, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2252, decode.acc_seg: 87.1147, src.loss_imnet_feat_dist: nan
+2023-10-29 19:52:35,935 - mmseg - INFO - Iter [17450/40000]	lr: 3.383e-05, eta: 4:30:27, time: 0.719, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2697, decode.acc_seg: 85.7860, src.loss_imnet_feat_dist: 0.1056
+2023-10-29 19:53:11,657 - mmseg - INFO - Iter [17500/40000]	lr: 3.375e-05, eta: 4:29:50, time: 0.714, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2957, decode.acc_seg: 84.3291, src.loss_imnet_feat_dist: nan
+2023-10-29 19:53:47,396 - mmseg - INFO - Iter [17550/40000]	lr: 3.368e-05, eta: 4:29:14, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2629, decode.acc_seg: 85.7911, src.loss_imnet_feat_dist: nan
+2023-10-29 19:54:23,189 - mmseg - INFO - Iter [17600/40000]	lr: 3.360e-05, eta: 4:28:38, time: 0.716, data_time: 0.014, memory: 9476, decode.loss_seg: 0.3409, decode.acc_seg: 83.3332, src.loss_imnet_feat_dist: nan
+2023-10-29 19:54:58,959 - mmseg - INFO - Iter [17650/40000]	lr: 3.353e-05, eta: 4:28:02, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2686, decode.acc_seg: 86.5465, src.loss_imnet_feat_dist: nan
+2023-10-29 19:55:34,743 - mmseg - INFO - Iter [17700/40000]	lr: 3.345e-05, eta: 4:27:25, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2788, decode.acc_seg: 85.7287, src.loss_imnet_feat_dist: nan
+2023-10-29 19:56:11,040 - mmseg - INFO - Iter [17750/40000]	lr: 3.338e-05, eta: 4:26:50, time: 0.726, data_time: 0.020, memory: 9476, decode.loss_seg: 0.2425, decode.acc_seg: 88.5978, src.loss_imnet_feat_dist: nan
+2023-10-29 19:56:47,198 - mmseg - INFO - Iter [17800/40000]	lr: 3.330e-05, eta: 4:26:14, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2745, decode.acc_seg: 85.9151, src.loss_imnet_feat_dist: nan
+2023-10-29 19:57:23,217 - mmseg - INFO - Iter [17850/40000]	lr: 3.323e-05, eta: 4:25:38, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2953, decode.acc_seg: 83.8614, src.loss_imnet_feat_dist: 0.1127
+2023-10-29 19:57:59,104 - mmseg - INFO - Iter [17900/40000]	lr: 3.315e-05, eta: 4:25:02, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2482, decode.acc_seg: 86.6170, src.loss_imnet_feat_dist: nan
+2023-10-29 19:58:34,969 - mmseg - INFO - Iter [17950/40000]	lr: 3.308e-05, eta: 4:24:26, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2883, decode.acc_seg: 83.7810, src.loss_imnet_feat_dist: nan
+2023-10-29 19:59:23,850 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 19:59:23,850 - mmseg - INFO - Iter [18000/40000]	lr: 3.300e-05, eta: 4:24:06, time: 0.978, data_time: 0.273, memory: 9476, decode.loss_seg: 0.2877, decode.acc_seg: 85.4609, src.loss_imnet_feat_dist: nan
+2023-10-29 20:00:32,944 - mmseg - INFO - Iter [18050/40000]	lr: 3.293e-05, eta: 4:24:10, time: 1.382, data_time: 0.676, memory: 9476, decode.loss_seg: 0.2382, decode.acc_seg: 85.2701, src.loss_imnet_feat_dist: nan
+2023-10-29 20:01:08,614 - mmseg - INFO - Iter [18100/40000]	lr: 3.285e-05, eta: 4:23:33, time: 0.713, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2570, decode.acc_seg: 88.0610, src.loss_imnet_feat_dist: nan
+2023-10-29 20:01:44,284 - mmseg - INFO - Iter [18150/40000]	lr: 3.278e-05, eta: 4:22:57, time: 0.713, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2133, decode.acc_seg: 87.7025, src.loss_imnet_feat_dist: nan
+2023-10-29 20:02:20,154 - mmseg - INFO - Iter [18200/40000]	lr: 3.270e-05, eta: 4:22:20, time: 0.717, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2366, decode.acc_seg: 86.0453, src.loss_imnet_feat_dist: nan
+2023-10-29 20:02:55,899 - mmseg - INFO - Iter [18250/40000]	lr: 3.263e-05, eta: 4:21:44, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2951, decode.acc_seg: 84.8106, src.loss_imnet_feat_dist: nan
+2023-10-29 20:03:31,662 - mmseg - INFO - Iter [18300/40000]	lr: 3.255e-05, eta: 4:21:07, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2497, decode.acc_seg: 87.5583, src.loss_imnet_feat_dist: 0.1036
+2023-10-29 20:04:07,600 - mmseg - INFO - Iter [18350/40000]	lr: 3.248e-05, eta: 4:20:31, time: 0.719, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2623, decode.acc_seg: 86.4188, src.loss_imnet_feat_dist: nan
+2023-10-29 20:04:43,345 - mmseg - INFO - Iter [18400/40000]	lr: 3.240e-05, eta: 4:19:54, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2720, decode.acc_seg: 86.2371, src.loss_imnet_feat_dist: nan
+2023-10-29 20:05:19,094 - mmseg - INFO - Iter [18450/40000]	lr: 3.233e-05, eta: 4:19:18, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2409, decode.acc_seg: 87.2502, src.loss_imnet_feat_dist: nan
+2023-10-29 20:05:54,895 - mmseg - INFO - Iter [18500/40000]	lr: 3.225e-05, eta: 4:18:42, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2829, decode.acc_seg: 84.4131, src.loss_imnet_feat_dist: nan
+2023-10-29 20:06:30,645 - mmseg - INFO - Iter [18550/40000]	lr: 3.218e-05, eta: 4:18:05, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2714, decode.acc_seg: 85.9051, src.loss_imnet_feat_dist: nan
+2023-10-29 20:07:06,409 - mmseg - INFO - Iter [18600/40000]	lr: 3.210e-05, eta: 4:17:29, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3860, decode.acc_seg: 83.7215, src.loss_imnet_feat_dist: nan
+2023-10-29 20:07:42,217 - mmseg - INFO - Iter [18650/40000]	lr: 3.203e-05, eta: 4:16:52, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3236, decode.acc_seg: 83.6331, src.loss_imnet_feat_dist: nan
+2023-10-29 20:08:17,985 - mmseg - INFO - Iter [18700/40000]	lr: 3.195e-05, eta: 4:16:16, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2682, decode.acc_seg: 86.4885, src.loss_imnet_feat_dist: 0.1091
+2023-10-29 20:08:53,768 - mmseg - INFO - Iter [18750/40000]	lr: 3.188e-05, eta: 4:15:39, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2907, decode.acc_seg: 85.5756, src.loss_imnet_feat_dist: nan
+2023-10-29 20:09:29,551 - mmseg - INFO - Iter [18800/40000]	lr: 3.180e-05, eta: 4:15:03, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3013, decode.acc_seg: 85.0359, src.loss_imnet_feat_dist: nan
+2023-10-29 20:10:05,372 - mmseg - INFO - Iter [18850/40000]	lr: 3.173e-05, eta: 4:14:26, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2670, decode.acc_seg: 85.0150, src.loss_imnet_feat_dist: nan
+2023-10-29 20:10:41,638 - mmseg - INFO - Iter [18900/40000]	lr: 3.165e-05, eta: 4:13:50, time: 0.725, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2650, decode.acc_seg: 87.2444, src.loss_imnet_feat_dist: nan
+2023-10-29 20:11:17,417 - mmseg - INFO - Iter [18950/40000]	lr: 3.158e-05, eta: 4:13:14, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2731, decode.acc_seg: 85.2084, src.loss_imnet_feat_dist: nan
+2023-10-29 20:11:53,585 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 20:11:53,586 - mmseg - INFO - Iter [19000/40000]	lr: 3.150e-05, eta: 4:12:38, time: 0.723, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2462, decode.acc_seg: 87.8698, src.loss_imnet_feat_dist: nan
+2023-10-29 20:12:29,355 - mmseg - INFO - Iter [19050/40000]	lr: 3.143e-05, eta: 4:12:02, time: 0.715, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2580, decode.acc_seg: 86.4222, src.loss_imnet_feat_dist: 0.1076
+2023-10-29 20:13:05,141 - mmseg - INFO - Iter [19100/40000]	lr: 3.135e-05, eta: 4:11:25, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2184, decode.acc_seg: 88.5676, src.loss_imnet_feat_dist: nan
+2023-10-29 20:13:41,486 - mmseg - INFO - Iter [19150/40000]	lr: 3.128e-05, eta: 4:10:49, time: 0.727, data_time: 0.024, memory: 9476, decode.loss_seg: 0.2889, decode.acc_seg: 86.3704, src.loss_imnet_feat_dist: 0.1069
+2023-10-29 20:14:17,254 - mmseg - INFO - Iter [19200/40000]	lr: 3.120e-05, eta: 4:10:13, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2330, decode.acc_seg: 87.9843, src.loss_imnet_feat_dist: nan
+2023-10-29 20:14:52,974 - mmseg - INFO - Iter [19250/40000]	lr: 3.113e-05, eta: 4:09:36, time: 0.714, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2486, decode.acc_seg: 86.7666, src.loss_imnet_feat_dist: nan
+2023-10-29 20:15:28,727 - mmseg - INFO - Iter [19300/40000]	lr: 3.105e-05, eta: 4:09:00, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2945, decode.acc_seg: 85.7053, src.loss_imnet_feat_dist: nan
+2023-10-29 20:16:04,513 - mmseg - INFO - Iter [19350/40000]	lr: 3.098e-05, eta: 4:08:24, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2372, decode.acc_seg: 87.4249, src.loss_imnet_feat_dist: nan
+2023-10-29 20:16:40,253 - mmseg - INFO - Iter [19400/40000]	lr: 3.090e-05, eta: 4:07:47, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3085, decode.acc_seg: 86.1322, src.loss_imnet_feat_dist: 0.0954
+2023-10-29 20:17:16,049 - mmseg - INFO - Iter [19450/40000]	lr: 3.083e-05, eta: 4:07:11, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2970, decode.acc_seg: 85.8608, src.loss_imnet_feat_dist: nan
+2023-10-29 20:17:51,753 - mmseg - INFO - Iter [19500/40000]	lr: 3.075e-05, eta: 4:06:34, time: 0.714, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2801, decode.acc_seg: 85.1773, src.loss_imnet_feat_dist: nan
+2023-10-29 20:18:28,501 - mmseg - INFO - Iter [19550/40000]	lr: 3.068e-05, eta: 4:05:59, time: 0.735, data_time: 0.033, memory: 9476, decode.loss_seg: 0.2384, decode.acc_seg: 87.6255, src.loss_imnet_feat_dist: nan
+2023-10-29 20:19:04,244 - mmseg - INFO - Iter [19600/40000]	lr: 3.060e-05, eta: 4:05:22, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2542, decode.acc_seg: 85.8705, src.loss_imnet_feat_dist: 0.1059
+2023-10-29 20:19:40,171 - mmseg - INFO - Iter [19650/40000]	lr: 3.053e-05, eta: 4:04:46, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2253, decode.acc_seg: 87.7618, src.loss_imnet_feat_dist: nan
+2023-10-29 20:20:15,963 - mmseg - INFO - Iter [19700/40000]	lr: 3.045e-05, eta: 4:04:10, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2541, decode.acc_seg: 86.5225, src.loss_imnet_feat_dist: nan
+2023-10-29 20:20:52,040 - mmseg - INFO - Iter [19750/40000]	lr: 3.038e-05, eta: 4:03:34, time: 0.722, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2294, decode.acc_seg: 86.6522, src.loss_imnet_feat_dist: 0.1094
+2023-10-29 20:21:27,796 - mmseg - INFO - Iter [19800/40000]	lr: 3.030e-05, eta: 4:02:57, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2409, decode.acc_seg: 86.3590, src.loss_imnet_feat_dist: 0.1055
+2023-10-29 20:22:03,644 - mmseg - INFO - Iter [19850/40000]	lr: 3.023e-05, eta: 4:02:21, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2352, decode.acc_seg: 87.5948, src.loss_imnet_feat_dist: nan
+2023-10-29 20:22:39,882 - mmseg - INFO - Iter [19900/40000]	lr: 3.015e-05, eta: 4:01:45, time: 0.725, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2719, decode.acc_seg: 84.3511, src.loss_imnet_feat_dist: nan
+2023-10-29 20:23:16,075 - mmseg - INFO - Iter [19950/40000]	lr: 3.008e-05, eta: 4:01:09, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2345, decode.acc_seg: 87.8064, src.loss_imnet_feat_dist: nan
+2023-10-29 20:23:51,998 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 20:23:51,998 - mmseg - INFO - Iter [20000/40000]	lr: 3.000e-05, eta: 4:00:33, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2583, decode.acc_seg: 85.5490, src.loss_imnet_feat_dist: nan
+2023-10-29 20:24:27,919 - mmseg - INFO - Iter [20050/40000]	lr: 2.993e-05, eta: 3:59:56, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2964, decode.acc_seg: 86.4912, src.loss_imnet_feat_dist: nan
+2023-10-29 20:25:03,838 - mmseg - INFO - Iter [20100/40000]	lr: 2.985e-05, eta: 3:59:20, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2901, decode.acc_seg: 86.1788, src.loss_imnet_feat_dist: nan
+2023-10-29 20:25:39,733 - mmseg - INFO - Iter [20150/40000]	lr: 2.978e-05, eta: 3:58:44, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2270, decode.acc_seg: 86.7542, src.loss_imnet_feat_dist: nan
+2023-10-29 20:26:15,900 - mmseg - INFO - Iter [20200/40000]	lr: 2.970e-05, eta: 3:58:08, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2268, decode.acc_seg: 86.4042, src.loss_imnet_feat_dist: nan
+2023-10-29 20:26:51,745 - mmseg - INFO - Iter [20250/40000]	lr: 2.963e-05, eta: 3:57:32, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2318, decode.acc_seg: 88.1675, src.loss_imnet_feat_dist: nan
