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s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB.log

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+[04/19 00:13:49] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 1111
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['s3dis', 'train', 'pointmetabase-ctwc-l', 'ngpus1']
+  name: s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: train
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: None
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudRotation', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 8
+val_batch_size: 1
+dataloader:
+  num_workers: 6
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 2
+min_lr: 1e-05
+lr: 0.02
+log_dir: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB
+model:
+  NAME: CtwcSeg
+  encoder_args:
+    NAME: PointMetaBase_CTWC_Encoder
+    blocks: [1, 3, 5, 3, 3]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 1
+    sa_use_res: False
+    width: 32
+    in_channels: 4
+    expansion: 1
+    radius: 0.1
+    nsample: 32
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNextDecoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
+      norm: bn
+need_closs: True
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointmetabase-ctwc-l
+opts: 
+is_training: True
+run_name: s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB
+run_dir: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB
+exp_dir: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB
+ckpt_dir: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint
+log_path: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB.log
+cfg_path: log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/cfg.yaml
+[04/19 00:13:49] S3DIS INFO: radius: [[0.1], [0.1, 0.2, 0.2], [0.2, 0.4, 0.4, 0.4, 0.4], [0.4, 0.8, 0.8], [0.8, 1.6, 1.6]],
+ nsample: [[32], [32, 32, 32], [32, 32, 32, 32, 32], [32, 32, 32], [32, 32, 32]]
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: False
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: True
+[04/19 00:13:49] S3DIS INFO: CtwcSeg(
+  (encoder): PointMetaBase_CTWC_Encoder(
+    (seq): FeatureRecorder()
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs1): Sequential(
+            (0): Sequential(
+              (0): Conv1d(4, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (convs1): Sequential(
+            (0): Sequential(
+              (0): Conv1d(32, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (convs2): Sequential(
+            (0): Sequential(
+              (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.025)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.025)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (convs1): Sequential(
+            (0): Sequential(
+              (0): Conv1d(64, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (convs2): Sequential(
+            (0): Sequential(
+              (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (3): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (4): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (5): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (convs1): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (convs2): Sequential(
+            (0): Sequential(
+              (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (convs1): Sequential(
+            (0): Sequential(
+              (0): Conv1d(256, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (convs2): Sequential(
+            (0): Sequential(
+              (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs1): Sequential(
+              (0): Sequential(
+                (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+                (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+        )
+      )
+    )
+    (pe_encoder): ModuleList(
+      (0): ModuleList()
+      (1): Sequential(
+        (0): Sequential(
+          (0): Conv2d(3, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+          (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (2): ReLU(inplace=True)
+        )
+      )
+      (2): Sequential(
+        (0): Sequential(
+          (0): Conv2d(3, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+          (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (2): ReLU(inplace=True)
+        )
+      )
+      (3): Sequential(
+        (0): Sequential(
+          (0): Conv2d(3, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+          (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (2): ReLU(inplace=True)
+        )
+      )
+      (4): Sequential(
+        (0): Sequential(
+          (0): Conv2d(3, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+          (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          (2): ReLU(inplace=True)
+        )
+      )
+    )
+  )
+  (decoder): PointNextDecoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[04/19 00:13:49] S3DIS INFO: Number of params: 3.0894 M
+[04/19 00:13:49] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
+      "encoder.encoder.0.0.convs1.0.0.weight",
+      "encoder.encoder.1.0.convs1.0.0.weight",
+      "encoder.encoder.1.0.convs2.0.0.weight",
+      "encoder.encoder.1.1.convs.convs1.0.0.weight",
+      "encoder.encoder.1.1.pwconv.0.0.weight",
+      "encoder.encoder.1.1.pwconv.1.0.weight",
+      "encoder.encoder.1.2.convs.convs1.0.0.weight",
+      "encoder.encoder.1.2.pwconv.0.0.weight",
+      "encoder.encoder.1.2.pwconv.1.0.weight",
+      "encoder.encoder.1.3.gate",
+      "encoder.encoder.1.3.pwconv.0.weight",
+      "encoder.encoder.2.0.convs1.0.0.weight",
+      "encoder.encoder.2.0.convs2.0.0.weight",
+      "encoder.encoder.2.1.convs.convs1.0.0.weight",
+      "encoder.encoder.2.1.pwconv.0.0.weight",
+      "encoder.encoder.2.1.pwconv.1.0.weight",
+      "encoder.encoder.2.2.convs.convs1.0.0.weight",
+      "encoder.encoder.2.2.pwconv.0.0.weight",
+      "encoder.encoder.2.2.pwconv.1.0.weight",
+      "encoder.encoder.2.3.convs.convs1.0.0.weight",
+      "encoder.encoder.2.3.pwconv.0.0.weight",
+      "encoder.encoder.2.3.pwconv.1.0.weight",
+      "encoder.encoder.2.4.convs.convs1.0.0.weight",
+      "encoder.encoder.2.4.pwconv.0.0.weight",
+      "encoder.encoder.2.4.pwconv.1.0.weight",
+      "encoder.encoder.2.5.gate",
+      "encoder.encoder.2.5.pwconv.0.weight",
+      "encoder.encoder.3.0.convs1.0.0.weight",
+      "encoder.encoder.3.0.convs2.0.0.weight",
+      "encoder.encoder.3.1.convs.convs1.0.0.weight",
+      "encoder.encoder.3.1.pwconv.0.0.weight",
+      "encoder.encoder.3.1.pwconv.1.0.weight",
+      "encoder.encoder.3.2.convs.convs1.0.0.weight",
+      "encoder.encoder.3.2.pwconv.0.0.weight",
+      "encoder.encoder.3.2.pwconv.1.0.weight",
+      "encoder.encoder.3.3.gate",
+      "encoder.encoder.3.3.pwconv.0.weight",
+      "encoder.encoder.4.0.convs1.0.0.weight",
+      "encoder.encoder.4.0.convs2.0.0.weight",
+      "encoder.encoder.4.1.convs.convs1.0.0.weight",
+      "encoder.encoder.4.1.pwconv.0.0.weight",
+      "encoder.encoder.4.1.pwconv.1.0.weight",
+      "encoder.encoder.4.2.convs.convs1.0.0.weight",
+      "encoder.encoder.4.2.pwconv.0.0.weight",
+      "encoder.encoder.4.2.pwconv.1.0.weight",
+      "encoder.encoder.4.3.gate",
+      "encoder.encoder.4.3.pwconv.0.weight",
+      "encoder.pe_encoder.1.0.0.weight",
+      "encoder.pe_encoder.2.0.0.weight",
+      "encoder.pe_encoder.3.0.0.weight",
+      "encoder.pe_encoder.4.0.0.weight",
+      "decoder.decoder.0.0.convs.0.0.weight",
+      "decoder.decoder.0.0.convs.1.0.weight",
+      "decoder.decoder.1.0.convs.0.0.weight",
+      "decoder.decoder.1.0.convs.1.0.weight",
+      "decoder.decoder.2.0.convs.0.0.weight",
+      "decoder.decoder.2.0.convs.1.0.weight",
+      "decoder.decoder.3.0.convs.0.0.weight",
+      "decoder.decoder.3.0.convs.1.0.weight",
+      "head.head.0.0.weight",
+      "head.head.2.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
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+      "encoder.encoder.1.0.convs1.0.1.weight",
+      "encoder.encoder.1.0.convs1.0.1.bias",
+      "encoder.encoder.1.0.convs2.0.1.weight",
+      "encoder.encoder.1.0.convs2.0.1.bias",
+      "encoder.encoder.1.1.convs.convs1.0.1.weight",
+      "encoder.encoder.1.1.convs.convs1.0.1.bias",
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+      "encoder.encoder.1.2.convs.convs1.0.1.bias",
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+      "encoder.encoder.1.2.pwconv.1.1.weight",
+      "encoder.encoder.1.2.pwconv.1.1.bias",
+      "encoder.encoder.1.3.a",
+      "encoder.encoder.1.3.b",
+      "encoder.encoder.1.3.c",
+      "encoder.encoder.1.3.pwconv.0.bias",
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+      "encoder.encoder.2.5.a",
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+      "decoder.decoder.1.0.convs.1.1.bias",
+      "decoder.decoder.2.0.convs.0.1.weight",
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+      "decoder.decoder.3.0.convs.1.1.weight",
+      "decoder.decoder.3.0.convs.1.1.bias",
+      "head.head.0.1.weight",
+      "head.head.0.1.bias",
+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[04/19 00:13:49] S3DIS INFO: 
+Totally 68 samples in val set
+[04/19 00:13:49] S3DIS INFO: length of validation dataset: 68
+[04/19 00:13:49] S3DIS INFO: number of classes of the dataset: 13
+[04/19 00:13:49] S3DIS INFO: Training from scratch
+[04/19 00:13:49] S3DIS INFO: 
+Totally 204 samples in train set
+[04/19 00:13:49] S3DIS INFO: length of training dataset: 6120
+[04/19 00:17:38] S3DIS INFO: Find a better ckpt @E1, val_miou 4.70 val_macc 10.47, val_oa 11.99
+mious: [ 3.79 20.47  9.4   0.02  1.83  3.47  1.23  0.51  5.38  0.29  7.86  0.04
+  6.74]
+[04/19 00:17:38] S3DIS INFO: Epoch 1 LR 0.000001 train_miou 3.23, val_miou 4.70, best val miou 4.70
+[04/19 00:17:39] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:21:28] S3DIS INFO: Find a better ckpt @E2, val_miou 31.79 val_macc 42.15, val_oa 73.00
+mious: [88.97 96.19 68.88  0.    0.    0.   11.83 59.67 33.52  0.   30.35  0.