+2023-10-29 20:27:27,580 - mmseg - INFO - Iter [20300/40000]	lr: 2.955e-05, eta: 3:56:55, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2591, decode.acc_seg: 86.9162, src.loss_imnet_feat_dist: nan
+2023-10-29 20:28:03,407 - mmseg - INFO - Iter [20350/40000]	lr: 2.948e-05, eta: 3:56:19, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2455, decode.acc_seg: 85.7607, src.loss_imnet_feat_dist: nan
+2023-10-29 20:28:39,230 - mmseg - INFO - Iter [20400/40000]	lr: 2.940e-05, eta: 3:55:43, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2276, decode.acc_seg: 88.4882, src.loss_imnet_feat_dist: nan
+2023-10-29 20:29:15,105 - mmseg - INFO - Iter [20450/40000]	lr: 2.933e-05, eta: 3:55:06, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2551, decode.acc_seg: 86.2635, src.loss_imnet_feat_dist: nan
+2023-10-29 20:29:50,907 - mmseg - INFO - Iter [20500/40000]	lr: 2.925e-05, eta: 3:54:30, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2501, decode.acc_seg: 86.1954, src.loss_imnet_feat_dist: nan
+2023-10-29 20:30:26,987 - mmseg - INFO - Iter [20550/40000]	lr: 2.918e-05, eta: 3:53:54, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2452, decode.acc_seg: 87.0634, src.loss_imnet_feat_dist: nan
+2023-10-29 20:31:02,908 - mmseg - INFO - Iter [20600/40000]	lr: 2.910e-05, eta: 3:53:18, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2359, decode.acc_seg: 86.7386, src.loss_imnet_feat_dist: nan
+2023-10-29 20:31:38,950 - mmseg - INFO - Iter [20650/40000]	lr: 2.903e-05, eta: 3:52:42, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2503, decode.acc_seg: 86.0975, src.loss_imnet_feat_dist: 0.1025
+2023-10-29 20:32:14,807 - mmseg - INFO - Iter [20700/40000]	lr: 2.895e-05, eta: 3:52:05, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2405, decode.acc_seg: 87.3404, src.loss_imnet_feat_dist: nan
+2023-10-29 20:32:50,669 - mmseg - INFO - Iter [20750/40000]	lr: 2.888e-05, eta: 3:51:29, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2427, decode.acc_seg: 86.9207, src.loss_imnet_feat_dist: nan
+2023-10-29 20:33:27,018 - mmseg - INFO - Iter [20800/40000]	lr: 2.880e-05, eta: 3:50:53, time: 0.727, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2100, decode.acc_seg: 88.4286, src.loss_imnet_feat_dist: nan
+2023-10-29 20:34:02,886 - mmseg - INFO - Iter [20850/40000]	lr: 2.873e-05, eta: 3:50:17, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2693, decode.acc_seg: 85.8326, src.loss_imnet_feat_dist: nan
+2023-10-29 20:34:38,690 - mmseg - INFO - Iter [20900/40000]	lr: 2.865e-05, eta: 3:49:41, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2460, decode.acc_seg: 86.8668, src.loss_imnet_feat_dist: nan
+2023-10-29 20:35:14,649 - mmseg - INFO - Iter [20950/40000]	lr: 2.858e-05, eta: 3:49:04, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2548, decode.acc_seg: 87.3242, src.loss_imnet_feat_dist: nan
+2023-10-29 20:35:50,903 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 20:35:50,903 - mmseg - INFO - Iter [21000/40000]	lr: 2.850e-05, eta: 3:48:29, time: 0.725, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2242, decode.acc_seg: 87.7534, src.loss_imnet_feat_dist: nan
+2023-10-29 20:36:26,766 - mmseg - INFO - Iter [21050/40000]	lr: 2.843e-05, eta: 3:47:52, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2383, decode.acc_seg: 86.7478, src.loss_imnet_feat_dist: nan
+2023-10-29 20:37:02,770 - mmseg - INFO - Iter [21100/40000]	lr: 2.835e-05, eta: 3:47:16, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2384, decode.acc_seg: 86.7752, src.loss_imnet_feat_dist: nan
+2023-10-29 20:37:38,600 - mmseg - INFO - Iter [21150/40000]	lr: 2.828e-05, eta: 3:46:40, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2596, decode.acc_seg: 86.9579, src.loss_imnet_feat_dist: nan
+2023-10-29 20:38:15,262 - mmseg - INFO - Iter [21200/40000]	lr: 2.820e-05, eta: 3:46:04, time: 0.733, data_time: 0.029, memory: 9476, decode.loss_seg: 0.2373, decode.acc_seg: 85.9391, src.loss_imnet_feat_dist: nan
+2023-10-29 20:38:51,586 - mmseg - INFO - Iter [21250/40000]	lr: 2.813e-05, eta: 3:45:28, time: 0.726, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2580, decode.acc_seg: 86.4181, src.loss_imnet_feat_dist: nan
+2023-10-29 20:39:27,364 - mmseg - INFO - Iter [21300/40000]	lr: 2.805e-05, eta: 3:44:52, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2233, decode.acc_seg: 86.7904, src.loss_imnet_feat_dist: 0.1065
+2023-10-29 20:40:03,124 - mmseg - INFO - Iter [21350/40000]	lr: 2.798e-05, eta: 3:44:16, time: 0.715, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2329, decode.acc_seg: 87.8061, src.loss_imnet_feat_dist: nan
+2023-10-29 20:40:38,938 - mmseg - INFO - Iter [21400/40000]	lr: 2.790e-05, eta: 3:43:39, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2297, decode.acc_seg: 89.1652, src.loss_imnet_feat_dist: nan
+2023-10-29 20:41:14,798 - mmseg - INFO - Iter [21450/40000]	lr: 2.783e-05, eta: 3:43:03, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2327, decode.acc_seg: 86.5712, src.loss_imnet_feat_dist: nan
+2023-10-29 20:41:50,679 - mmseg - INFO - Iter [21500/40000]	lr: 2.775e-05, eta: 3:42:27, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2544, decode.acc_seg: 86.1134, src.loss_imnet_feat_dist: 0.1080
+2023-10-29 20:42:26,552 - mmseg - INFO - Iter [21550/40000]	lr: 2.768e-05, eta: 3:41:51, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2132, decode.acc_seg: 88.4622, src.loss_imnet_feat_dist: nan
+2023-10-29 20:43:02,378 - mmseg - INFO - Iter [21600/40000]	lr: 2.760e-05, eta: 3:41:14, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2969, decode.acc_seg: 85.8174, src.loss_imnet_feat_dist: nan
+2023-10-29 20:43:38,176 - mmseg - INFO - Iter [21650/40000]	lr: 2.753e-05, eta: 3:40:38, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2458, decode.acc_seg: 87.6946, src.loss_imnet_feat_dist: 0.1045
+2023-10-29 20:44:14,157 - mmseg - INFO - Iter [21700/40000]	lr: 2.745e-05, eta: 3:40:02, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2367, decode.acc_seg: 86.8014, src.loss_imnet_feat_dist: nan
+2023-10-29 20:44:50,132 - mmseg - INFO - Iter [21750/40000]	lr: 2.738e-05, eta: 3:39:26, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2034, decode.acc_seg: 87.8575, src.loss_imnet_feat_dist: nan
+2023-10-29 20:45:26,262 - mmseg - INFO - Iter [21800/40000]	lr: 2.730e-05, eta: 3:38:50, time: 0.723, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2365, decode.acc_seg: 86.5402, src.loss_imnet_feat_dist: 0.1019
+2023-10-29 20:46:02,207 - mmseg - INFO - Iter [21850/40000]	lr: 2.723e-05, eta: 3:38:14, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2240, decode.acc_seg: 86.0597, src.loss_imnet_feat_dist: nan
+2023-10-29 20:46:38,080 - mmseg - INFO - Iter [21900/40000]	lr: 2.715e-05, eta: 3:37:37, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1887, decode.acc_seg: 88.1944, src.loss_imnet_feat_dist: nan
+2023-10-29 20:47:13,931 - mmseg - INFO - Iter [21950/40000]	lr: 2.708e-05, eta: 3:37:01, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2118, decode.acc_seg: 86.4628, src.loss_imnet_feat_dist: nan
+2023-10-29 20:47:50,072 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 20:47:50,072 - mmseg - INFO - Iter [22000/40000]	lr: 2.700e-05, eta: 3:36:25, time: 0.723, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2194, decode.acc_seg: 86.4272, src.loss_imnet_feat_dist: nan
+2023-10-29 20:48:26,461 - mmseg - INFO - Iter [22050/40000]	lr: 2.693e-05, eta: 3:35:49, time: 0.728, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2308, decode.acc_seg: 87.7595, src.loss_imnet_feat_dist: nan
+2023-10-29 20:49:02,395 - mmseg - INFO - Iter [22100/40000]	lr: 2.685e-05, eta: 3:35:13, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2202, decode.acc_seg: 87.7994, src.loss_imnet_feat_dist: nan
+2023-10-29 20:49:38,418 - mmseg - INFO - Iter [22150/40000]	lr: 2.678e-05, eta: 3:34:37, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2344, decode.acc_seg: 88.1889, src.loss_imnet_feat_dist: 0.1027
+2023-10-29 20:50:14,561 - mmseg - INFO - Iter [22200/40000]	lr: 2.670e-05, eta: 3:34:01, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2471, decode.acc_seg: 86.2037, src.loss_imnet_feat_dist: nan
+2023-10-29 20:50:50,452 - mmseg - INFO - Iter [22250/40000]	lr: 2.663e-05, eta: 3:33:25, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2124, decode.acc_seg: 86.6868, src.loss_imnet_feat_dist: nan
+2023-10-29 20:51:26,289 - mmseg - INFO - Iter [22300/40000]	lr: 2.655e-05, eta: 3:32:49, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2509, decode.acc_seg: 86.9515, src.loss_imnet_feat_dist: nan
+2023-10-29 20:52:02,203 - mmseg - INFO - Iter [22350/40000]	lr: 2.648e-05, eta: 3:32:12, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2303, decode.acc_seg: 86.9415, src.loss_imnet_feat_dist: nan
+2023-10-29 20:52:38,081 - mmseg - INFO - Iter [22400/40000]	lr: 2.640e-05, eta: 3:31:36, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2203, decode.acc_seg: 87.0482, src.loss_imnet_feat_dist: nan
+2023-10-29 20:53:13,912 - mmseg - INFO - Iter [22450/40000]	lr: 2.633e-05, eta: 3:31:00, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2409, decode.acc_seg: 87.3364, src.loss_imnet_feat_dist: nan
+2023-10-29 20:53:49,892 - mmseg - INFO - Iter [22500/40000]	lr: 2.625e-05, eta: 3:30:24, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2171, decode.acc_seg: 88.6177, src.loss_imnet_feat_dist: nan
+2023-10-29 20:54:25,810 - mmseg - INFO - Iter [22550/40000]	lr: 2.618e-05, eta: 3:29:48, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2153, decode.acc_seg: 88.0312, src.loss_imnet_feat_dist: nan
+2023-10-29 20:55:01,942 - mmseg - INFO - Iter [22600/40000]	lr: 2.610e-05, eta: 3:29:12, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2136, decode.acc_seg: 86.8331, src.loss_imnet_feat_dist: nan
+2023-10-29 20:55:37,824 - mmseg - INFO - Iter [22650/40000]	lr: 2.603e-05, eta: 3:28:35, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2108, decode.acc_seg: 87.0790, src.loss_imnet_feat_dist: nan
+2023-10-29 20:56:13,693 - mmseg - INFO - Iter [22700/40000]	lr: 2.595e-05, eta: 3:27:59, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2186, decode.acc_seg: 85.4889, src.loss_imnet_feat_dist: nan
+2023-10-29 20:56:49,595 - mmseg - INFO - Iter [22750/40000]	lr: 2.588e-05, eta: 3:27:23, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2263, decode.acc_seg: 87.2821, src.loss_imnet_feat_dist: nan
+2023-10-29 20:57:25,512 - mmseg - INFO - Iter [22800/40000]	lr: 2.580e-05, eta: 3:26:47, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2396, decode.acc_seg: 87.5303, src.loss_imnet_feat_dist: nan
+2023-10-29 20:58:01,574 - mmseg - INFO - Iter [22850/40000]	lr: 2.573e-05, eta: 3:26:11, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2423, decode.acc_seg: 86.3489, src.loss_imnet_feat_dist: nan
+2023-10-29 20:58:37,658 - mmseg - INFO - Iter [22900/40000]	lr: 2.565e-05, eta: 3:25:35, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2547, decode.acc_seg: 86.0702, src.loss_imnet_feat_dist: nan
+2023-10-29 20:59:13,554 - mmseg - INFO - Iter [22950/40000]	lr: 2.558e-05, eta: 3:24:58, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2511, decode.acc_seg: 87.5414, src.loss_imnet_feat_dist: 0.1070
+2023-10-29 20:59:49,724 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 20:59:49,724 - mmseg - INFO - Iter [23000/40000]	lr: 2.550e-05, eta: 3:24:22, time: 0.723, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2209, decode.acc_seg: 86.1721, src.loss_imnet_feat_dist: nan
+2023-10-29 21:00:25,622 - mmseg - INFO - Iter [23050/40000]	lr: 2.543e-05, eta: 3:23:46, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2635, decode.acc_seg: 87.7377, src.loss_imnet_feat_dist: nan
+2023-10-29 21:01:01,639 - mmseg - INFO - Iter [23100/40000]	lr: 2.535e-05, eta: 3:23:10, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2263, decode.acc_seg: 87.6978, src.loss_imnet_feat_dist: nan
+2023-10-29 21:01:37,489 - mmseg - INFO - Iter [23150/40000]	lr: 2.528e-05, eta: 3:22:34, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2120, decode.acc_seg: 87.6031, src.loss_imnet_feat_dist: nan
+2023-10-29 21:02:13,418 - mmseg - INFO - Iter [23200/40000]	lr: 2.520e-05, eta: 3:21:58, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.3054, decode.acc_seg: 84.8887, src.loss_imnet_feat_dist: nan
+2023-10-29 21:02:49,421 - mmseg - INFO - Iter [23250/40000]	lr: 2.513e-05, eta: 3:21:22, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.3011, decode.acc_seg: 85.6691, src.loss_imnet_feat_dist: nan
+2023-10-29 21:03:25,296 - mmseg - INFO - Iter [23300/40000]	lr: 2.505e-05, eta: 3:20:45, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2154, decode.acc_seg: 88.2585, src.loss_imnet_feat_dist: nan
+2023-10-29 21:04:01,213 - mmseg - INFO - Iter [23350/40000]	lr: 2.498e-05, eta: 3:20:09, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2513, decode.acc_seg: 86.7004, src.loss_imnet_feat_dist: nan
+2023-10-29 21:04:37,508 - mmseg - INFO - Iter [23400/40000]	lr: 2.490e-05, eta: 3:19:33, time: 0.726, data_time: 0.020, memory: 9476, decode.loss_seg: 0.2310, decode.acc_seg: 88.0676, src.loss_imnet_feat_dist: nan
+2023-10-29 21:05:13,357 - mmseg - INFO - Iter [23450/40000]	lr: 2.483e-05, eta: 3:18:57, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2333, decode.acc_seg: 87.7280, src.loss_imnet_feat_dist: nan
+2023-10-29 21:05:49,147 - mmseg - INFO - Iter [23500/40000]	lr: 2.475e-05, eta: 3:18:21, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2519, decode.acc_seg: 86.9769, src.loss_imnet_feat_dist: nan
+2023-10-29 21:06:25,052 - mmseg - INFO - Iter [23550/40000]	lr: 2.468e-05, eta: 3:17:45, time: 0.718, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2387, decode.acc_seg: 86.3873, src.loss_imnet_feat_dist: nan
+2023-10-29 21:07:00,931 - mmseg - INFO - Iter [23600/40000]	lr: 2.460e-05, eta: 3:17:08, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2753, decode.acc_seg: 84.2831, src.loss_imnet_feat_dist: nan
+2023-10-29 21:07:36,821 - mmseg - INFO - Iter [23650/40000]	lr: 2.453e-05, eta: 3:16:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2227, decode.acc_seg: 87.3164, src.loss_imnet_feat_dist: nan
+2023-10-29 21:08:13,384 - mmseg - INFO - Iter [23700/40000]	lr: 2.445e-05, eta: 3:15:57, time: 0.731, data_time: 0.026, memory: 9476, decode.loss_seg: 0.2512, decode.acc_seg: 87.7148, src.loss_imnet_feat_dist: nan
+2023-10-29 21:08:49,287 - mmseg - INFO - Iter [23750/40000]	lr: 2.438e-05, eta: 3:15:20, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2685, decode.acc_seg: 85.1965, src.loss_imnet_feat_dist: nan
+2023-10-29 21:09:25,276 - mmseg - INFO - Iter [23800/40000]	lr: 2.430e-05, eta: 3:14:44, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2294, decode.acc_seg: 87.0791, src.loss_imnet_feat_dist: nan
+2023-10-29 21:10:01,450 - mmseg - INFO - Iter [23850/40000]	lr: 2.423e-05, eta: 3:14:08, time: 0.723, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2335, decode.acc_seg: 86.8622, src.loss_imnet_feat_dist: nan
+2023-10-29 21:10:37,911 - mmseg - INFO - Iter [23900/40000]	lr: 2.415e-05, eta: 3:13:32, time: 0.729, data_time: 0.023, memory: 9476, decode.loss_seg: 0.2745, decode.acc_seg: 86.2053, src.loss_imnet_feat_dist: nan
+2023-10-29 21:11:13,863 - mmseg - INFO - Iter [23950/40000]	lr: 2.408e-05, eta: 3:12:56, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2197, decode.acc_seg: 88.4818, src.loss_imnet_feat_dist: nan
+2023-10-29 21:11:49,850 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 21:11:49,850 - mmseg - INFO - Iter [24000/40000]	lr: 2.400e-05, eta: 3:12:20, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2026, decode.acc_seg: 87.1004, src.loss_imnet_feat_dist: nan
+2023-10-29 21:12:25,786 - mmseg - INFO - Iter [24050/40000]	lr: 2.393e-05, eta: 3:11:44, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2163, decode.acc_seg: 87.7365, src.loss_imnet_feat_dist: nan
+2023-10-29 21:13:01,810 - mmseg - INFO - Iter [24100/40000]	lr: 2.385e-05, eta: 3:11:08, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2478, decode.acc_seg: 87.4377, src.loss_imnet_feat_dist: nan
+2023-10-29 21:13:37,727 - mmseg - INFO - Iter [24150/40000]	lr: 2.378e-05, eta: 3:10:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2160, decode.acc_seg: 88.0216, src.loss_imnet_feat_dist: nan
+2023-10-29 21:14:13,741 - mmseg - INFO - Iter [24200/40000]	lr: 2.370e-05, eta: 3:09:56, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2374, decode.acc_seg: 86.6040, src.loss_imnet_feat_dist: 0.0998
+2023-10-29 21:14:49,776 - mmseg - INFO - Iter [24250/40000]	lr: 2.363e-05, eta: 3:09:20, time: 0.721, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2059, decode.acc_seg: 88.8445, src.loss_imnet_feat_dist: nan
+2023-10-29 21:15:25,722 - mmseg - INFO - Iter [24300/40000]	lr: 2.355e-05, eta: 3:08:44, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2388, decode.acc_seg: 88.2930, src.loss_imnet_feat_dist: nan
+2023-10-29 21:16:01,618 - mmseg - INFO - Iter [24350/40000]	lr: 2.348e-05, eta: 3:08:07, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2342, decode.acc_seg: 84.8331, src.loss_imnet_feat_dist: nan
+2023-10-29 21:16:37,543 - mmseg - INFO - Iter [24400/40000]	lr: 2.340e-05, eta: 3:07:31, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2189, decode.acc_seg: 88.0331, src.loss_imnet_feat_dist: nan
+2023-10-29 21:17:13,468 - mmseg - INFO - Iter [24450/40000]	lr: 2.333e-05, eta: 3:06:55, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2374, decode.acc_seg: 85.0670, src.loss_imnet_feat_dist: nan
+2023-10-29 21:17:49,314 - mmseg - INFO - Iter [24500/40000]	lr: 2.325e-05, eta: 3:06:19, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2297, decode.acc_seg: 86.5546, src.loss_imnet_feat_dist: nan
+2023-10-29 21:18:25,170 - mmseg - INFO - Iter [24550/40000]	lr: 2.318e-05, eta: 3:05:43, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2525, decode.acc_seg: 85.2351, src.loss_imnet_feat_dist: nan
+2023-10-29 21:19:01,103 - mmseg - INFO - Iter [24600/40000]	lr: 2.310e-05, eta: 3:05:06, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2163, decode.acc_seg: 87.7558, src.loss_imnet_feat_dist: nan
+2023-10-29 21:19:36,992 - mmseg - INFO - Iter [24650/40000]	lr: 2.303e-05, eta: 3:04:30, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2300, decode.acc_seg: 88.1987, src.loss_imnet_feat_dist: nan
+2023-10-29 21:20:12,827 - mmseg - INFO - Iter [24700/40000]	lr: 2.295e-05, eta: 3:03:54, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2267, decode.acc_seg: 87.4321, src.loss_imnet_feat_dist: nan
+2023-10-29 21:20:48,748 - mmseg - INFO - Iter [24750/40000]	lr: 2.288e-05, eta: 3:03:18, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2490, decode.acc_seg: 85.3107, src.loss_imnet_feat_dist: 0.1044
+2023-10-29 21:21:24,660 - mmseg - INFO - Iter [24800/40000]	lr: 2.280e-05, eta: 3:02:42, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2678, decode.acc_seg: 86.6590, src.loss_imnet_feat_dist: nan
+2023-10-29 21:22:00,780 - mmseg - INFO - Iter [24850/40000]	lr: 2.273e-05, eta: 3:02:06, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2201, decode.acc_seg: 87.5496, src.loss_imnet_feat_dist: nan
+2023-10-29 21:22:36,673 - mmseg - INFO - Iter [24900/40000]	lr: 2.265e-05, eta: 3:01:30, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2485, decode.acc_seg: 87.0494, src.loss_imnet_feat_dist: nan
+2023-10-29 21:23:13,186 - mmseg - INFO - Iter [24950/40000]	lr: 2.258e-05, eta: 3:00:54, time: 0.730, data_time: 0.025, memory: 9476, decode.loss_seg: 0.2256, decode.acc_seg: 87.6952, src.loss_imnet_feat_dist: nan
+2023-10-29 21:23:49,021 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 21:23:49,022 - mmseg - INFO - Iter [25000/40000]	lr: 2.250e-05, eta: 3:00:18, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2277, decode.acc_seg: 88.0056, src.loss_imnet_feat_dist: 0.1009
+2023-10-29 21:24:24,916 - mmseg - INFO - Iter [25050/40000]	lr: 2.243e-05, eta: 2:59:41, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2528, decode.acc_seg: 86.1586, src.loss_imnet_feat_dist: nan
+2023-10-29 21:25:01,252 - mmseg - INFO - Iter [25100/40000]	lr: 2.235e-05, eta: 2:59:06, time: 0.727, data_time: 0.021, memory: 9476, decode.loss_seg: 0.1983, decode.acc_seg: 89.6456, src.loss_imnet_feat_dist: nan
+2023-10-29 21:25:37,077 - mmseg - INFO - Iter [25150/40000]	lr: 2.228e-05, eta: 2:58:29, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2477, decode.acc_seg: 85.8636, src.loss_imnet_feat_dist: nan
+2023-10-29 21:26:13,022 - mmseg - INFO - Iter [25200/40000]	lr: 2.220e-05, eta: 2:57:53, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2307, decode.acc_seg: 86.5303, src.loss_imnet_feat_dist: nan
+2023-10-29 21:26:49,006 - mmseg - INFO - Iter [25250/40000]	lr: 2.213e-05, eta: 2:57:17, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2485, decode.acc_seg: 87.7393, src.loss_imnet_feat_dist: nan
+2023-10-29 21:27:24,980 - mmseg - INFO - Iter [25300/40000]	lr: 2.205e-05, eta: 2:56:41, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.1922, decode.acc_seg: 87.5279, src.loss_imnet_feat_dist: nan
+2023-10-29 21:28:01,157 - mmseg - INFO - Iter [25350/40000]	lr: 2.198e-05, eta: 2:56:05, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2285, decode.acc_seg: 87.6522, src.loss_imnet_feat_dist: nan
+2023-10-29 21:28:37,079 - mmseg - INFO - Iter [25400/40000]	lr: 2.190e-05, eta: 2:55:29, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2173, decode.acc_seg: 88.7555, src.loss_imnet_feat_dist: nan
+2023-10-29 21:29:12,983 - mmseg - INFO - Iter [25450/40000]	lr: 2.183e-05, eta: 2:54:53, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2418, decode.acc_seg: 86.2358, src.loss_imnet_feat_dist: nan
+2023-10-29 21:29:48,874 - mmseg - INFO - Iter [25500/40000]	lr: 2.175e-05, eta: 2:54:17, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2540, decode.acc_seg: 87.1017, src.loss_imnet_feat_dist: nan
+2023-10-29 21:30:24,705 - mmseg - INFO - Iter [25550/40000]	lr: 2.168e-05, eta: 2:53:40, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2002, decode.acc_seg: 87.4772, src.loss_imnet_feat_dist: nan
+2023-10-29 21:31:00,998 - mmseg - INFO - Iter [25600/40000]	lr: 2.160e-05, eta: 2:53:05, time: 0.726, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2228, decode.acc_seg: 87.1195, src.loss_imnet_feat_dist: nan
+2023-10-29 21:31:36,866 - mmseg - INFO - Iter [25650/40000]	lr: 2.153e-05, eta: 2:52:28, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2080, decode.acc_seg: 87.8372, src.loss_imnet_feat_dist: nan
+2023-10-29 21:32:12,754 - mmseg - INFO - Iter [25700/40000]	lr: 2.145e-05, eta: 2:51:52, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2501, decode.acc_seg: 86.6670, src.loss_imnet_feat_dist: nan
+2023-10-29 21:32:48,636 - mmseg - INFO - Iter [25750/40000]	lr: 2.138e-05, eta: 2:51:16, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2764, decode.acc_seg: 85.3893, src.loss_imnet_feat_dist: nan
+2023-10-29 21:33:24,538 - mmseg - INFO - Iter [25800/40000]	lr: 2.130e-05, eta: 2:50:40, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2146, decode.acc_seg: 87.6935, src.loss_imnet_feat_dist: nan
+2023-10-29 21:34:00,352 - mmseg - INFO - Iter [25850/40000]	lr: 2.123e-05, eta: 2:50:04, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2469, decode.acc_seg: 87.0934, src.loss_imnet_feat_dist: nan
+2023-10-29 21:34:36,254 - mmseg - INFO - Iter [25900/40000]	lr: 2.115e-05, eta: 2:49:28, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2205, decode.acc_seg: 87.1208, src.loss_imnet_feat_dist: nan
+2023-10-29 21:35:12,120 - mmseg - INFO - Iter [25950/40000]	lr: 2.108e-05, eta: 2:48:51, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2083, decode.acc_seg: 87.9099, src.loss_imnet_feat_dist: nan
+2023-10-29 21:35:48,100 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 21:35:48,101 - mmseg - INFO - Iter [26000/40000]	lr: 2.100e-05, eta: 2:48:15, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2364, decode.acc_seg: 87.4693, src.loss_imnet_feat_dist: 0.1003
+2023-10-29 21:36:26,265 - mmseg - INFO - Iter [26050/40000]	lr: 2.093e-05, eta: 2:47:40, time: 0.763, data_time: 0.057, memory: 9476, decode.loss_seg: 0.2286, decode.acc_seg: 88.4675, src.loss_imnet_feat_dist: nan