+ 23.81]
+[04/19 00:21:28] S3DIS INFO: Epoch 2 LR 0.010000 train_miou 36.30, val_miou 31.79, best val miou 31.79
+[04/19 00:21:28] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:25:16] S3DIS INFO: Find a better ckpt @E3, val_miou 41.78 val_macc 48.43, val_oa 79.57
+mious: [85.61 97.28 73.23  0.    0.   30.18 18.96 62.18 71.75  0.   63.23  0.
+ 40.73]
+[04/19 00:25:16] S3DIS INFO: Epoch 3 LR 0.019980 train_miou 45.58, val_miou 41.78, best val miou 41.78
+[04/19 00:25:16] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:29:10] S3DIS INFO: Find a better ckpt @E4, val_miou 44.73 val_macc 50.87, val_oa 82.71
+mious: [89.89 97.38 71.99  0.    0.   19.08 34.81 71.51 80.42  0.   68.96  0.
+ 47.41]
+[04/19 00:29:10] S3DIS INFO: Epoch 4 LR 0.019956 train_miou 49.04, val_miou 44.73, best val miou 44.73
+[04/19 00:29:11] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:33:01] S3DIS INFO: Find a better ckpt @E5, val_miou 48.46 val_macc 56.71, val_oa 83.33
+mious: [91.05 95.87 75.8   0.    0.   39.27 39.   68.02 79.84  0.   67.27 25.07
+ 48.84]
+[04/19 00:33:01] S3DIS INFO: Epoch 5 LR 0.019921 train_miou 52.55, val_miou 48.46, best val miou 48.46
+[04/19 00:33:01] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:36:56] S3DIS INFO: Find a better ckpt @E6, val_miou 49.92 val_macc 57.43, val_oa 83.63
+mious: [90.   97.19 76.94  0.01  0.   36.95 47.99 66.22 67.05  0.   66.54 52.43
+ 47.67]
+[04/19 00:36:56] S3DIS INFO: Epoch 6 LR 0.019877 train_miou 55.70, val_miou 49.92, best val miou 49.92
+[04/19 00:36:57] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:40:50] S3DIS INFO: Epoch 7 LR 0.019823 train_miou 58.62, val_miou 44.42, best val miou 49.92
+[04/19 00:44:46] S3DIS INFO: Find a better ckpt @E8, val_miou 58.97 val_macc 67.42, val_oa 85.42
+mious: [92.87 97.34 77.73  0.   16.8  54.83 44.96 70.67 81.05 53.78 65.63 58.66
+ 52.36]
+[04/19 00:44:46] S3DIS INFO: Epoch 8 LR 0.019759 train_miou 63.53, val_miou 58.97, best val miou 58.97
+[04/19 00:44:46] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 00:48:37] S3DIS INFO: Epoch 9 LR 0.019686 train_miou 66.22, val_miou 55.15, best val miou 58.97
+[04/19 00:52:28] S3DIS INFO: Epoch 10 LR 0.019603 train_miou 68.29, val_miou 57.69, best val miou 58.97
+[04/19 00:56:19] S3DIS INFO: Find a better ckpt @E11, val_miou 60.11 val_macc 72.90, val_oa 86.63
+mious: [91.29 97.28 80.77  0.   37.95 53.07 60.21 77.8  72.77 32.34 65.9  58.67
+ 53.35]
+[04/19 00:56:19] S3DIS INFO: Epoch 11 LR 0.019511 train_miou 69.63, val_miou 60.11, best val miou 60.11
+[04/19 00:56:19] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:00:09] S3DIS INFO: Find a better ckpt @E12, val_miou 61.70 val_macc 68.56, val_oa 86.51
+mious: [92.35 97.55 75.47  0.   32.96 50.27 38.26 78.69 88.63 63.24 73.88 56.13
+ 54.64]
+[04/19 01:00:09] S3DIS INFO: Epoch 12 LR 0.019409 train_miou 71.11, val_miou 61.70, best val miou 61.70
+[04/19 01:00:09] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:04:02] S3DIS INFO: Epoch 13 LR 0.019298 train_miou 72.54, val_miou 61.48, best val miou 61.70
+[04/19 01:07:53] S3DIS INFO: Find a better ckpt @E14, val_miou 62.54 val_macc 68.97, val_oa 87.45
+mious: [90.6  97.62 78.92  0.   37.53 53.38 51.59 78.37 86.79 41.23 76.35 65.67
+ 55.01]
+[04/19 01:07:53] S3DIS INFO: Epoch 14 LR 0.019178 train_miou 73.42, val_miou 62.54, best val miou 62.54
+[04/19 01:07:53] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:11:41] S3DIS INFO: Find a better ckpt @E15, val_miou 64.02 val_macc 71.22, val_oa 87.54
+mious: [92.88 97.59 78.4   0.   33.63 50.93 55.4  79.1  89.12 57.2  73.42 68.27
+ 56.36]
+[04/19 01:11:41] S3DIS INFO: Epoch 15 LR 0.019049 train_miou 74.47, val_miou 64.02, best val miou 64.02
+[04/19 01:11:41] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:15:33] S3DIS INFO: Epoch 16 LR 0.018911 train_miou 75.26, val_miou 60.36, best val miou 64.02
+[04/19 01:19:26] S3DIS INFO: Epoch 17 LR 0.018764 train_miou 75.77, val_miou 61.57, best val miou 64.02
+[04/19 01:23:23] S3DIS INFO: Find a better ckpt @E18, val_miou 64.27 val_macc 71.63, val_oa 88.45
+mious: [93.13 97.67 82.15  0.   32.89 56.01 59.75 78.99 88.4  50.03 72.71 65.22
+ 58.52]
+[04/19 01:23:23] S3DIS INFO: Epoch 18 LR 0.018608 train_miou 76.08, val_miou 64.27, best val miou 64.27
+[04/19 01:23:23] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:27:12] S3DIS INFO: Find a better ckpt @E19, val_miou 64.57 val_macc 71.58, val_oa 88.16
+mious: [92.84 97.66 80.35  0.   33.78 53.   62.89 76.94 84.88 62.24 73.74 64.37
+ 56.68]
+[04/19 01:27:12] S3DIS INFO: Epoch 19 LR 0.018444 train_miou 77.52, val_miou 64.57, best val miou 64.57
+[04/19 01:27:12] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:31:08] S3DIS INFO: Find a better ckpt @E20, val_miou 65.60 val_macc 71.97, val_oa 88.23
+mious: [92.98 97.75 81.07  0.   33.68 56.05 51.03 78.55 88.82 72.91 72.13 69.59
+ 58.29]
+[04/19 01:31:08] S3DIS INFO: Epoch 20 LR 0.018272 train_miou 78.31, val_miou 65.60, best val miou 65.60
+[04/19 01:31:08] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:35:02] S3DIS INFO: Epoch 21 LR 0.018091 train_miou 78.29, val_miou 62.42, best val miou 65.60
+[04/19 01:38:58] S3DIS INFO: Find a better ckpt @E22, val_miou 66.28 val_macc 72.93, val_oa 89.02