+2023-10-29 21:37:02,204 - mmseg - INFO - Iter [26100/40000]	lr: 2.085e-05, eta: 2:47:04, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2105, decode.acc_seg: 88.2993, src.loss_imnet_feat_dist: 0.1031
+2023-10-29 21:37:38,263 - mmseg - INFO - Iter [26150/40000]	lr: 2.078e-05, eta: 2:46:28, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2034, decode.acc_seg: 87.0765, src.loss_imnet_feat_dist: nan
+2023-10-29 21:38:14,438 - mmseg - INFO - Iter [26200/40000]	lr: 2.070e-05, eta: 2:45:52, time: 0.724, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2117, decode.acc_seg: 87.7722, src.loss_imnet_feat_dist: nan
+2023-10-29 21:38:50,383 - mmseg - INFO - Iter [26250/40000]	lr: 2.063e-05, eta: 2:45:16, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2387, decode.acc_seg: 87.4523, src.loss_imnet_feat_dist: nan
+2023-10-29 21:39:26,387 - mmseg - INFO - Iter [26300/40000]	lr: 2.055e-05, eta: 2:44:40, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1993, decode.acc_seg: 87.9124, src.loss_imnet_feat_dist: 0.0975
+2023-10-29 21:40:02,403 - mmseg - INFO - Iter [26350/40000]	lr: 2.048e-05, eta: 2:44:04, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2230, decode.acc_seg: 88.1117, src.loss_imnet_feat_dist: nan
+2023-10-29 21:40:38,302 - mmseg - INFO - Iter [26400/40000]	lr: 2.040e-05, eta: 2:43:28, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2197, decode.acc_seg: 85.9327, src.loss_imnet_feat_dist: nan
+2023-10-29 21:41:14,317 - mmseg - INFO - Iter [26450/40000]	lr: 2.033e-05, eta: 2:42:52, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2590, decode.acc_seg: 86.4838, src.loss_imnet_feat_dist: nan
+2023-10-29 21:41:50,167 - mmseg - INFO - Iter [26500/40000]	lr: 2.025e-05, eta: 2:42:15, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2083, decode.acc_seg: 87.1882, src.loss_imnet_feat_dist: nan
+2023-10-29 21:42:26,093 - mmseg - INFO - Iter [26550/40000]	lr: 2.018e-05, eta: 2:41:39, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2497, decode.acc_seg: 86.6025, src.loss_imnet_feat_dist: nan
+2023-10-29 21:43:02,195 - mmseg - INFO - Iter [26600/40000]	lr: 2.010e-05, eta: 2:41:03, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1908, decode.acc_seg: 87.8601, src.loss_imnet_feat_dist: nan
+2023-10-29 21:43:38,130 - mmseg - INFO - Iter [26650/40000]	lr: 2.003e-05, eta: 2:40:27, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2036, decode.acc_seg: 87.9589, src.loss_imnet_feat_dist: nan
+2023-10-29 21:44:14,033 - mmseg - INFO - Iter [26700/40000]	lr: 1.995e-05, eta: 2:39:51, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2173, decode.acc_seg: 88.0397, src.loss_imnet_feat_dist: nan
+2023-10-29 21:44:50,153 - mmseg - INFO - Iter [26750/40000]	lr: 1.988e-05, eta: 2:39:15, time: 0.722, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2039, decode.acc_seg: 88.7136, src.loss_imnet_feat_dist: nan
+2023-10-29 21:45:26,033 - mmseg - INFO - Iter [26800/40000]	lr: 1.980e-05, eta: 2:38:39, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1921, decode.acc_seg: 87.9269, src.loss_imnet_feat_dist: nan
+2023-10-29 21:46:02,085 - mmseg - INFO - Iter [26850/40000]	lr: 1.973e-05, eta: 2:38:03, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2256, decode.acc_seg: 86.3057, src.loss_imnet_feat_dist: nan
+2023-10-29 21:46:37,926 - mmseg - INFO - Iter [26900/40000]	lr: 1.965e-05, eta: 2:37:27, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2213, decode.acc_seg: 87.6549, src.loss_imnet_feat_dist: nan
+2023-10-29 21:47:13,823 - mmseg - INFO - Iter [26950/40000]	lr: 1.958e-05, eta: 2:36:51, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2039, decode.acc_seg: 88.3296, src.loss_imnet_feat_dist: nan
+2023-10-29 21:47:49,788 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 21:47:49,788 - mmseg - INFO - Iter [27000/40000]	lr: 1.950e-05, eta: 2:36:14, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2048, decode.acc_seg: 89.1382, src.loss_imnet_feat_dist: nan
+2023-10-29 21:48:25,749 - mmseg - INFO - Iter [27050/40000]	lr: 1.943e-05, eta: 2:35:38, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2537, decode.acc_seg: 87.2055, src.loss_imnet_feat_dist: nan
+2023-10-29 21:49:01,789 - mmseg - INFO - Iter [27100/40000]	lr: 1.935e-05, eta: 2:35:02, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2047, decode.acc_seg: 87.7812, src.loss_imnet_feat_dist: nan
+2023-10-29 21:49:37,765 - mmseg - INFO - Iter [27150/40000]	lr: 1.928e-05, eta: 2:34:26, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2259, decode.acc_seg: 87.0723, src.loss_imnet_feat_dist: nan
+2023-10-29 21:50:13,768 - mmseg - INFO - Iter [27200/40000]	lr: 1.920e-05, eta: 2:33:50, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2395, decode.acc_seg: 87.7264, src.loss_imnet_feat_dist: nan
+2023-10-29 21:50:49,611 - mmseg - INFO - Iter [27250/40000]	lr: 1.913e-05, eta: 2:33:14, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2073, decode.acc_seg: 88.4504, src.loss_imnet_feat_dist: nan
+2023-10-29 21:51:25,471 - mmseg - INFO - Iter [27300/40000]	lr: 1.905e-05, eta: 2:32:38, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1749, decode.acc_seg: 88.1601, src.loss_imnet_feat_dist: nan
+2023-10-29 21:52:01,353 - mmseg - INFO - Iter [27350/40000]	lr: 1.898e-05, eta: 2:32:02, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2163, decode.acc_seg: 87.0752, src.loss_imnet_feat_dist: nan
+2023-10-29 21:52:37,272 - mmseg - INFO - Iter [27400/40000]	lr: 1.890e-05, eta: 2:31:26, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2215, decode.acc_seg: 86.2413, src.loss_imnet_feat_dist: nan
+2023-10-29 21:53:13,200 - mmseg - INFO - Iter [27450/40000]	lr: 1.883e-05, eta: 2:30:49, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2036, decode.acc_seg: 88.4090, src.loss_imnet_feat_dist: nan
+2023-10-29 21:53:49,080 - mmseg - INFO - Iter [27500/40000]	lr: 1.875e-05, eta: 2:30:13, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1994, decode.acc_seg: 88.9026, src.loss_imnet_feat_dist: nan
+2023-10-29 21:54:24,950 - mmseg - INFO - Iter [27550/40000]	lr: 1.868e-05, eta: 2:29:37, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2290, decode.acc_seg: 87.9132, src.loss_imnet_feat_dist: nan
+2023-10-29 21:55:00,855 - mmseg - INFO - Iter [27600/40000]	lr: 1.860e-05, eta: 2:29:01, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1944, decode.acc_seg: 87.9464, src.loss_imnet_feat_dist: nan
+2023-10-29 21:55:36,759 - mmseg - INFO - Iter [27650/40000]	lr: 1.853e-05, eta: 2:28:25, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2186, decode.acc_seg: 88.0555, src.loss_imnet_feat_dist: nan
+2023-10-29 21:56:12,619 - mmseg - INFO - Iter [27700/40000]	lr: 1.845e-05, eta: 2:27:49, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2591, decode.acc_seg: 87.3669, src.loss_imnet_feat_dist: nan
+2023-10-29 21:56:48,444 - mmseg - INFO - Iter [27750/40000]	lr: 1.838e-05, eta: 2:27:13, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2140, decode.acc_seg: 87.7420, src.loss_imnet_feat_dist: nan
+2023-10-29 21:57:24,265 - mmseg - INFO - Iter [27800/40000]	lr: 1.830e-05, eta: 2:26:36, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2105, decode.acc_seg: 87.8324, src.loss_imnet_feat_dist: nan
+2023-10-29 21:58:00,125 - mmseg - INFO - Iter [27850/40000]	lr: 1.823e-05, eta: 2:26:00, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2169, decode.acc_seg: 88.2617, src.loss_imnet_feat_dist: nan
+2023-10-29 21:58:36,048 - mmseg - INFO - Iter [27900/40000]	lr: 1.815e-05, eta: 2:25:24, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2181, decode.acc_seg: 87.3515, src.loss_imnet_feat_dist: nan
+2023-10-29 21:59:11,946 - mmseg - INFO - Iter [27950/40000]	lr: 1.808e-05, eta: 2:24:48, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2009, decode.acc_seg: 87.9123, src.loss_imnet_feat_dist: nan
+2023-10-29 21:59:47,759 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 21:59:47,760 - mmseg - INFO - Iter [28000/40000]	lr: 1.800e-05, eta: 2:24:12, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2519, decode.acc_seg: 87.5024, src.loss_imnet_feat_dist: nan
+2023-10-29 22:00:23,914 - mmseg - INFO - Iter [28050/40000]	lr: 1.793e-05, eta: 2:23:36, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2131, decode.acc_seg: 87.8029, src.loss_imnet_feat_dist: 0.0945
+2023-10-29 22:00:59,817 - mmseg - INFO - Iter [28100/40000]	lr: 1.785e-05, eta: 2:23:00, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1951, decode.acc_seg: 88.6521, src.loss_imnet_feat_dist: nan
+2023-10-29 22:01:35,827 - mmseg - INFO - Iter [28150/40000]	lr: 1.778e-05, eta: 2:22:24, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2140, decode.acc_seg: 87.5006, src.loss_imnet_feat_dist: nan
+2023-10-29 22:02:11,761 - mmseg - INFO - Iter [28200/40000]	lr: 1.770e-05, eta: 2:21:48, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2572, decode.acc_seg: 86.5118, src.loss_imnet_feat_dist: nan
+2023-10-29 22:02:48,013 - mmseg - INFO - Iter [28250/40000]	lr: 1.763e-05, eta: 2:21:12, time: 0.725, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2272, decode.acc_seg: 87.9821, src.loss_imnet_feat_dist: nan
+2023-10-29 22:03:24,033 - mmseg - INFO - Iter [28300/40000]	lr: 1.755e-05, eta: 2:20:36, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2663, decode.acc_seg: 86.9993, src.loss_imnet_feat_dist: nan
+2023-10-29 22:03:59,915 - mmseg - INFO - Iter [28350/40000]	lr: 1.748e-05, eta: 2:19:59, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2232, decode.acc_seg: 87.7888, src.loss_imnet_feat_dist: nan
+2023-10-29 22:04:35,908 - mmseg - INFO - Iter [28400/40000]	lr: 1.740e-05, eta: 2:19:23, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2059, decode.acc_seg: 87.0204, src.loss_imnet_feat_dist: nan
+2023-10-29 22:05:12,087 - mmseg - INFO - Iter [28450/40000]	lr: 1.733e-05, eta: 2:18:47, time: 0.724, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2138, decode.acc_seg: 85.2264, src.loss_imnet_feat_dist: nan
+2023-10-29 22:05:48,230 - mmseg - INFO - Iter [28500/40000]	lr: 1.725e-05, eta: 2:18:11, time: 0.723, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2028, decode.acc_seg: 87.7883, src.loss_imnet_feat_dist: nan
+2023-10-29 22:06:24,160 - mmseg - INFO - Iter [28550/40000]	lr: 1.718e-05, eta: 2:17:35, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2121, decode.acc_seg: 87.0853, src.loss_imnet_feat_dist: nan
+2023-10-29 22:07:00,026 - mmseg - INFO - Iter [28600/40000]	lr: 1.710e-05, eta: 2:16:59, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2580, decode.acc_seg: 85.3469, src.loss_imnet_feat_dist: nan
+2023-10-29 22:07:36,014 - mmseg - INFO - Iter [28650/40000]	lr: 1.703e-05, eta: 2:16:23, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2399, decode.acc_seg: 88.0367, src.loss_imnet_feat_dist: nan
+2023-10-29 22:08:11,977 - mmseg - INFO - Iter [28700/40000]	lr: 1.695e-05, eta: 2:15:47, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2076, decode.acc_seg: 86.5570, src.loss_imnet_feat_dist: 0.0979
+2023-10-29 22:08:48,420 - mmseg - INFO - Iter [28750/40000]	lr: 1.688e-05, eta: 2:15:11, time: 0.729, data_time: 0.023, memory: 9476, decode.loss_seg: 0.1999, decode.acc_seg: 87.9082, src.loss_imnet_feat_dist: nan
+2023-10-29 22:09:24,346 - mmseg - INFO - Iter [28800/40000]	lr: 1.680e-05, eta: 2:14:35, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2413, decode.acc_seg: 86.9020, src.loss_imnet_feat_dist: nan
+2023-10-29 22:10:00,176 - mmseg - INFO - Iter [28850/40000]	lr: 1.673e-05, eta: 2:13:59, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2373, decode.acc_seg: 87.9206, src.loss_imnet_feat_dist: nan
+2023-10-29 22:10:36,530 - mmseg - INFO - Iter [28900/40000]	lr: 1.665e-05, eta: 2:13:23, time: 0.727, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2245, decode.acc_seg: 88.6315, src.loss_imnet_feat_dist: nan
+2023-10-29 22:11:12,672 - mmseg - INFO - Iter [28950/40000]	lr: 1.658e-05, eta: 2:12:47, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2046, decode.acc_seg: 87.4236, src.loss_imnet_feat_dist: nan