+mious: [93.14 97.67 81.41  0.   37.04 55.36 63.   78.64 88.7  59.32 76.04 69.9
+ 61.36]
+[04/19 01:38:58] S3DIS INFO: Epoch 22 LR 0.017903 train_miou 79.14, val_miou 66.28, best val miou 66.28
+[04/19 01:38:58] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:42:49] S3DIS INFO: Epoch 23 LR 0.017706 train_miou 79.43, val_miou 63.25, best val miou 66.28
+[04/19 01:46:41] S3DIS INFO: Find a better ckpt @E24, val_miou 66.70 val_macc 73.09, val_oa 88.37
+mious: [93.02 97.77 80.27  0.   40.11 54.3  57.68 79.51 88.15 70.49 73.81 73.19
+ 58.83]
+[04/19 01:46:41] S3DIS INFO: Epoch 24 LR 0.017502 train_miou 79.93, val_miou 66.70, best val miou 66.70
+[04/19 01:46:41] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 01:50:34] S3DIS INFO: Epoch 25 LR 0.017291 train_miou 80.08, val_miou 65.29, best val miou 66.70
+[04/19 01:54:26] S3DIS INFO: Epoch 26 LR 0.017073 train_miou 80.99, val_miou 65.32, best val miou 66.70
+[04/19 01:58:18] S3DIS INFO: Epoch 27 LR 0.016847 train_miou 81.14, val_miou 66.02, best val miou 66.70
+[04/19 02:02:12] S3DIS INFO: Epoch 28 LR 0.016615 train_miou 81.55, val_miou 65.08, best val miou 66.70
+[04/19 02:05:59] S3DIS INFO: Epoch 29 LR 0.016376 train_miou 82.08, val_miou 65.79, best val miou 66.70
+[04/19 02:09:50] S3DIS INFO: Epoch 30 LR 0.016131 train_miou 82.29, val_miou 64.68, best val miou 66.70
+[04/19 02:13:40] S3DIS INFO: Epoch 31 LR 0.015880 train_miou 82.29, val_miou 65.95, best val miou 66.70
+[04/19 02:17:30] S3DIS INFO: Epoch 32 LR 0.015623 train_miou 82.34, val_miou 66.47, best val miou 66.70
+[04/19 02:21:22] S3DIS INFO: Epoch 33 LR 0.015361 train_miou 83.03, val_miou 65.95, best val miou 66.70
+[04/19 02:25:15] S3DIS INFO: Epoch 34 LR 0.015093 train_miou 83.27, val_miou 65.68, best val miou 66.70
+[04/19 02:29:06] S3DIS INFO: Epoch 35 LR 0.014820 train_miou 83.14, val_miou 66.42, best val miou 66.70
+[04/19 02:33:00] S3DIS INFO: Epoch 36 LR 0.014543 train_miou 83.75, val_miou 64.84, best val miou 66.70
+[04/19 02:36:53] S3DIS INFO: Epoch 37 LR 0.014261 train_miou 83.40, val_miou 65.48, best val miou 66.70
+[04/19 02:40:47] S3DIS INFO: Epoch 38 LR 0.013974 train_miou 83.73, val_miou 64.60, best val miou 66.70
+[04/19 02:44:37] S3DIS INFO: Epoch 39 LR 0.013684 train_miou 83.93, val_miou 65.80, best val miou 66.70
+[04/19 02:48:28] S3DIS INFO: Find a better ckpt @E40, val_miou 68.45 val_macc 75.06, val_oa 89.18
+mious: [93.14 97.74 81.05  0.   36.01 55.1  71.54 80.23 89.82 75.46 76.27 72.4
+ 61.12]
+[04/19 02:48:28] S3DIS INFO: Epoch 40 LR 0.013391 train_miou 83.84, val_miou 68.45, best val miou 68.45
+[04/19 02:48:28] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 02:52:23] S3DIS INFO: Epoch 41 LR 0.013094 train_miou 84.40, val_miou 64.80, best val miou 68.45
+[04/19 02:56:15] S3DIS INFO: Epoch 42 LR 0.012794 train_miou 84.61, val_miou 66.37, best val miou 68.45
+[04/19 03:00:07] S3DIS INFO: Epoch 43 LR 0.012491 train_miou 84.18, val_miou 68.20, best val miou 68.45
+[04/19 03:04:02] S3DIS INFO: Epoch 44 LR 0.012185 train_miou 84.90, val_miou 66.84, best val miou 68.45
+[04/19 03:07:52] S3DIS INFO: Epoch 45 LR 0.011878 train_miou 84.95, val_miou 66.83, best val miou 68.45
+[04/19 03:11:42] S3DIS INFO: Epoch 46 LR 0.011569 train_miou 85.16, val_miou 68.43, best val miou 68.45
+[04/19 03:15:31] S3DIS INFO: Epoch 47 LR 0.011258 train_miou 85.26, val_miou 66.74, best val miou 68.45
+[04/19 03:19:21] S3DIS INFO: Epoch 48 LR 0.010946 train_miou 85.45, val_miou 66.76, best val miou 68.45
+[04/19 03:23:10] S3DIS INFO: Epoch 49 LR 0.010633 train_miou 85.55, val_miou 66.97, best val miou 68.45
+[04/19 03:27:04] S3DIS INFO: Epoch 50 LR 0.010319 train_miou 85.85, val_miou 66.85, best val miou 68.45
+[04/19 03:30:57] S3DIS INFO: Epoch 51 LR 0.010005 train_miou 85.73, val_miou 66.24, best val miou 68.45
+[04/19 03:34:50] S3DIS INFO: Epoch 52 LR 0.009691 train_miou 85.85, val_miou 66.11, best val miou 68.45
+[04/19 03:38:40] S3DIS INFO: Epoch 53 LR 0.009377 train_miou 86.08, val_miou 66.84, best val miou 68.45
+[04/19 03:42:35] S3DIS INFO: Epoch 54 LR 0.009064 train_miou 86.09, val_miou 67.35, best val miou 68.45
+[04/19 03:46:26] S3DIS INFO: Epoch 55 LR 0.008752 train_miou 86.28, val_miou 67.10, best val miou 68.45
+[04/19 03:50:16] S3DIS INFO: Find a better ckpt @E56, val_miou 68.78 val_macc 75.26, val_oa 88.97
+mious: [92.73 97.82 80.88  0.   35.67 57.   73.85 79.17 90.01 75.91 76.06 75.17
+ 59.91]
+[04/19 03:50:16] S3DIS INFO: Epoch 56 LR 0.008441 train_miou 86.05, val_miou 68.78, best val miou 68.78
+[04/19 03:50:16] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 03:54:08] S3DIS INFO: Epoch 57 LR 0.008132 train_miou 86.49, val_miou 68.01, best val miou 68.78
+[04/19 03:57:59] S3DIS INFO: Epoch 58 LR 0.007825 train_miou 86.67, val_miou 67.68, best val miou 68.78
+[04/19 04:01:46] S3DIS INFO: Epoch 59 LR 0.007519 train_miou 86.42, val_miou 67.58, best val miou 68.78
+[04/19 04:05:37] S3DIS INFO: Epoch 60 LR 0.007216 train_miou 86.62, val_miou 67.96, best val miou 68.78
+[04/19 04:09:26] S3DIS INFO: Epoch 61 LR 0.006916 train_miou 86.90, val_miou 67.25, best val miou 68.78
+[04/19 04:13:23] S3DIS INFO: Epoch 62 LR 0.006619 train_miou 86.98, val_miou 68.09, best val miou 68.78