+2023-10-29 22:11:48,820 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 22:11:48,821 - mmseg - INFO - Iter [29000/40000]	lr: 1.650e-05, eta: 2:12:11, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2115, decode.acc_seg: 88.4456, src.loss_imnet_feat_dist: nan
+2023-10-29 22:12:24,688 - mmseg - INFO - Iter [29050/40000]	lr: 1.643e-05, eta: 2:11:35, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1995, decode.acc_seg: 88.4124, src.loss_imnet_feat_dist: 0.1008
+2023-10-29 22:13:00,520 - mmseg - INFO - Iter [29100/40000]	lr: 1.635e-05, eta: 2:10:59, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2039, decode.acc_seg: 87.2207, src.loss_imnet_feat_dist: 0.0927
+2023-10-29 22:13:36,655 - mmseg - INFO - Iter [29150/40000]	lr: 1.628e-05, eta: 2:10:23, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2430, decode.acc_seg: 85.5245, src.loss_imnet_feat_dist: nan
+2023-10-29 22:14:13,583 - mmseg - INFO - Iter [29200/40000]	lr: 1.620e-05, eta: 2:09:47, time: 0.739, data_time: 0.033, memory: 9476, decode.loss_seg: 0.2330, decode.acc_seg: 87.1787, src.loss_imnet_feat_dist: nan
+2023-10-29 22:14:49,455 - mmseg - INFO - Iter [29250/40000]	lr: 1.613e-05, eta: 2:09:11, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2243, decode.acc_seg: 87.9675, src.loss_imnet_feat_dist: nan
+2023-10-29 22:15:25,316 - mmseg - INFO - Iter [29300/40000]	lr: 1.605e-05, eta: 2:08:35, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2279, decode.acc_seg: 87.1789, src.loss_imnet_feat_dist: nan
+2023-10-29 22:16:01,150 - mmseg - INFO - Iter [29350/40000]	lr: 1.598e-05, eta: 2:07:59, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1847, decode.acc_seg: 88.4359, src.loss_imnet_feat_dist: nan
+2023-10-29 22:16:36,961 - mmseg - INFO - Iter [29400/40000]	lr: 1.590e-05, eta: 2:07:22, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2046, decode.acc_seg: 87.3778, src.loss_imnet_feat_dist: nan
+2023-10-29 22:17:12,900 - mmseg - INFO - Iter [29450/40000]	lr: 1.583e-05, eta: 2:06:46, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2174, decode.acc_seg: 87.9660, src.loss_imnet_feat_dist: nan
+2023-10-29 22:17:48,733 - mmseg - INFO - Iter [29500/40000]	lr: 1.575e-05, eta: 2:06:10, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2123, decode.acc_seg: 88.1236, src.loss_imnet_feat_dist: nan
+2023-10-29 22:18:24,564 - mmseg - INFO - Iter [29550/40000]	lr: 1.568e-05, eta: 2:05:34, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2052, decode.acc_seg: 87.7443, src.loss_imnet_feat_dist: nan
+2023-10-29 22:19:00,400 - mmseg - INFO - Iter [29600/40000]	lr: 1.560e-05, eta: 2:04:58, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1996, decode.acc_seg: 87.9774, src.loss_imnet_feat_dist: nan
+2023-10-29 22:19:36,492 - mmseg - INFO - Iter [29650/40000]	lr: 1.553e-05, eta: 2:04:22, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.1993, decode.acc_seg: 87.4242, src.loss_imnet_feat_dist: 0.0971
+2023-10-29 22:20:12,365 - mmseg - INFO - Iter [29700/40000]	lr: 1.545e-05, eta: 2:03:46, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2151, decode.acc_seg: 87.4759, src.loss_imnet_feat_dist: 0.0960
+2023-10-29 22:20:48,244 - mmseg - INFO - Iter [29750/40000]	lr: 1.538e-05, eta: 2:03:10, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2176, decode.acc_seg: 87.4031, src.loss_imnet_feat_dist: nan
+2023-10-29 22:21:24,113 - mmseg - INFO - Iter [29800/40000]	lr: 1.530e-05, eta: 2:02:34, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2169, decode.acc_seg: 87.5272, src.loss_imnet_feat_dist: nan
+2023-10-29 22:22:00,010 - mmseg - INFO - Iter [29850/40000]	lr: 1.523e-05, eta: 2:01:57, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2225, decode.acc_seg: 88.3695, src.loss_imnet_feat_dist: nan
+2023-10-29 22:22:36,526 - mmseg - INFO - Iter [29900/40000]	lr: 1.515e-05, eta: 2:01:22, time: 0.730, data_time: 0.025, memory: 9476, decode.loss_seg: 0.2128, decode.acc_seg: 87.5174, src.loss_imnet_feat_dist: nan
+2023-10-29 22:23:12,307 - mmseg - INFO - Iter [29950/40000]	lr: 1.508e-05, eta: 2:00:45, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2012, decode.acc_seg: 89.1514, src.loss_imnet_feat_dist: nan
+2023-10-29 22:23:48,388 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 22:23:48,388 - mmseg - INFO - Iter [30000/40000]	lr: 1.500e-05, eta: 2:00:09, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2322, decode.acc_seg: 88.2805, src.loss_imnet_feat_dist: nan
+2023-10-29 22:24:24,240 - mmseg - INFO - Iter [30050/40000]	lr: 1.493e-05, eta: 1:59:33, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1935, decode.acc_seg: 87.9445, src.loss_imnet_feat_dist: nan
+2023-10-29 22:25:00,292 - mmseg - INFO - Iter [30100/40000]	lr: 1.485e-05, eta: 1:58:57, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2326, decode.acc_seg: 86.6097, src.loss_imnet_feat_dist: nan
+2023-10-29 22:25:36,176 - mmseg - INFO - Iter [30150/40000]	lr: 1.478e-05, eta: 1:58:21, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1865, decode.acc_seg: 88.8538, src.loss_imnet_feat_dist: nan
+2023-10-29 22:26:12,070 - mmseg - INFO - Iter [30200/40000]	lr: 1.470e-05, eta: 1:57:45, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2358, decode.acc_seg: 87.0314, src.loss_imnet_feat_dist: nan
+2023-10-29 22:26:48,141 - mmseg - INFO - Iter [30250/40000]	lr: 1.463e-05, eta: 1:57:09, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1650, decode.acc_seg: 89.5328, src.loss_imnet_feat_dist: 0.0931
+2023-10-29 22:27:25,316 - mmseg - INFO - Iter [30300/40000]	lr: 1.455e-05, eta: 1:56:33, time: 0.744, data_time: 0.037, memory: 9476, decode.loss_seg: 0.2191, decode.acc_seg: 88.2588, src.loss_imnet_feat_dist: nan
+2023-10-29 22:28:01,297 - mmseg - INFO - Iter [30350/40000]	lr: 1.448e-05, eta: 1:55:57, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2072, decode.acc_seg: 88.9992, src.loss_imnet_feat_dist: nan
+2023-10-29 22:28:37,639 - mmseg - INFO - Iter [30400/40000]	lr: 1.440e-05, eta: 1:55:21, time: 0.727, data_time: 0.021, memory: 9476, decode.loss_seg: 0.2123, decode.acc_seg: 88.8448, src.loss_imnet_feat_dist: nan
+2023-10-29 22:29:13,894 - mmseg - INFO - Iter [30450/40000]	lr: 1.433e-05, eta: 1:54:45, time: 0.725, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2238, decode.acc_seg: 87.6465, src.loss_imnet_feat_dist: nan
+2023-10-29 22:29:49,762 - mmseg - INFO - Iter [30500/40000]	lr: 1.425e-05, eta: 1:54:09, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2427, decode.acc_seg: 87.7432, src.loss_imnet_feat_dist: 0.1011
+2023-10-29 22:30:25,876 - mmseg - INFO - Iter [30550/40000]	lr: 1.418e-05, eta: 1:53:33, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.1937, decode.acc_seg: 87.5785, src.loss_imnet_feat_dist: nan
+2023-10-29 22:31:01,807 - mmseg - INFO - Iter [30600/40000]	lr: 1.410e-05, eta: 1:52:57, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2118, decode.acc_seg: 88.1314, src.loss_imnet_feat_dist: nan
+2023-10-29 22:31:37,696 - mmseg - INFO - Iter [30650/40000]	lr: 1.403e-05, eta: 1:52:21, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2193, decode.acc_seg: 87.5204, src.loss_imnet_feat_dist: nan
+2023-10-29 22:32:13,930 - mmseg - INFO - Iter [30700/40000]	lr: 1.395e-05, eta: 1:51:45, time: 0.725, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2132, decode.acc_seg: 88.3368, src.loss_imnet_feat_dist: nan
+2023-10-29 22:32:49,751 - mmseg - INFO - Iter [30750/40000]	lr: 1.388e-05, eta: 1:51:09, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2163, decode.acc_seg: 89.4915, src.loss_imnet_feat_dist: nan
+2023-10-29 22:33:25,650 - mmseg - INFO - Iter [30800/40000]	lr: 1.380e-05, eta: 1:50:33, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1943, decode.acc_seg: 88.1925, src.loss_imnet_feat_dist: nan
+2023-10-29 22:34:01,539 - mmseg - INFO - Iter [30850/40000]	lr: 1.373e-05, eta: 1:49:57, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2205, decode.acc_seg: 86.3685, src.loss_imnet_feat_dist: nan
+2023-10-29 22:34:37,994 - mmseg - INFO - Iter [30900/40000]	lr: 1.365e-05, eta: 1:49:21, time: 0.729, data_time: 0.024, memory: 9476, decode.loss_seg: 0.2257, decode.acc_seg: 87.1748, src.loss_imnet_feat_dist: nan
+2023-10-29 22:35:14,110 - mmseg - INFO - Iter [30950/40000]	lr: 1.358e-05, eta: 1:48:45, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2210, decode.acc_seg: 86.6613, src.loss_imnet_feat_dist: nan
+2023-10-29 22:35:50,120 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 22:35:50,120 - mmseg - INFO - Iter [31000/40000]	lr: 1.350e-05, eta: 1:48:09, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2844, decode.acc_seg: 85.2351, src.loss_imnet_feat_dist: nan
+2023-10-29 22:36:25,982 - mmseg - INFO - Iter [31050/40000]	lr: 1.343e-05, eta: 1:47:32, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2152, decode.acc_seg: 89.0211, src.loss_imnet_feat_dist: nan
+2023-10-29 22:37:01,826 - mmseg - INFO - Iter [31100/40000]	lr: 1.335e-05, eta: 1:46:56, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2245, decode.acc_seg: 87.4038, src.loss_imnet_feat_dist: nan
+2023-10-29 22:37:37,740 - mmseg - INFO - Iter [31150/40000]	lr: 1.328e-05, eta: 1:46:20, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2239, decode.acc_seg: 88.1623, src.loss_imnet_feat_dist: nan
+2023-10-29 22:38:13,556 - mmseg - INFO - Iter [31200/40000]	lr: 1.320e-05, eta: 1:45:44, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1889, decode.acc_seg: 89.9338, src.loss_imnet_feat_dist: nan
+2023-10-29 22:38:49,441 - mmseg - INFO - Iter [31250/40000]	lr: 1.313e-05, eta: 1:45:08, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2262, decode.acc_seg: 87.9432, src.loss_imnet_feat_dist: nan
+2023-10-29 22:39:25,335 - mmseg - INFO - Iter [31300/40000]	lr: 1.305e-05, eta: 1:44:32, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1968, decode.acc_seg: 88.6470, src.loss_imnet_feat_dist: nan
+2023-10-29 22:40:01,165 - mmseg - INFO - Iter [31350/40000]	lr: 1.298e-05, eta: 1:43:56, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2107, decode.acc_seg: 86.9713, src.loss_imnet_feat_dist: nan
+2023-10-29 22:40:37,140 - mmseg - INFO - Iter [31400/40000]	lr: 1.290e-05, eta: 1:43:20, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2024, decode.acc_seg: 84.6018, src.loss_imnet_feat_dist: nan
+2023-10-29 22:41:13,067 - mmseg - INFO - Iter [31450/40000]	lr: 1.283e-05, eta: 1:42:44, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2326, decode.acc_seg: 86.9991, src.loss_imnet_feat_dist: nan
+2023-10-29 22:41:49,023 - mmseg - INFO - Iter [31500/40000]	lr: 1.275e-05, eta: 1:42:08, time: 0.719, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1955, decode.acc_seg: 89.4044, src.loss_imnet_feat_dist: 0.1017
+2023-10-29 22:42:24,924 - mmseg - INFO - Iter [31550/40000]	lr: 1.268e-05, eta: 1:41:32, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1656, decode.acc_seg: 88.5552, src.loss_imnet_feat_dist: nan
+2023-10-29 22:43:00,900 - mmseg - INFO - Iter [31600/40000]	lr: 1.260e-05, eta: 1:40:56, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.1792, decode.acc_seg: 87.7278, src.loss_imnet_feat_dist: 0.0940
+2023-10-29 22:43:36,745 - mmseg - INFO - Iter [31650/40000]	lr: 1.253e-05, eta: 1:40:19, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1928, decode.acc_seg: 88.3359, src.loss_imnet_feat_dist: nan
+2023-10-29 22:44:12,965 - mmseg - INFO - Iter [31700/40000]	lr: 1.245e-05, eta: 1:39:43, time: 0.724, data_time: 0.020, memory: 9476, decode.loss_seg: 0.2338, decode.acc_seg: 86.6724, src.loss_imnet_feat_dist: nan
+2023-10-29 22:44:48,900 - mmseg - INFO - Iter [31750/40000]	lr: 1.238e-05, eta: 1:39:07, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2141, decode.acc_seg: 87.4333, src.loss_imnet_feat_dist: nan
+2023-10-29 22:45:24,730 - mmseg - INFO - Iter [31800/40000]	lr: 1.230e-05, eta: 1:38:31, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2163, decode.acc_seg: 87.2586, src.loss_imnet_feat_dist: nan
+2023-10-29 22:46:00,618 - mmseg - INFO - Iter [31850/40000]	lr: 1.223e-05, eta: 1:37:55, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2022, decode.acc_seg: 87.2944, src.loss_imnet_feat_dist: nan
+2023-10-29 22:46:36,474 - mmseg - INFO - Iter [31900/40000]	lr: 1.215e-05, eta: 1:37:19, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2062, decode.acc_seg: 88.3525, src.loss_imnet_feat_dist: 0.0967