+[04/19 04:17:16] S3DIS INFO: Epoch 63 LR 0.006326 train_miou 86.96, val_miou 66.22, best val miou 68.78
+[04/19 04:21:09] S3DIS INFO: Epoch 64 LR 0.006036 train_miou 87.01, val_miou 68.52, best val miou 68.78
+[04/19 04:25:04] S3DIS INFO: Epoch 65 LR 0.005749 train_miou 87.21, val_miou 68.21, best val miou 68.78
+[04/19 04:28:57] S3DIS INFO: Epoch 66 LR 0.005467 train_miou 87.38, val_miou 67.92, best val miou 68.78
+[04/19 04:32:52] S3DIS INFO: Epoch 67 LR 0.005190 train_miou 87.33, val_miou 67.18, best val miou 68.78
+[04/19 04:36:42] S3DIS INFO: Epoch 68 LR 0.004917 train_miou 87.36, val_miou 68.61, best val miou 68.78
+[04/19 04:40:35] S3DIS INFO: Epoch 69 LR 0.004649 train_miou 87.42, val_miou 68.21, best val miou 68.78
+[04/19 04:44:31] S3DIS INFO: Epoch 70 LR 0.004387 train_miou 87.51, val_miou 67.90, best val miou 68.78
+[04/19 04:48:22] S3DIS INFO: Epoch 71 LR 0.004130 train_miou 87.63, val_miou 68.08, best val miou 68.78
+[04/19 04:52:17] S3DIS INFO: Epoch 72 LR 0.003879 train_miou 87.66, val_miou 68.47, best val miou 68.78
+[04/19 04:56:10] S3DIS INFO: Epoch 73 LR 0.003634 train_miou 87.58, val_miou 68.54, best val miou 68.78
+[04/19 04:59:58] S3DIS INFO: Epoch 74 LR 0.003395 train_miou 87.83, val_miou 68.48, best val miou 68.78
+[04/19 05:03:47] S3DIS INFO: Epoch 75 LR 0.003163 train_miou 87.88, val_miou 68.35, best val miou 68.78
+[04/19 05:07:40] S3DIS INFO: Epoch 76 LR 0.002937 train_miou 87.83, val_miou 68.11, best val miou 68.78
+[04/19 05:11:30] S3DIS INFO: Epoch 77 LR 0.002719 train_miou 87.98, val_miou 67.92, best val miou 68.78
+[04/19 05:15:18] S3DIS INFO: Epoch 78 LR 0.002508 train_miou 87.97, val_miou 68.54, best val miou 68.78
+[04/19 05:19:10] S3DIS INFO: Epoch 79 LR 0.002304 train_miou 87.92, val_miou 68.54, best val miou 68.78
+[04/19 05:22:59] S3DIS INFO: Epoch 80 LR 0.002107 train_miou 88.01, val_miou 68.47, best val miou 68.78
+[04/19 05:26:55] S3DIS INFO: Epoch 81 LR 0.001919 train_miou 88.05, val_miou 68.33, best val miou 68.78
+[04/19 05:30:50] S3DIS INFO: Epoch 82 LR 0.001738 train_miou 88.14, val_miou 68.40, best val miou 68.78
+[04/19 05:34:44] S3DIS INFO: Find a better ckpt @E83, val_miou 68.91 val_macc 74.93, val_oa 89.55
+mious: [93.3  97.88 82.51  0.   34.59 57.84 74.01 79.56 89.76 74.45 76.14 75.37
+ 60.4 ]
+[04/19 05:34:44] S3DIS INFO: Epoch 83 LR 0.001566 train_miou 88.15, val_miou 68.91, best val miou 68.91
+[04/19 05:34:44] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 05:38:33] S3DIS INFO: Epoch 84 LR 0.001402 train_miou 88.17, val_miou 68.58, best val miou 68.91
+[04/19 05:42:26] S3DIS INFO: Epoch 85 LR 0.001246 train_miou 88.14, val_miou 68.47, best val miou 68.91
+[04/19 05:46:16] S3DIS INFO: Epoch 86 LR 0.001099 train_miou 88.35, val_miou 68.86, best val miou 68.91
+[04/19 05:50:09] S3DIS INFO: Epoch 87 LR 0.000961 train_miou 88.25, val_miou 68.82, best val miou 68.91
+[04/19 05:54:06] S3DIS INFO: Epoch 88 LR 0.000832 train_miou 88.21, val_miou 68.66, best val miou 68.91
+[04/19 05:57:55] S3DIS INFO: Epoch 89 LR 0.000712 train_miou 88.36, val_miou 68.75, best val miou 68.91
+[04/19 06:01:45] S3DIS INFO: Epoch 90 LR 0.000601 train_miou 88.31, val_miou 68.80, best val miou 68.91
+[04/19 06:05:38] S3DIS INFO: Epoch 91 LR 0.000499 train_miou 88.34, val_miou 68.68, best val miou 68.91
+[04/19 06:09:31] S3DIS INFO: Epoch 92 LR 0.000407 train_miou 88.31, val_miou 68.36, best val miou 68.91
+[04/19 06:13:20] S3DIS INFO: Find a better ckpt @E93, val_miou 68.98 val_macc 75.20, val_oa 89.46
+mious: [93.28 97.88 82.21  0.   34.76 56.34 75.34 79.46 89.99 74.   76.09 76.96
+ 60.39]
+[04/19 06:13:20] S3DIS INFO: Epoch 93 LR 0.000324 train_miou 88.34, val_miou 68.98, best val miou 68.98
+[04/19 06:13:20] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 06:17:07] S3DIS INFO: Epoch 94 LR 0.000251 train_miou 88.31, val_miou 68.85, best val miou 68.98
+[04/19 06:20:58] S3DIS INFO: Epoch 95 LR 0.000187 train_miou 88.28, val_miou 68.63, best val miou 68.98
+[04/19 06:24:49] S3DIS INFO: Epoch 96 LR 0.000133 train_miou 88.39, val_miou 68.55, best val miou 68.98
+[04/19 06:28:42] S3DIS INFO: Epoch 97 LR 0.000089 train_miou 88.39, val_miou 68.69, best val miou 68.98
+[04/19 06:32:33] S3DIS INFO: Epoch 98 LR 0.000054 train_miou 88.31, val_miou 68.38, best val miou 68.98
+[04/19 06:36:21] S3DIS INFO: Epoch 99 LR 0.000030 train_miou 88.38, val_miou 68.62, best val miou 68.98
+[04/19 06:40:13] S3DIS INFO: Epoch 100 LR 0.000015 train_miou 88.38, val_miou 68.72, best val miou 68.98
+[04/19 06:40:13] S3DIS INFO: Best ckpt @E93,  val_oa 89.46, val_macc 75.20, val_miou 68.98, 
+iou per cls is: [93.28 97.88 82.21  0.   34.76 56.34 75.34 79.46 89.99 74.   76.09 76.96
+ 60.39]
+[04/19 06:40:13] S3DIS INFO: Successful Loading the ckpt from log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/checkpoint/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth
+[04/19 06:40:13] S3DIS INFO: ckpts @ 93 epoch( {'best_val': 68.97756958007812} )
+[04/19 06:40:13] S3DIS INFO: Test [0]/[68] cloud
+[04/19 06:40:23] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 92.65 97.71 88.14, 
+iou per cls is: [ 97.01  99.16  79.71 100.   100.   100.    97.74   0.   100.   100.
+ 100.   100.    72.13]
+[04/19 06:40:23] S3DIS INFO: Test [1]/[68] cloud
+[04/19 06:40:30] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 90.94 97.10 95.06, 
+iou per cls is: [ 97.26  99.02  75.89 100.   100.   100.    97.91 100.   100.   100.
+ 100.   100.    65.71]
+[04/19 06:40:30] S3DIS INFO: Test [2]/[68] cloud
+[04/19 06:40:45] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 92.17 93.07 73.98, 
+iou per cls is: [ 97.18  98.84  82.1    0.    50.19  74.45  97.71  93.67  94.84 100.
+   0.    96.3   76.44]
+[04/19 06:40:45] S3DIS INFO: Test [3]/[68] cloud
+[04/19 06:42:15] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 92.58 90.36 79.15, 
+iou per cls is: [ 97.13  97.41  85.89   0.    83.69 100.    93.99  92.57  92.19  99.77
+  74.91  45.42  65.97]
+[04/19 06:42:15] S3DIS INFO: Test [4]/[68] cloud
+[04/19 06:42:50] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 92.27 89.54 71.23, 
+iou per cls is: [ 96.    99.59  79.77   0.    77.48  77.71  89.14  71.2   97.31 100.
+   0.    66.95  70.9 ]
+[04/19 06:42:50] S3DIS INFO: Test [5]/[68] cloud
+[04/19 06:46:03] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 80.91 80.65 36.10, 
+iou per cls is: [91.02 98.78 48.35  0.    5.76  0.   24.87  0.    0.   72.82 90.69  0.
+ 36.99]
+[04/19 06:46:03] S3DIS INFO: Test [6]/[68] cloud
+[04/19 06:46:27] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 98.30 98.15 89.71, 
+iou per cls is: [ 98.36  99.32  97.38   0.   100.   100.    77.4  100.   100.   100.
+ 100.   100.    93.8 ]
+[04/19 06:46:27] S3DIS INFO: Test [7]/[68] cloud
+[04/19 06:46:40] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 97.53 97.92 89.93, 
+iou per cls is: [ 96.65  98.63  96.01 100.   100.   100.    77.85 100.   100.   100.
+ 100.   100.     0.  ]
+[04/19 06:46:40] S3DIS INFO: Test [8]/[68] cloud
+[04/19 06:46:53] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.30 98.36 96.50, 
+iou per cls is: [ 97.49  98.99  97.25 100.   100.   100.    82.88 100.   100.   100.
+ 100.   100.    77.91]
+[04/19 06:46:53] S3DIS INFO: Test [9]/[68] cloud
+[04/19 06:47:20] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 89.94 90.93 76.37, 
+iou per cls is: [ 98.61  99.28  86.76 100.     0.     0.    26.85 100.   100.   100.
+ 100.   100.    81.35]
+[04/19 06:47:20] S3DIS INFO: Test [10]/[68] cloud
+[04/19 06:47:28] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 93.94 95.29 71.35, 
+iou per cls is: [ 97.05  98.83  90.7  100.     0.   100.    53.02 100.   100.   100.
+   0.     0.    87.9 ]
+[04/19 06:47:28] S3DIS INFO: Test [11]/[68] cloud
+[04/19 06:47:59] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 85.27 82.42 60.97, 
+iou per cls is: [ 97.58  99.07  68.56 100.     0.     0.    50.06   0.   100.   100.
+   0.   100.    77.38]
+[04/19 06:47:59] S3DIS INFO: Test [12]/[68] cloud
+[04/19 06:52:59] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 89.82 94.75 39.88, 
+iou per cls is: [ 94.18  98.93  82.31   0.     0.     0.    51.45   0.     0.   100.
+   0.     0.    91.51]
+[04/19 06:52:59] S3DIS INFO: Test [13]/[68] cloud
+[04/19 06:53:19] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 96.18 92.63 61.35, 
+iou per cls is: [ 97.92  98.36  94.51 100.     0.   100.    19.19   0.   100.   100.
+   0.     0.    87.51]
+[04/19 06:53:19] S3DIS INFO: Test [14]/[68] cloud
+[04/19 06:53:34] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 94.58 84.90 52.67, 
+iou per cls is: [ 98.12  99.37  94.52 100.   100.     0.    83.61   0.     0.    71.23
+  30.97   0.     6.83]
+[04/19 06:53:34] S3DIS INFO: Test [15]/[68] cloud
+[04/19 06:55:19] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 96.44 90.01 55.97, 
+iou per cls is: [ 99.16  99.86  95.06 100.     0.     0.    65.62   0.     0.    31.95
+  80.48 100.    55.45]
+[04/19 06:55:19] S3DIS INFO: Test [16]/[68] cloud
+[04/19 06:55:32] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 95.52 97.72 95.74, 
+iou per cls is: [ 97.52  98.94  91.47 100.   100.   100.    83.27 100.   100.   100.
+ 100.   100.    73.36]
+[04/19 06:55:32] S3DIS INFO: Test [17]/[68] cloud
+[04/19 06:55:56] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 95.83 97.64 65.88, 
+iou per cls is: [ 98.61  99.16  92.57   0.   100.   100.    83.65   0.   100.   100.
+   0.     0.    82.39]
+[04/19 06:55:56] S3DIS INFO: Test [18]/[68] cloud
+[04/19 06:56:01] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 96.93 93.09 84.78, 
+iou per cls is: [ 96.77  99.46  94.15 100.   100.   100.    79.23   0.   100.   100.
+ 100.   100.    32.51]
+[04/19 06:56:01] S3DIS INFO: Test [19]/[68] cloud
+[04/19 06:56:26] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 96.06 82.74 72.91, 
+iou per cls is: [ 96.11  99.23  93.64 100.     0.38   0.    75.1  100.   100.   100.
+   0.   100.    83.39]
+[04/19 06:56:26] S3DIS INFO: Test [20]/[68] cloud
+[04/19 06:56:46] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 95.72 94.59 62.56, 
+iou per cls is: [ 99.52  98.21  91.55 100.     0.   100.   100.    93.26  92.08   0.
+   0.     0.    38.72]
+[04/19 06:56:46] S3DIS INFO: Test [21]/[68] cloud
+[04/19 06:56:56] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 92.00 89.34 69.73, 
+iou per cls is: [97.74 98.48 67.74  0.   57.82 78.57 96.7  92.25 95.65  0.   97.98 60.4
+ 63.18]
+[04/19 06:56:56] S3DIS INFO: Test [22]/[68] cloud
+[04/19 06:57:07] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 92.86 89.71 77.63, 
+iou per cls is: [ 98.42  98.46  74.87   0.    20.33  91.26  96.39  79.46  96.66 100.