+2023-10-29 22:47:12,361 - mmseg - INFO - Iter [31950/40000]	lr: 1.208e-05, eta: 1:36:43, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2334, decode.acc_seg: 87.9560, src.loss_imnet_feat_dist: nan
+2023-10-29 22:47:48,555 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 22:47:48,555 - mmseg - INFO - Iter [32000/40000]	lr: 1.200e-05, eta: 1:36:07, time: 0.724, data_time: 0.019, memory: 9476, decode.loss_seg: 0.1991, decode.acc_seg: 88.8390, src.loss_imnet_feat_dist: nan
+2023-10-29 22:48:24,463 - mmseg - INFO - Iter [32050/40000]	lr: 1.193e-05, eta: 1:35:31, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2058, decode.acc_seg: 87.8822, src.loss_imnet_feat_dist: nan
+2023-10-29 22:49:00,329 - mmseg - INFO - Iter [32100/40000]	lr: 1.185e-05, eta: 1:34:55, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2034, decode.acc_seg: 87.6833, src.loss_imnet_feat_dist: nan
+2023-10-29 22:49:36,432 - mmseg - INFO - Iter [32150/40000]	lr: 1.178e-05, eta: 1:34:19, time: 0.722, data_time: 0.018, memory: 9476, decode.loss_seg: 0.1873, decode.acc_seg: 88.9954, src.loss_imnet_feat_dist: nan
+2023-10-29 22:50:12,238 - mmseg - INFO - Iter [32200/40000]	lr: 1.170e-05, eta: 1:33:43, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2018, decode.acc_seg: 87.9147, src.loss_imnet_feat_dist: nan
+2023-10-29 22:50:48,311 - mmseg - INFO - Iter [32250/40000]	lr: 1.163e-05, eta: 1:33:07, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1809, decode.acc_seg: 88.5420, src.loss_imnet_feat_dist: nan
+2023-10-29 22:51:24,320 - mmseg - INFO - Iter [32300/40000]	lr: 1.155e-05, eta: 1:32:31, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2013, decode.acc_seg: 89.1413, src.loss_imnet_feat_dist: nan
+2023-10-29 22:52:00,298 - mmseg - INFO - Iter [32350/40000]	lr: 1.148e-05, eta: 1:31:54, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2505, decode.acc_seg: 86.7500, src.loss_imnet_feat_dist: nan
+2023-10-29 22:52:36,133 - mmseg - INFO - Iter [32400/40000]	lr: 1.140e-05, eta: 1:31:18, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2249, decode.acc_seg: 89.2984, src.loss_imnet_feat_dist: nan
+2023-10-29 22:53:12,077 - mmseg - INFO - Iter [32450/40000]	lr: 1.133e-05, eta: 1:30:42, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1821, decode.acc_seg: 87.4428, src.loss_imnet_feat_dist: nan
+2023-10-29 22:53:48,163 - mmseg - INFO - Iter [32500/40000]	lr: 1.125e-05, eta: 1:30:06, time: 0.722, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2034, decode.acc_seg: 88.1037, src.loss_imnet_feat_dist: nan
+2023-10-29 22:54:25,082 - mmseg - INFO - Iter [32550/40000]	lr: 1.118e-05, eta: 1:29:30, time: 0.738, data_time: 0.032, memory: 9476, decode.loss_seg: 0.1982, decode.acc_seg: 88.5878, src.loss_imnet_feat_dist: nan
+2023-10-29 22:55:01,102 - mmseg - INFO - Iter [32600/40000]	lr: 1.110e-05, eta: 1:28:54, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2248, decode.acc_seg: 86.4536, src.loss_imnet_feat_dist: nan
+2023-10-29 22:55:36,986 - mmseg - INFO - Iter [32650/40000]	lr: 1.103e-05, eta: 1:28:18, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2037, decode.acc_seg: 88.4840, src.loss_imnet_feat_dist: nan
+2023-10-29 22:56:12,790 - mmseg - INFO - Iter [32700/40000]	lr: 1.095e-05, eta: 1:27:42, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1893, decode.acc_seg: 88.1402, src.loss_imnet_feat_dist: nan
+2023-10-29 22:56:48,664 - mmseg - INFO - Iter [32750/40000]	lr: 1.088e-05, eta: 1:27:06, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2030, decode.acc_seg: 90.7275, src.loss_imnet_feat_dist: nan
+2023-10-29 22:57:24,576 - mmseg - INFO - Iter [32800/40000]	lr: 1.080e-05, eta: 1:26:30, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2191, decode.acc_seg: 87.3791, src.loss_imnet_feat_dist: 0.0921
+2023-10-29 22:58:00,493 - mmseg - INFO - Iter [32850/40000]	lr: 1.073e-05, eta: 1:25:54, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1831, decode.acc_seg: 89.7105, src.loss_imnet_feat_dist: 0.0909
+2023-10-29 22:58:36,448 - mmseg - INFO - Iter [32900/40000]	lr: 1.065e-05, eta: 1:25:18, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2153, decode.acc_seg: 87.5661, src.loss_imnet_feat_dist: 0.0873
+2023-10-29 22:59:12,356 - mmseg - INFO - Iter [32950/40000]	lr: 1.058e-05, eta: 1:24:42, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2046, decode.acc_seg: 88.1280, src.loss_imnet_feat_dist: nan
+2023-10-29 22:59:48,269 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 22:59:48,269 - mmseg - INFO - Iter [33000/40000]	lr: 1.050e-05, eta: 1:24:06, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1771, decode.acc_seg: 87.4250, src.loss_imnet_feat_dist: nan
+2023-10-29 23:00:24,196 - mmseg - INFO - Iter [33050/40000]	lr: 1.043e-05, eta: 1:23:30, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2521, decode.acc_seg: 85.5529, src.loss_imnet_feat_dist: nan
+2023-10-29 23:01:00,249 - mmseg - INFO - Iter [33100/40000]	lr: 1.035e-05, eta: 1:22:54, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1966, decode.acc_seg: 87.5674, src.loss_imnet_feat_dist: nan
+2023-10-29 23:01:36,260 - mmseg - INFO - Iter [33150/40000]	lr: 1.028e-05, eta: 1:22:18, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1962, decode.acc_seg: 88.7875, src.loss_imnet_feat_dist: nan
+2023-10-29 23:02:12,132 - mmseg - INFO - Iter [33200/40000]	lr: 1.020e-05, eta: 1:21:42, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1872, decode.acc_seg: 88.1646, src.loss_imnet_feat_dist: nan
+2023-10-29 23:02:48,091 - mmseg - INFO - Iter [33250/40000]	lr: 1.013e-05, eta: 1:21:05, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2228, decode.acc_seg: 87.5053, src.loss_imnet_feat_dist: nan
+2023-10-29 23:03:23,978 - mmseg - INFO - Iter [33300/40000]	lr: 1.005e-05, eta: 1:20:29, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2022, decode.acc_seg: 87.1422, src.loss_imnet_feat_dist: nan
+2023-10-29 23:04:00,405 - mmseg - INFO - Iter [33350/40000]	lr: 9.976e-06, eta: 1:19:53, time: 0.729, data_time: 0.024, memory: 9476, decode.loss_seg: 0.1841, decode.acc_seg: 90.5465, src.loss_imnet_feat_dist: nan
+2023-10-29 23:04:36,257 - mmseg - INFO - Iter [33400/40000]	lr: 9.901e-06, eta: 1:19:17, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1935, decode.acc_seg: 88.7085, src.loss_imnet_feat_dist: nan
+2023-10-29 23:05:12,856 - mmseg - INFO - Iter [33450/40000]	lr: 9.826e-06, eta: 1:18:41, time: 0.732, data_time: 0.026, memory: 9476, decode.loss_seg: 0.1894, decode.acc_seg: 89.1542, src.loss_imnet_feat_dist: nan
+2023-10-29 23:05:48,731 - mmseg - INFO - Iter [33500/40000]	lr: 9.752e-06, eta: 1:18:05, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1938, decode.acc_seg: 88.9606, src.loss_imnet_feat_dist: nan
+2023-10-29 23:06:24,628 - mmseg - INFO - Iter [33550/40000]	lr: 9.676e-06, eta: 1:17:29, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2052, decode.acc_seg: 86.8419, src.loss_imnet_feat_dist: nan
+2023-10-29 23:07:00,527 - mmseg - INFO - Iter [33600/40000]	lr: 9.601e-06, eta: 1:16:53, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2322, decode.acc_seg: 88.4886, src.loss_imnet_feat_dist: nan
+2023-10-29 23:07:36,582 - mmseg - INFO - Iter [33650/40000]	lr: 9.527e-06, eta: 1:16:17, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2135, decode.acc_seg: 87.8434, src.loss_imnet_feat_dist: nan
+2023-10-29 23:08:12,481 - mmseg - INFO - Iter [33700/40000]	lr: 9.452e-06, eta: 1:15:41, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1997, decode.acc_seg: 88.7502, src.loss_imnet_feat_dist: nan
+2023-10-29 23:08:48,929 - mmseg - INFO - Iter [33750/40000]	lr: 9.377e-06, eta: 1:15:05, time: 0.729, data_time: 0.023, memory: 9476, decode.loss_seg: 0.2336, decode.acc_seg: 88.1262, src.loss_imnet_feat_dist: nan
+2023-10-29 23:09:24,920 - mmseg - INFO - Iter [33800/40000]	lr: 9.301e-06, eta: 1:14:29, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2246, decode.acc_seg: 86.0261, src.loss_imnet_feat_dist: nan
+2023-10-29 23:10:00,855 - mmseg - INFO - Iter [33850/40000]	lr: 9.227e-06, eta: 1:13:53, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2018, decode.acc_seg: 87.1387, src.loss_imnet_feat_dist: nan
+2023-10-29 23:10:36,733 - mmseg - INFO - Iter [33900/40000]	lr: 9.152e-06, eta: 1:13:17, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1921, decode.acc_seg: 87.2293, src.loss_imnet_feat_dist: nan
+2023-10-29 23:11:12,655 - mmseg - INFO - Iter [33950/40000]	lr: 9.077e-06, eta: 1:12:41, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1907, decode.acc_seg: 87.2610, src.loss_imnet_feat_dist: nan
+2023-10-29 23:11:48,565 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 23:11:48,565 - mmseg - INFO - Iter [34000/40000]	lr: 9.001e-06, eta: 1:12:05, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1828, decode.acc_seg: 89.0874, src.loss_imnet_feat_dist: nan
+2023-10-29 23:12:24,593 - mmseg - INFO - Iter [34050/40000]	lr: 8.926e-06, eta: 1:11:29, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.1955, decode.acc_seg: 87.2960, src.loss_imnet_feat_dist: nan
+2023-10-29 23:13:00,422 - mmseg - INFO - Iter [34100/40000]	lr: 8.852e-06, eta: 1:10:53, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1930, decode.acc_seg: 87.5338, src.loss_imnet_feat_dist: nan
+2023-10-29 23:13:36,295 - mmseg - INFO - Iter [34150/40000]	lr: 8.777e-06, eta: 1:10:17, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1876, decode.acc_seg: 87.9353, src.loss_imnet_feat_dist: nan
+2023-10-29 23:14:12,165 - mmseg - INFO - Iter [34200/40000]	lr: 8.701e-06, eta: 1:09:40, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2223, decode.acc_seg: 88.5907, src.loss_imnet_feat_dist: nan
+2023-10-29 23:14:48,022 - mmseg - INFO - Iter [34250/40000]	lr: 8.626e-06, eta: 1:09:04, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1886, decode.acc_seg: 88.5752, src.loss_imnet_feat_dist: nan
+2023-10-29 23:15:23,883 - mmseg - INFO - Iter [34300/40000]	lr: 8.552e-06, eta: 1:08:28, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2153, decode.acc_seg: 87.3511, src.loss_imnet_feat_dist: nan
+2023-10-29 23:15:59,755 - mmseg - INFO - Iter [34350/40000]	lr: 8.477e-06, eta: 1:07:52, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2251, decode.acc_seg: 88.0406, src.loss_imnet_feat_dist: nan
+2023-10-29 23:16:35,604 - mmseg - INFO - Iter [34400/40000]	lr: 8.401e-06, eta: 1:07:16, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1784, decode.acc_seg: 88.0810, src.loss_imnet_feat_dist: nan
+2023-10-29 23:17:11,616 - mmseg - INFO - Iter [34450/40000]	lr: 8.326e-06, eta: 1:06:40, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2078, decode.acc_seg: 87.9443, src.loss_imnet_feat_dist: nan
+2023-10-29 23:17:47,595 - mmseg - INFO - Iter [34500/40000]	lr: 8.252e-06, eta: 1:06:04, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.1989, decode.acc_seg: 87.6715, src.loss_imnet_feat_dist: nan
+2023-10-29 23:18:23,428 - mmseg - INFO - Iter [34550/40000]	lr: 8.177e-06, eta: 1:05:28, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2401, decode.acc_seg: 87.7903, src.loss_imnet_feat_dist: nan
+2023-10-29 23:18:59,279 - mmseg - INFO - Iter [34600/40000]	lr: 8.101e-06, eta: 1:04:52, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1872, decode.acc_seg: 88.9032, src.loss_imnet_feat_dist: 0.0932
+2023-10-29 23:19:35,390 - mmseg - INFO - Iter [34650/40000]	lr: 8.026e-06, eta: 1:04:16, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2322, decode.acc_seg: 87.4401, src.loss_imnet_feat_dist: nan
+2023-10-29 23:20:11,669 - mmseg - INFO - Iter [34700/40000]	lr: 7.952e-06, eta: 1:03:40, time: 0.726, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2130, decode.acc_seg: 86.4002, src.loss_imnet_feat_dist: nan
+2023-10-29 23:20:47,636 - mmseg - INFO - Iter [34750/40000]	lr: 7.877e-06, eta: 1:03:04, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.1899, decode.acc_seg: 88.7595, src.loss_imnet_feat_dist: nan
+2023-10-29 23:21:24,052 - mmseg - INFO - Iter [34800/40000]	lr: 7.801e-06, eta: 1:02:28, time: 0.728, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2098, decode.acc_seg: 88.4943, src.loss_imnet_feat_dist: nan