+  94.77  92.2   66.42]
+[04/19 06:57:07] S3DIS INFO: Test [23]/[68] cloud
+[04/19 06:57:18] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 95.70 88.88 76.69, 
+iou per cls is: [ 97.73  97.87  81.57   0.     8.11  81.11  98.09  72.87  87.72 100.
+  97.2   94.63  80.04]
+[04/19 06:57:18] S3DIS INFO: Test [24]/[68] cloud
+[04/19 06:57:30] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 91.92 93.22 80.45, 
+iou per cls is: [ 97.63  96.72  79.2    0.    77.18  81.27  91.85  85.06  82.45 100.
+  90.97 100.    63.52]
+[04/19 06:57:30] S3DIS INFO: Test [25]/[68] cloud
+[04/19 06:57:46] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 90.69 86.11 73.15, 
+iou per cls is: [ 98.28  97.85  72.62   0.    31.8   87.33  33.63  86.29  94.72 100.
+  89.6   92.41  66.44]
+[04/19 06:57:46] S3DIS INFO: Test [26]/[68] cloud
+[04/19 06:58:11] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 85.58 84.23 70.06, 
+iou per cls is: [ 93.95  97.97  72.16   0.    16.69  40.2   93.07  68.62  91.   100.
+  81.49  95.34  60.32]
+[04/19 06:58:11] S3DIS INFO: Test [27]/[68] cloud
+[04/19 06:58:39] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 91.87 92.07 79.77, 
+iou per cls is: [ 95.43  98.56  80.88   0.    61.79  80.3   88.    86.51  96.58 100.
+  89.85  94.26  64.8 ]
+[04/19 06:58:39] S3DIS INFO: Test [28]/[68] cloud
+[04/19 06:58:50] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 93.12 87.92 76.55, 
+iou per cls is: [ 98.57  98.35  90.71   0.    57.35 100.    96.86  87.    94.02 100.
+  34.13  74.86  63.36]
+[04/19 06:58:50] S3DIS INFO: Test [29]/[68] cloud
+[04/19 06:59:05] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 87.67 92.11 72.28, 
+iou per cls is: [ 97.45  98.68  96.19   0.     0.   100.    95.62  45.91 100.   100.
+  56.71 100.    49.13]
+[04/19 06:59:05] S3DIS INFO: Test [30]/[68] cloud
+[04/19 06:59:29] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 95.71 90.82 80.06, 
+iou per cls is: [ 99.23  98.85  94.78   0.    49.79 100.    91.98  98.06  93.47 100.
+  80.58  66.84  67.19]
+[04/19 06:59:29] S3DIS INFO: Test [31]/[68] cloud
+[04/19 07:00:14] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 86.01 91.26 70.54, 
+iou per cls is: [ 94.45  99.14  75.13   0.     0.   100.    89.91  87.18  94.64 100.
+  56.62  77.84  42.07]
+[04/19 07:00:14] S3DIS INFO: Test [32]/[68] cloud
+[04/19 07:00:27] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 94.62 88.66 77.91, 
+iou per cls is: [ 98.22  98.11  78.5    0.     2.68  79.15  96.99  88.56  95.55 100.
+  96.74  89.95  88.39]
+[04/19 07:00:27] S3DIS INFO: Test [33]/[68] cloud
+[04/19 07:00:32] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 90.84 92.97 80.19, 
+iou per cls is: [ 98.17  97.43  82.89   0.    67.05 100.    85.84  91.72  93.73 100.
+  64.35 100.    61.27]
+[04/19 07:00:32] S3DIS INFO: Test [34]/[68] cloud
+[04/19 07:01:35] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 92.96 92.66 71.48, 
+iou per cls is: [ 98.75  99.43  87.61   0.    80.57   0.    97.36  91.53  91.78 100.
+  44.07  94.91  43.25]
+[04/19 07:01:35] S3DIS INFO: Test [35]/[68] cloud
+[04/19 07:01:46] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 92.49 87.49 75.88, 
+iou per cls is: [ 96.79  98.27  78.34   0.     4.98  77.29  97.69  84.14  93.72 100.
+  93.62  86.89  74.67]
+[04/19 07:01:46] S3DIS INFO: Test [36]/[68] cloud
+[04/19 07:02:01] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 93.19 91.76 80.15, 
+iou per cls is: [ 97.79  97.35  82.05   0.    60.96  72.04  90.85  87.52  90.09 100.
+  93.93  93.84  75.49]
+[04/19 07:02:01] S3DIS INFO: Test [37]/[68] cloud
+[04/19 07:02:42] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 83.74 85.76 70.25, 
+iou per cls is: [97.28 94.73 61.46  0.   67.3  84.24 82.8  80.15 84.67 72.39 50.06 91.1
+ 47.05]
+[04/19 07:02:42] S3DIS INFO: Test [38]/[68] cloud
+[04/19 07:02:49] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 90.94 93.20 80.87, 
+iou per cls is: [ 96.74  95.58  85.66   0.   100.    83.91  92.13  80.14  98.26 100.
+  79.34  80.77  58.71]
+[04/19 07:02:49] S3DIS INFO: Test [39]/[68] cloud
+[04/19 07:03:00] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 86.16 83.58 69.13, 
+iou per cls is: [ 95.46  97.55  80.92   0.    49.82  80.13  95.91  81.76  95.19 100.
+  64.12   8.6   49.16]
+[04/19 07:03:00] S3DIS INFO: Test [40]/[68] cloud
+[04/19 07:03:10] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 91.71 87.43 68.43, 
+iou per cls is: [96.48 99.24 81.43  0.    7.72 85.11 93.01 89.12 96.83  0.   90.61 85.68
+ 64.37]
+[04/19 07:03:10] S3DIS INFO: Test [41]/[68] cloud
+[04/19 07:03:21] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 93.94 91.92 80.52, 
+iou per cls is: [ 97.37  98.92  88.26   0.    72.87  90.11  85.85  83.04  90.89 100.
+  90.31  92.78  56.34]
+[04/19 07:03:21] S3DIS INFO: Test [42]/[68] cloud
+[04/19 07:04:06] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 80.08 85.18 69.94, 
+iou per cls is: [ 97.23  98.1   57.35   0.    62.82  58.62  96.5   87.54  93.06 100.
+  21.98  93.55  42.4 ]
+[04/19 07:04:06] S3DIS INFO: Test [43]/[68] cloud
+[04/19 07:04:16] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 92.81 93.83 67.10, 
+iou per cls is: [97.84 98.24 75.6   0.    0.   84.37 97.18 83.85 94.79  0.   91.88 92.9
+ 55.62]
+[04/19 07:04:16] S3DIS INFO: Test [44]/[68] cloud
+[04/19 07:04:21] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 96.77 96.57 94.27, 
+iou per cls is: [ 94.22  97.42  95.37 100.   100.   100.    93.39  84.17  94.05 100.
+  95.13  93.83  77.9 ]
+[04/19 07:04:21] S3DIS INFO: Test [45]/[68] cloud
+[04/19 07:04:35] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 89.47 90.10 77.60, 
+iou per cls is: [ 97.19  99.47  63.88   0.    20.77  87.01  91.36  91.74  94.42 100.
+  89.9  100.    73.01]
+[04/19 07:04:35] S3DIS INFO: Test [46]/[68] cloud
+[04/19 07:04:45] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 91.10 88.91 77.35, 
+iou per cls is: [ 96.7   99.44  75.81   0.     9.59  91.23  86.43  90.49  91.88 100.