+2023-10-29 23:21:59,900 - mmseg - INFO - Iter [34850/40000]	lr: 7.726e-06, eta: 1:01:52, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1919, decode.acc_seg: 86.5376, src.loss_imnet_feat_dist: nan
+2023-10-29 23:22:36,171 - mmseg - INFO - Iter [34900/40000]	lr: 7.651e-06, eta: 1:01:16, time: 0.725, data_time: 0.020, memory: 9476, decode.loss_seg: 0.1918, decode.acc_seg: 87.7973, src.loss_imnet_feat_dist: nan
+2023-10-29 23:23:12,146 - mmseg - INFO - Iter [34950/40000]	lr: 7.577e-06, eta: 1:00:40, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2137, decode.acc_seg: 86.8660, src.loss_imnet_feat_dist: nan
+2023-10-29 23:23:48,370 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 23:23:48,370 - mmseg - INFO - Iter [35000/40000]	lr: 7.502e-06, eta: 1:00:04, time: 0.724, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2235, decode.acc_seg: 87.0933, src.loss_imnet_feat_dist: 0.0985
+2023-10-29 23:24:24,377 - mmseg - INFO - Iter [35050/40000]	lr: 7.426e-06, eta: 0:59:28, time: 0.720, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1935, decode.acc_seg: 88.1630, src.loss_imnet_feat_dist: nan
+2023-10-29 23:25:00,299 - mmseg - INFO - Iter [35100/40000]	lr: 7.351e-06, eta: 0:58:52, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1942, decode.acc_seg: 89.5081, src.loss_imnet_feat_dist: nan
+2023-10-29 23:25:36,236 - mmseg - INFO - Iter [35150/40000]	lr: 7.277e-06, eta: 0:58:16, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2139, decode.acc_seg: 86.5573, src.loss_imnet_feat_dist: nan
+2023-10-29 23:26:12,437 - mmseg - INFO - Iter [35200/40000]	lr: 7.202e-06, eta: 0:57:40, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2122, decode.acc_seg: 87.8262, src.loss_imnet_feat_dist: nan
+2023-10-29 23:26:48,366 - mmseg - INFO - Iter [35250/40000]	lr: 7.126e-06, eta: 0:57:03, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1983, decode.acc_seg: 87.6284, src.loss_imnet_feat_dist: nan
+2023-10-29 23:27:24,940 - mmseg - INFO - Iter [35300/40000]	lr: 7.051e-06, eta: 0:56:28, time: 0.731, data_time: 0.026, memory: 9476, decode.loss_seg: 0.1888, decode.acc_seg: 88.5602, src.loss_imnet_feat_dist: nan
+2023-10-29 23:28:00,840 - mmseg - INFO - Iter [35350/40000]	lr: 6.977e-06, eta: 0:55:51, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2305, decode.acc_seg: 86.5414, src.loss_imnet_feat_dist: nan
+2023-10-29 23:28:36,760 - mmseg - INFO - Iter [35400/40000]	lr: 6.902e-06, eta: 0:55:15, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1929, decode.acc_seg: 88.3153, src.loss_imnet_feat_dist: nan
+2023-10-29 23:29:12,646 - mmseg - INFO - Iter [35450/40000]	lr: 6.826e-06, eta: 0:54:39, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2008, decode.acc_seg: 88.5829, src.loss_imnet_feat_dist: nan
+2023-10-29 23:29:48,757 - mmseg - INFO - Iter [35500/40000]	lr: 6.751e-06, eta: 0:54:03, time: 0.722, data_time: 0.015, memory: 9476, decode.loss_seg: 0.1773, decode.acc_seg: 89.0228, src.loss_imnet_feat_dist: nan
+2023-10-29 23:30:24,702 - mmseg - INFO - Iter [35550/40000]	lr: 6.677e-06, eta: 0:53:27, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1957, decode.acc_seg: 86.8906, src.loss_imnet_feat_dist: 0.0992
+2023-10-29 23:31:00,743 - mmseg - INFO - Iter [35600/40000]	lr: 6.602e-06, eta: 0:52:51, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.2024, decode.acc_seg: 87.6593, src.loss_imnet_feat_dist: nan
+2023-10-29 23:31:36,716 - mmseg - INFO - Iter [35650/40000]	lr: 6.526e-06, eta: 0:52:15, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.2073, decode.acc_seg: 88.5840, src.loss_imnet_feat_dist: 0.0927
+2023-10-29 23:32:12,894 - mmseg - INFO - Iter [35700/40000]	lr: 6.451e-06, eta: 0:51:39, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.1939, decode.acc_seg: 88.4599, src.loss_imnet_feat_dist: nan
+2023-10-29 23:32:48,782 - mmseg - INFO - Iter [35750/40000]	lr: 6.377e-06, eta: 0:51:03, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.2065, decode.acc_seg: 87.6536, src.loss_imnet_feat_dist: nan
+2023-10-29 23:33:24,803 - mmseg - INFO - Iter [35800/40000]	lr: 6.302e-06, eta: 0:50:27, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2427, decode.acc_seg: 87.8013, src.loss_imnet_feat_dist: nan
+2023-10-29 23:34:00,733 - mmseg - INFO - Iter [35850/40000]	lr: 6.226e-06, eta: 0:49:51, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1860, decode.acc_seg: 86.7684, src.loss_imnet_feat_dist: nan
+2023-10-29 23:34:37,810 - mmseg - INFO - Iter [35900/40000]	lr: 6.151e-06, eta: 0:49:15, time: 0.741, data_time: 0.036, memory: 9476, decode.loss_seg: 0.1783, decode.acc_seg: 88.7380, src.loss_imnet_feat_dist: nan
+2023-10-29 23:35:13,973 - mmseg - INFO - Iter [35950/40000]	lr: 6.077e-06, eta: 0:48:39, time: 0.724, data_time: 0.019, memory: 9476, decode.loss_seg: 0.1600, decode.acc_seg: 89.4951, src.loss_imnet_feat_dist: nan
+2023-10-29 23:35:50,090 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 23:35:50,093 - mmseg - INFO - Iter [36000/40000]	lr: 6.002e-06, eta: 0:48:03, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2132, decode.acc_seg: 87.3938, src.loss_imnet_feat_dist: 0.0901
+2023-10-29 23:36:26,036 - mmseg - INFO - Iter [36050/40000]	lr: 5.926e-06, eta: 0:47:27, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1838, decode.acc_seg: 89.9567, src.loss_imnet_feat_dist: nan
+2023-10-29 23:37:02,127 - mmseg - INFO - Iter [36100/40000]	lr: 5.851e-06, eta: 0:46:51, time: 0.722, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2133, decode.acc_seg: 86.9812, src.loss_imnet_feat_dist: nan
+2023-10-29 23:37:38,077 - mmseg - INFO - Iter [36150/40000]	lr: 5.777e-06, eta: 0:46:15, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1869, decode.acc_seg: 87.3769, src.loss_imnet_feat_dist: nan
+2023-10-29 23:38:14,152 - mmseg - INFO - Iter [36200/40000]	lr: 5.702e-06, eta: 0:45:39, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.1931, decode.acc_seg: 87.4433, src.loss_imnet_feat_dist: 0.0955
+2023-10-29 23:38:50,036 - mmseg - INFO - Iter [36250/40000]	lr: 5.627e-06, eta: 0:45:03, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1978, decode.acc_seg: 88.4906, src.loss_imnet_feat_dist: nan
+2023-10-29 23:39:26,797 - mmseg - INFO - Iter [36300/40000]	lr: 5.551e-06, eta: 0:44:27, time: 0.735, data_time: 0.031, memory: 9476, decode.loss_seg: 0.2131, decode.acc_seg: 86.2129, src.loss_imnet_feat_dist: 0.0931
+2023-10-29 23:40:03,281 - mmseg - INFO - Iter [36350/40000]	lr: 5.476e-06, eta: 0:43:51, time: 0.729, data_time: 0.024, memory: 9476, decode.loss_seg: 0.2058, decode.acc_seg: 87.9622, src.loss_imnet_feat_dist: nan
+2023-10-29 23:40:39,258 - mmseg - INFO - Iter [36400/40000]	lr: 5.402e-06, eta: 0:43:15, time: 0.720, data_time: 0.015, memory: 9476, decode.loss_seg: 0.1902, decode.acc_seg: 89.6195, src.loss_imnet_feat_dist: nan
+2023-10-29 23:41:15,251 - mmseg - INFO - Iter [36450/40000]	lr: 5.327e-06, eta: 0:42:39, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1898, decode.acc_seg: 88.8673, src.loss_imnet_feat_dist: nan
+2023-10-29 23:41:51,425 - mmseg - INFO - Iter [36500/40000]	lr: 5.251e-06, eta: 0:42:03, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.1910, decode.acc_seg: 88.3631, src.loss_imnet_feat_dist: nan
+2023-10-29 23:42:27,310 - mmseg - INFO - Iter [36550/40000]	lr: 5.176e-06, eta: 0:41:27, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1978, decode.acc_seg: 87.9426, src.loss_imnet_feat_dist: nan
+2023-10-29 23:43:03,181 - mmseg - INFO - Iter [36600/40000]	lr: 5.102e-06, eta: 0:40:51, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2047, decode.acc_seg: 88.5844, src.loss_imnet_feat_dist: 0.0855
+2023-10-29 23:43:39,062 - mmseg - INFO - Iter [36650/40000]	lr: 5.027e-06, eta: 0:40:14, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1829, decode.acc_seg: 89.7511, src.loss_imnet_feat_dist: 0.0918
+2023-10-29 23:44:14,930 - mmseg - INFO - Iter [36700/40000]	lr: 4.951e-06, eta: 0:39:38, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1902, decode.acc_seg: 87.9464, src.loss_imnet_feat_dist: nan
+2023-10-29 23:44:51,165 - mmseg - INFO - Iter [36750/40000]	lr: 4.876e-06, eta: 0:39:02, time: 0.725, data_time: 0.019, memory: 9476, decode.loss_seg: 0.2191, decode.acc_seg: 87.6680, src.loss_imnet_feat_dist: nan
+2023-10-29 23:45:27,546 - mmseg - INFO - Iter [36800/40000]	lr: 4.802e-06, eta: 0:38:26, time: 0.728, data_time: 0.022, memory: 9476, decode.loss_seg: 0.2264, decode.acc_seg: 88.7965, src.loss_imnet_feat_dist: nan
+2023-10-29 23:46:03,473 - mmseg - INFO - Iter [36850/40000]	lr: 4.727e-06, eta: 0:37:50, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2166, decode.acc_seg: 87.9213, src.loss_imnet_feat_dist: nan
+2023-10-29 23:46:39,619 - mmseg - INFO - Iter [36900/40000]	lr: 4.651e-06, eta: 0:37:14, time: 0.723, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1778, decode.acc_seg: 89.5544, src.loss_imnet_feat_dist: nan
+2023-10-29 23:47:15,584 - mmseg - INFO - Iter [36950/40000]	lr: 4.576e-06, eta: 0:36:38, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1682, decode.acc_seg: 89.7592, src.loss_imnet_feat_dist: nan
+2023-10-29 23:47:51,401 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 23:47:51,401 - mmseg - INFO - Iter [37000/40000]	lr: 4.502e-06, eta: 0:36:02, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1851, decode.acc_seg: 89.8296, src.loss_imnet_feat_dist: 0.0906
+2023-10-29 23:48:27,994 - mmseg - INFO - Iter [37050/40000]	lr: 4.427e-06, eta: 0:35:26, time: 0.732, data_time: 0.025, memory: 9476, decode.loss_seg: 0.1770, decode.acc_seg: 89.3856, src.loss_imnet_feat_dist: nan
+2023-10-29 23:49:03,938 - mmseg - INFO - Iter [37100/40000]	lr: 4.351e-06, eta: 0:34:50, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2011, decode.acc_seg: 88.4542, src.loss_imnet_feat_dist: nan
+2023-10-29 23:49:41,427 - mmseg - INFO - Iter [37150/40000]	lr: 4.276e-06, eta: 0:34:14, time: 0.750, data_time: 0.042, memory: 9476, decode.loss_seg: 0.1822, decode.acc_seg: 87.1981, src.loss_imnet_feat_dist: nan
+2023-10-29 23:50:17,678 - mmseg - INFO - Iter [37200/40000]	lr: 4.202e-06, eta: 0:33:38, time: 0.725, data_time: 0.018, memory: 9476, decode.loss_seg: 0.1767, decode.acc_seg: 88.1361, src.loss_imnet_feat_dist: nan
+2023-10-29 23:50:53,586 - mmseg - INFO - Iter [37250/40000]	lr: 4.127e-06, eta: 0:33:02, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1894, decode.acc_seg: 89.5808, src.loss_imnet_feat_dist: nan
+2023-10-29 23:51:29,546 - mmseg - INFO - Iter [37300/40000]	lr: 4.051e-06, eta: 0:32:26, time: 0.719, data_time: 0.014, memory: 9476, decode.loss_seg: 0.1973, decode.acc_seg: 88.9438, src.loss_imnet_feat_dist: nan
+2023-10-29 23:52:05,381 - mmseg - INFO - Iter [37350/40000]	lr: 3.976e-06, eta: 0:31:50, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1775, decode.acc_seg: 89.4163, src.loss_imnet_feat_dist: 0.0952
+2023-10-29 23:52:41,278 - mmseg - INFO - Iter [37400/40000]	lr: 3.901e-06, eta: 0:31:14, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2004, decode.acc_seg: 87.4888, src.loss_imnet_feat_dist: nan
+2023-10-29 23:53:17,144 - mmseg - INFO - Iter [37450/40000]	lr: 3.827e-06, eta: 0:30:38, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1890, decode.acc_seg: 90.0648, src.loss_imnet_feat_dist: nan
+2023-10-29 23:53:53,073 - mmseg - INFO - Iter [37500/40000]	lr: 3.752e-06, eta: 0:30:02, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2214, decode.acc_seg: 86.5225, src.loss_imnet_feat_dist: 0.0912
+2023-10-29 23:54:29,097 - mmseg - INFO - Iter [37550/40000]	lr: 3.676e-06, eta: 0:29:26, time: 0.720, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1800, decode.acc_seg: 90.1497, src.loss_imnet_feat_dist: nan
+2023-10-29 23:55:04,988 - mmseg - INFO - Iter [37600/40000]	lr: 3.601e-06, eta: 0:28:50, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1830, decode.acc_seg: 88.8693, src.loss_imnet_feat_dist: nan
+2023-10-29 23:55:41,135 - mmseg - INFO - Iter [37650/40000]	lr: 3.527e-06, eta: 0:28:14, time: 0.723, data_time: 0.018, memory: 9476, decode.loss_seg: 0.2008, decode.acc_seg: 88.0967, src.loss_imnet_feat_dist: nan