+  86.1  100.    77.92]
+[04/19 07:04:45] S3DIS INFO: Test [47]/[68] cloud
+[04/19 07:05:01] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 93.30 89.72 78.44, 
+iou per cls is: [ 97.05  99.76  83.7    0.    12.05  89.16  96.72  89.36  96.38 100.
+  90.68  93.45  71.36]
+[04/19 07:05:01] S3DIS INFO: Test [48]/[68] cloud
+[04/19 07:05:17] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 86.73 87.44 74.12, 
+iou per cls is: [ 96.27  97.79  70.52   0.    29.72  86.01  95.62  66.85  96.25 100.
+  75.12  93.47  55.86]
+[04/19 07:05:17] S3DIS INFO: Test [49]/[68] cloud
+[04/19 07:05:32] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 97.77 97.62 88.71, 
+iou per cls is: [ 98.62  96.7   94.71   0.   100.   100.    97.72  94.76  92.87 100.
+  95.8   94.19  87.9 ]
+[04/19 07:05:32] S3DIS INFO: Test [50]/[68] cloud
+[04/19 07:05:56] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.80 93.30 79.97, 
+iou per cls is: [ 98.61  96.79  94.74   0.   100.   100.    95.94  77.07  94.99 100.
+  50.29  92.13  38.99]
+[04/19 07:05:56] S3DIS INFO: Test [51]/[68] cloud
+[04/19 07:07:50] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 83.82 80.27 58.73, 
+iou per cls is: [ 75.32  98.68  79.3    0.     0.02 100.    67.61  73.65  83.47   0.
+  67.72  60.1   57.57]
+[04/19 07:07:50] S3DIS INFO: Test [52]/[68] cloud
+[04/19 07:10:08] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 79.52 84.92 53.11, 
+iou per cls is: [73.97 97.48 64.9   0.   36.19  0.   82.94 60.41 78.96 74.28 66.11  0.
+ 55.18]
+[04/19 07:10:08] S3DIS INFO: Test [53]/[68] cloud
+[04/19 07:10:22] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 90.96 85.03 72.21, 
+iou per cls is: [ 92.87  98.27  91.91   0.     0.   100.    88.8   86.47  92.92 100.
+  50.45  83.81  53.23]
+[04/19 07:10:22] S3DIS INFO: Test [54]/[68] cloud
+[04/19 07:10:33] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 95.72 92.66 81.51, 
+iou per cls is: [ 97.77  98.44  84.47   0.    42.72  82.39  95.53  93.62  96.46 100.
+  96.9   93.22  78.05]
+[04/19 07:10:33] S3DIS INFO: Test [55]/[68] cloud
+[04/19 07:12:43] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 90.52 87.17 74.52, 
+iou per cls is: [ 97.63  96.82  88.84 100.    68.93 100.    87.13  77.14  84.37   0.
+  75.83  36.66  55.45]
+[04/19 07:12:43] S3DIS INFO: Test [56]/[68] cloud
+[04/19 07:13:21] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 92.94 93.46 79.57, 
+iou per cls is: [ 97.59  98.22  78.23   0.    55.69  86.24  97.43  87.75  83.25 100.
+  80.7   91.2   78.1 ]
+[04/19 07:13:21] S3DIS INFO: Test [57]/[68] cloud
+[04/19 07:13:37] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 91.16 91.80 78.65, 
+iou per cls is: [ 97.58  97.95  72.68   0.    43.35  67.35  92.97  88.86  96.68 100.
+  89.86 100.    75.12]
+[04/19 07:13:37] S3DIS INFO: Test [58]/[68] cloud
+[04/19 07:13:46] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 96.17 97.24 79.64, 
+iou per cls is: [ 97.56  98.32  89.96   0.     0.    78.45  95.73  93.74  98.75 100.
+  95.33 100.    87.43]
+[04/19 07:13:46] S3DIS INFO: Test [59]/[68] cloud
+[04/19 07:13:56] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 93.03 92.94 73.52, 
+iou per cls is: [ 97.9   97.75  77.1    0.     0.    63.92  93.32  82.58  81.55 100.
+  91.83  96.54  73.23]
+[04/19 07:13:56] S3DIS INFO: Test [60]/[68] cloud
+[04/19 07:14:10] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 92.54 86.68 75.04, 
+iou per cls is: [ 98.24  98.13  71.54   0.     5.27  76.69  93.36  83.79  95.65 100.
+  92.55  86.59  73.72]
+[04/19 07:14:10] S3DIS INFO: Test [61]/[68] cloud
+[04/19 07:14:26] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 94.08 90.06 76.94, 
+iou per cls is: [ 98.36  96.47  81.26   0.    33.9   61.84  97.03  92.22  92.96 100.
+  96.69  94.93  54.54]
+[04/19 07:14:26] S3DIS INFO: Test [62]/[68] cloud
+[04/19 07:14:37] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 94.48 95.43 76.04, 
+iou per cls is: [ 96.73  96.05  89.25   0.     0.    78.54  98.51  77.36  97.62  82.72
+  95.91 100.    75.86]
+[04/19 07:14:37] S3DIS INFO: Test [63]/[68] cloud
+[04/19 07:14:45] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 78.35 94.22 55.18, 
+iou per cls is: [ 94.13  97.35  94.13 100.     0.   100.     0.     0.   100.   100.
+   0.     0.    31.7 ]
+[04/19 07:14:45] S3DIS INFO: Test [64]/[68] cloud
+[04/19 07:14:53] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 80.40 81.33 67.73, 
+iou per cls is: [ 92.57  96.48  76.21   0.    12.93   0.    88.36 100.   100.   100.
+  84.37 100.    29.63]
+[04/19 07:14:53] S3DIS INFO: Test [65]/[68] cloud
+[04/19 07:15:06] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 80.09 91.09 70.94, 
+iou per cls is: [ 55.65  96.99  74.27 100.   100.   100.    71.24   0.   100.   100.
+  67.58   0.    56.54]
+[04/19 07:15:06] S3DIS INFO: Test [66]/[68] cloud
+[04/19 07:15:07] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 86.69 94.61 70.64, 
+iou per cls is: [ 73.32  99.62  91.48 100.   100.   100.    95.38 100.     0.   100.
+   0.     0.    58.51]
+[04/19 07:15:07] S3DIS INFO: Test [67]/[68] cloud
+[04/19 07:15:16] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 85.64 86.58 61.74, 
+iou per cls is: [ 91.13  98.83  91.58   0.   100.   100.    51.37  60.24  65.44 100.