+2023-10-29 23:56:17,037 - mmseg - INFO - Iter [37700/40000]	lr: 3.452e-06, eta: 0:27:38, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1978, decode.acc_seg: 88.3649, src.loss_imnet_feat_dist: 0.0963
+2023-10-29 23:56:53,107 - mmseg - INFO - Iter [37750/40000]	lr: 3.376e-06, eta: 0:27:02, time: 0.721, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1638, decode.acc_seg: 89.8122, src.loss_imnet_feat_dist: nan
+2023-10-29 23:57:28,943 - mmseg - INFO - Iter [37800/40000]	lr: 3.301e-06, eta: 0:26:25, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1867, decode.acc_seg: 88.2871, src.loss_imnet_feat_dist: nan
+2023-10-29 23:58:05,106 - mmseg - INFO - Iter [37850/40000]	lr: 3.227e-06, eta: 0:25:49, time: 0.723, data_time: 0.017, memory: 9476, decode.loss_seg: 0.1909, decode.acc_seg: 88.5760, src.loss_imnet_feat_dist: nan
+2023-10-29 23:58:41,487 - mmseg - INFO - Iter [37900/40000]	lr: 3.152e-06, eta: 0:25:13, time: 0.728, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1991, decode.acc_seg: 88.2559, src.loss_imnet_feat_dist: nan
+2023-10-29 23:59:17,347 - mmseg - INFO - Iter [37950/40000]	lr: 3.076e-06, eta: 0:24:37, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1986, decode.acc_seg: 88.6647, src.loss_imnet_feat_dist: nan
+2023-10-29 23:59:53,229 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-29 23:59:53,229 - mmseg - INFO - Iter [38000/40000]	lr: 3.001e-06, eta: 0:24:01, time: 0.718, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1947, decode.acc_seg: 87.9344, src.loss_imnet_feat_dist: nan
+2023-10-30 00:00:29,260 - mmseg - INFO - Iter [38050/40000]	lr: 2.927e-06, eta: 0:23:25, time: 0.721, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2146, decode.acc_seg: 86.0498, src.loss_imnet_feat_dist: nan
+2023-10-30 00:01:05,125 - mmseg - INFO - Iter [38100/40000]	lr: 2.852e-06, eta: 0:22:49, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1931, decode.acc_seg: 89.9355, src.loss_imnet_feat_dist: nan
+2023-10-30 00:01:41,067 - mmseg - INFO - Iter [38150/40000]	lr: 2.776e-06, eta: 0:22:13, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1809, decode.acc_seg: 88.5431, src.loss_imnet_feat_dist: 0.0926
+2023-10-30 00:02:17,081 - mmseg - INFO - Iter [38200/40000]	lr: 2.701e-06, eta: 0:21:37, time: 0.720, data_time: 0.014, memory: 9476, decode.loss_seg: 0.1815, decode.acc_seg: 88.6323, src.loss_imnet_feat_dist: nan
+2023-10-30 00:02:53,025 - mmseg - INFO - Iter [38250/40000]	lr: 2.627e-06, eta: 0:21:01, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2198, decode.acc_seg: 87.7714, src.loss_imnet_feat_dist: nan
+2023-10-30 00:03:28,900 - mmseg - INFO - Iter [38300/40000]	lr: 2.552e-06, eta: 0:20:25, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1924, decode.acc_seg: 87.4417, src.loss_imnet_feat_dist: 0.1000
+2023-10-30 00:04:04,811 - mmseg - INFO - Iter [38350/40000]	lr: 2.476e-06, eta: 0:19:49, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1702, decode.acc_seg: 88.2153, src.loss_imnet_feat_dist: 0.0936
+2023-10-30 00:04:40,744 - mmseg - INFO - Iter [38400/40000]	lr: 2.401e-06, eta: 0:19:13, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1734, decode.acc_seg: 88.0223, src.loss_imnet_feat_dist: nan
+2023-10-30 00:05:16,625 - mmseg - INFO - Iter [38450/40000]	lr: 2.327e-06, eta: 0:18:37, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1960, decode.acc_seg: 87.7615, src.loss_imnet_feat_dist: nan
+2023-10-30 00:05:52,500 - mmseg - INFO - Iter [38500/40000]	lr: 2.252e-06, eta: 0:18:01, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1845, decode.acc_seg: 87.4536, src.loss_imnet_feat_dist: nan
+2023-10-30 00:06:28,354 - mmseg - INFO - Iter [38550/40000]	lr: 2.176e-06, eta: 0:17:25, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1862, decode.acc_seg: 88.3775, src.loss_imnet_feat_dist: nan
+2023-10-30 00:07:04,181 - mmseg - INFO - Iter [38600/40000]	lr: 2.101e-06, eta: 0:16:49, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2115, decode.acc_seg: 87.4334, src.loss_imnet_feat_dist: nan
+2023-10-30 00:07:39,995 - mmseg - INFO - Iter [38650/40000]	lr: 2.026e-06, eta: 0:16:13, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1842, decode.acc_seg: 89.5646, src.loss_imnet_feat_dist: nan
+2023-10-30 00:08:16,076 - mmseg - INFO - Iter [38700/40000]	lr: 1.952e-06, eta: 0:15:37, time: 0.722, data_time: 0.016, memory: 9476, decode.loss_seg: 0.1884, decode.acc_seg: 88.2988, src.loss_imnet_feat_dist: nan
+2023-10-30 00:08:51,969 - mmseg - INFO - Iter [38750/40000]	lr: 1.877e-06, eta: 0:15:01, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1885, decode.acc_seg: 90.0744, src.loss_imnet_feat_dist: nan
+2023-10-30 00:09:27,903 - mmseg - INFO - Iter [38800/40000]	lr: 1.801e-06, eta: 0:14:25, time: 0.719, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1819, decode.acc_seg: 88.6943, src.loss_imnet_feat_dist: nan
+2023-10-30 00:10:03,754 - mmseg - INFO - Iter [38850/40000]	lr: 1.726e-06, eta: 0:13:48, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1950, decode.acc_seg: 88.5166, src.loss_imnet_feat_dist: nan
+2023-10-30 00:10:39,558 - mmseg - INFO - Iter [38900/40000]	lr: 1.652e-06, eta: 0:13:12, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1976, decode.acc_seg: 86.5983, src.loss_imnet_feat_dist: nan
+2023-10-30 00:11:15,618 - mmseg - INFO - Iter [38950/40000]	lr: 1.577e-06, eta: 0:12:36, time: 0.721, data_time: 0.017, memory: 9476, decode.loss_seg: 0.2106, decode.acc_seg: 86.8297, src.loss_imnet_feat_dist: nan
+2023-10-30 00:11:51,531 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-30 00:11:51,532 - mmseg - INFO - Iter [39000/40000]	lr: 1.501e-06, eta: 0:12:00, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2344, decode.acc_seg: 86.1976, src.loss_imnet_feat_dist: nan
+2023-10-30 00:12:28,457 - mmseg - INFO - Iter [39050/40000]	lr: 1.426e-06, eta: 0:11:24, time: 0.738, data_time: 0.034, memory: 9476, decode.loss_seg: 0.2054, decode.acc_seg: 87.8432, src.loss_imnet_feat_dist: nan
+2023-10-30 00:13:04,354 - mmseg - INFO - Iter [39100/40000]	lr: 1.352e-06, eta: 0:10:48, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1766, decode.acc_seg: 88.5226, src.loss_imnet_feat_dist: nan
+2023-10-30 00:13:40,211 - mmseg - INFO - Iter [39150/40000]	lr: 1.277e-06, eta: 0:10:12, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1946, decode.acc_seg: 89.8277, src.loss_imnet_feat_dist: nan
+2023-10-30 00:14:16,394 - mmseg - INFO - Iter [39200/40000]	lr: 1.201e-06, eta: 0:09:36, time: 0.724, data_time: 0.018, memory: 9476, decode.loss_seg: 0.1774, decode.acc_seg: 88.3227, src.loss_imnet_feat_dist: nan
+2023-10-30 00:14:52,455 - mmseg - INFO - Iter [39250/40000]	lr: 1.126e-06, eta: 0:09:00, time: 0.721, data_time: 0.014, memory: 9476, decode.loss_seg: 0.1795, decode.acc_seg: 89.3382, src.loss_imnet_feat_dist: nan
+2023-10-30 00:15:28,321 - mmseg - INFO - Iter [39300/40000]	lr: 1.052e-06, eta: 0:08:24, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1852, decode.acc_seg: 89.3418, src.loss_imnet_feat_dist: 0.0900
+2023-10-30 00:16:04,195 - mmseg - INFO - Iter [39350/40000]	lr: 9.765e-07, eta: 0:07:48, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1906, decode.acc_seg: 89.9206, src.loss_imnet_feat_dist: nan
+2023-10-30 00:16:40,103 - mmseg - INFO - Iter [39400/40000]	lr: 9.015e-07, eta: 0:07:12, time: 0.718, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1836, decode.acc_seg: 89.3722, src.loss_imnet_feat_dist: nan
+2023-10-30 00:17:15,913 - mmseg - INFO - Iter [39450/40000]	lr: 8.265e-07, eta: 0:06:36, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1842, decode.acc_seg: 88.5966, src.loss_imnet_feat_dist: nan
+2023-10-30 00:17:51,862 - mmseg - INFO - Iter [39500/40000]	lr: 7.515e-07, eta: 0:06:00, time: 0.719, data_time: 0.015, memory: 9476, decode.loss_seg: 0.2338, decode.acc_seg: 88.3712, src.loss_imnet_feat_dist: nan
+2023-10-30 00:18:27,731 - mmseg - INFO - Iter [39550/40000]	lr: 6.765e-07, eta: 0:05:24, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1791, decode.acc_seg: 87.8529, src.loss_imnet_feat_dist: nan
+2023-10-30 00:19:04,857 - mmseg - INFO - Iter [39600/40000]	lr: 6.015e-07, eta: 0:04:48, time: 0.743, data_time: 0.038, memory: 9476, decode.loss_seg: 0.1767, decode.acc_seg: 87.9308, src.loss_imnet_feat_dist: nan
+2023-10-30 00:19:40,700 - mmseg - INFO - Iter [39650/40000]	lr: 5.265e-07, eta: 0:04:12, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.2231, decode.acc_seg: 86.1013, src.loss_imnet_feat_dist: 0.0897
+2023-10-30 00:20:16,863 - mmseg - INFO - Iter [39700/40000]	lr: 4.515e-07, eta: 0:03:36, time: 0.723, data_time: 0.019, memory: 9476, decode.loss_seg: 0.1834, decode.acc_seg: 87.3667, src.loss_imnet_feat_dist: nan
+2023-10-30 00:20:52,689 - mmseg - INFO - Iter [39750/40000]	lr: 3.765e-07, eta: 0:03:00, time: 0.716, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1719, decode.acc_seg: 89.1341, src.loss_imnet_feat_dist: nan
+2023-10-30 00:21:28,520 - mmseg - INFO - Iter [39800/40000]	lr: 3.015e-07, eta: 0:02:24, time: 0.717, data_time: 0.013, memory: 9476, decode.loss_seg: 0.1684, decode.acc_seg: 89.9044, src.loss_imnet_feat_dist: nan
+2023-10-30 00:22:04,385 - mmseg - INFO - Iter [39850/40000]	lr: 2.265e-07, eta: 0:01:48, time: 0.717, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1817, decode.acc_seg: 88.4611, src.loss_imnet_feat_dist: nan
+2023-10-30 00:22:40,164 - mmseg - INFO - Iter [39900/40000]	lr: 1.515e-07, eta: 0:01:12, time: 0.716, data_time: 0.012, memory: 9476, decode.loss_seg: 0.1907, decode.acc_seg: 89.2980, src.loss_imnet_feat_dist: nan
+2023-10-30 00:23:16,343 - mmseg - INFO - Iter [39950/40000]	lr: 7.650e-08, eta: 0:00:36, time: 0.724, data_time: 0.020, memory: 9476, decode.loss_seg: 0.1881, decode.acc_seg: 88.8155, src.loss_imnet_feat_dist: nan
+2023-10-30 00:26:20,067 - mmseg - INFO - per class results:
+2023-10-30 00:26:20,074 - mmseg - INFO - 
++---------------+-------+-------+
+|     Class     |  IoU  |  Acc  |
++---------------+-------+-------+
+|      road     | 89.33 | 93.73 |
+|    sidewalk   | 43.97 | 63.44 |
+|    building   | 86.56 | 94.07 |
+|      wall     | 48.81 | 64.87 |
+|     fence     | 33.46 | 44.91 |
+|      pole     | 38.94 | 44.26 |
+| traffic light | 46.16 | 50.77 |
+|  traffic sign | 35.72 |  36.7 |
+|   vegetation  | 87.64 | 95.45 |
+|    terrain    | 37.42 | 71.19 |
+|      sky      | 88.91 | 96.98 |
+|     person    | 66.12 | 76.22 |
+|     rider     | 37.59 | 57.73 |
+|      car      | 88.65 | 92.12 |
+|     truck     | 51.15 | 88.18 |
+|      bus      | 65.22 | 73.84 |
+|     train     | 47.31 | 51.31 |
+|   motorcycle  | 41.51 | 56.94 |
+|    bicycle    | 33.17 | 34.84 |
++---------------+-------+-------+
+2023-10-30 00:26:20,075 - mmseg - INFO - Summary:
+2023-10-30 00:26:20,075 - mmseg - INFO - 
++-------+-------+-------+
+|  aAcc |  mIoU |  mAcc |
++-------+-------+-------+
+| 89.58 | 56.19 | 67.77 |
++-------+-------+-------+
+2023-10-30 00:26:20,078 - mmseg - INFO - Saving checkpoint at 40000 iterations
+2023-10-30 00:26:22,306 - mmseg - INFO - Exp name: 231029_1622_gengta3mix2cs_dgdacs_fdthings_srconly_daformer_sepaspp_sl_mitb5_poly10warm_w1_s0_49f77
+2023-10-30 00:26:22,306 - mmseg - INFO - Iter [500/40000]	lr: 1.500e-09, eta: 0:00:00, time: 0.716, data_time: 0.013, memory: 9476, aAcc: 0.8958, mIoU: 0.5619, mAcc: 0.6777, IoU.road: 0.8933, IoU.sidewalk: 0.4397, IoU.building: 0.8656, IoU.wall: 0.4881, IoU.fence: 0.3346, IoU.pole: 0.3894, IoU.traffic light: 0.4616, IoU.traffic sign: 0.3572, IoU.vegetation: 0.8764, IoU.terrain: 0.3742, IoU.sky: 0.8891, IoU.person: 0.6612, IoU.rider: 0.3759, IoU.car: 0.8865, IoU.truck: 0.5115, IoU.bus: 0.6522, IoU.train: 0.4731, IoU.motorcycle: 0.4151, IoU.bicycle: 0.3317, Acc.road: 0.9373, Acc.sidewalk: 0.6344, Acc.building: 0.9407, Acc.wall: 0.6487, Acc.fence: 0.4491, Acc.pole: 0.4426, Acc.traffic light: 0.5077, Acc.traffic sign: 0.3670, Acc.vegetation: 0.9545, Acc.terrain: 0.7119, Acc.sky: 0.9698, Acc.person: 0.7622, Acc.rider: 0.5773, Acc.car: 0.9212, Acc.truck: 0.8818, Acc.bus: 0.7384, Acc.train: 0.5131, Acc.motorcycle: 0.5694, Acc.bicycle: 0.3484, decode.loss_seg: 0.2185, decode.acc_seg: 87.5762, src.loss_imnet_feat_dist: nan