+   0.     0.    44.04]
+[04/19 07:15:16] S3DIS INFO: Best ckpt @E93,  test_oa 90.48, test_macc 76.11, test_miou 70.08, 
+iou per cls is: [94.68 98.51 83.74  0.   35.43 59.81 76.37 81.78 90.65 74.93 77.01 77.3
+ 60.81]
+[04/19 07:15:16] S3DIS INFO: save results in log/s3dis/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB/s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB.csv

s3dis-train-pointmetabase-ctwc-l-ngpus1-20260419-001349-Xkb85zg5HJa2RydLXjcBxB_ckpt_best.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:6dac78d3c11c93af8fbc86b3e9a26ab9a1f5b78f585ecd64811c26cc627ba738
+size 37589006

s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73.log

@@ -0,0 +1,1360 @@
+[04/18 16:14:12] S3DIS INFO: dist_url: tcp://localhost:8888
+dist_backend: nccl
+multiprocessing_distributed: False
+ngpus_per_node: 1
+world_size: 1
+launcher: mp
+local_rank: 0
+use_gpu: True
+seed: 1234
+epoch: 0
+epochs: 100
+ignore_index: None
+val_fn: validate
+deterministic: False
+sync_bn: False
+criterion_args:
+  NAME: CrossEntropy
+  label_smoothing: 0.2
+use_mask: False
+grad_norm_clip: 10
+layer_decay: 0
+step_per_update: 1
+start_epoch: 1
+sched_on_epoch: True
+wandb:
+  use_wandb: False
+  project: PointNeXt-S3DIS
+  tags: ['s3dis', 'train', 'pointnext_ctwc-l', 'ngpus1']
+  name: s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73
+use_amp: False
+use_voting: False
+val_freq: 1
+resume: False
+test: False
+finetune: False
+mode: train
+logname: None
+load_path: None
+print_freq: 50
+save_freq: -1
+root_dir: log/s3dis
+pretrained_path: None
+datatransforms:
+  train: ['ChromaticAutoContrast', 'PointsToTensor', 'PointCloudScaling', 'PointCloudXYZAlign', 'PointCloudRotation', 'PointCloudJitter', 'ChromaticDropGPU', 'ChromaticNormalize']
+  val: ['PointsToTensor', 'PointCloudXYZAlign', 'ChromaticNormalize']
+  vote: ['ChromaticDropGPU']
+  kwargs:
+    color_drop: 0.2
+    gravity_dim: 2
+    scale: [0.9, 1.1]
+    angle: [0, 0, 1]
+    jitter_sigma: 0.005
+    jitter_clip: 0.02
+feature_keys: x,heights
+dataset:
+  common:
+    NAME: S3DIS
+    data_root: data/S3DIS/s3disfull
+    test_area: 5
+    voxel_size: 0.04
+  train:
+    split: train
+    voxel_max: 24000
+    loop: 30
+    presample: False
+  val:
+    split: val
+    voxel_max: None
+    presample: True
+  test:
+    split: test
+    voxel_max: None
+    presample: False
+num_classes: 13
+batch_size: 8
+val_batch_size: 1
+dataloader:
+  num_workers: 6
+cls_weighed_loss: False
+optimizer:
+  NAME: adamw
+  weight_decay: 0.0001
+sched: cosine
+warmup_epochs: 2
+min_lr: 1e-05
+lr: 0.02
+log_dir: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73
+need_closs: True
+model:
+  NAME: CtwcSeg
+  encoder_args:
+    NAME: PointNext_CTWC_Encoder
+    blocks: [1, 3, 5, 3, 3]
+    strides: [1, 4, 4, 4, 4]
+    sa_layers: 1
+    sa_use_res: False
+    width: 32
+    in_channels: 4
+    expansion: 4
+    radius: 0.1
+    nsample: 32
+    aggr_args:
+      feature_type: dp_fj
+      reduction: max
+    group_args:
+      NAME: ballquery
+      normalize_dp: True
+    conv_args:
+      order: conv-norm-act
+    act_args:
+      act: relu
+    norm_args:
+      norm: bn
+  decoder_args:
+    NAME: PointNext_CTWC_Decoder
+  cls_args:
+    NAME: SegHead
+    num_classes: 13
+    in_channels: None
+    norm_args:
+      norm: bn
+rank: 0
+distributed: False
+mp: False
+task_name: s3dis
+cfg_basename: pointnext_ctwc-l
+opts: 
+is_training: True
+run_name: s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73
+run_dir: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73
+exp_dir: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73
+ckpt_dir: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint
+log_path: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73.log
+cfg_path: log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/cfg.yaml
+[04/18 16:14:12] S3DIS INFO: radius: [[0.1], [0.1, 0.2, 0.2], [0.2, 0.4, 0.4, 0.4, 0.4], [0.4, 0.8, 0.8], [0.8, 1.6, 1.6]],
+ nsample: [[32], [32, 32, 32], [32, 32, 32, 32, 32], [32, 32, 32], [32, 32, 32]]
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.1
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: True
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.2
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: True
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.4
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: True
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 0.8
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: False
+[04/18 16:14:12] S3DIS INFO: NAME: ballquery
+normalize_dp: True
+radius: 1.6
+nsample: 32
+return_idx: True
+[04/18 16:14:12] S3DIS INFO: CtwcSeg(
+  (encoder): PointNext_CTWC_Encoder(
+    (seq): FeatureRecorder()
+    (encoder): Sequential(
+      (0): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(4, 32, kernel_size=(1,), stride=(1,))
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(35, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.025)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(67, 64, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(64, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.025)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+          (act): ReLU(inplace=True)
+          (dropout): Dropout(p=0.2, inplace=False)
+          (drop_path): DropPath(drop_prob=0.200)
+        )
+      )
+      (2): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(67, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (3): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (4): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(131, 128, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(128, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(512, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.050)
+          (seq): FeatureRecorder()
+        )
+        (5): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+          (act): ReLU(inplace=True)
+          (dropout): Dropout(p=0.2, inplace=False)
+          (drop_path): DropPath(drop_prob=0.025)
+        )
+      )
+      (3): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(131, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(1024, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(259, 256, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(256, 1024, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(1024, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(1024, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+          (act): ReLU(inplace=True)
+          (dropout): Dropout(p=0.2, inplace=False)
+          (drop_path): DropPath(drop_prob=0.050)
+        )
+      )
+      (4): Sequential(
+        (0): SetAbstraction(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv2d(259, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+              (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+          (grouper): QueryAndGroup()
+        )
+        (1): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(515, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(2048, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (2): InvResMLP(
+          (convs): LocalAggregation(
+            (convs): Sequential(
+              (0): Sequential(
+                (0): Conv2d(515, 512, kernel_size=(1, 1), stride=(1, 1), bias=False)
+                (1): BatchNorm2d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+                (2): ReLU(inplace=True)
+              )
+            )
+            (grouper): QueryAndGroup()
+          )
+          (pwconv): Sequential(
+            (0): Sequential(
+              (0): Conv1d(512, 2048, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(2048, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(2048, 512, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+            )
+          )
+          (act): ReLU(inplace=True)
+          (drop_path): DropPath(drop_prob=0.075)
+          (seq): FeatureRecorder()
+        )
+        (3): CTWC_Block(
+          (grouper): QueryAndGroup()
+          (seq): FeatureRecorder()
+          (pwconv): Sequential(
+            (0): Conv1d(512, 512, kernel_size=(1,), stride=(1,))
+            (1): ReLU(inplace=True)
+            (2): BatchNorm1d(512, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+          )
+          (act): ReLU(inplace=True)
+          (dropout): Dropout(p=0.2, inplace=False)
+          (drop_path): DropPath(drop_prob=0.075)
+        )
+      )
+    )
+  )
+  (decoder): PointNext_CTWC_Decoder(
+    (decoder): Sequential(
+      (0): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(96, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (1): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(192, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(64, 64, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(64, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (2): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(384, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(128, 128, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(128, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+      (3): Sequential(
+        (0): FeaturePropogation(
+          (convs): Sequential(
+            (0): Sequential(
+              (0): Conv1d(768, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+            (1): Sequential(
+              (0): Conv1d(256, 256, kernel_size=(1,), stride=(1,), bias=False)
+              (1): BatchNorm1d(256, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+              (2): ReLU(inplace=True)
+            )
+          )
+        )
+      )
+    )
+  )
+  (head): SegHead(
+    (head): Sequential(
+      (0): Sequential(
+        (0): Conv1d(32, 32, kernel_size=(1,), stride=(1,), bias=False)
+        (1): BatchNorm1d(32, eps=1e-05, momentum=0.1, affine=True, track_running_stats=True)
+        (2): ReLU(inplace=True)
+      )
+      (1): Dropout(p=0.5, inplace=False)
+      (2): Sequential(
+        (0): Conv1d(32, 13, kernel_size=(1,), stride=(1,))
+      )
+    )
+  )
+)
+[04/18 16:14:12] S3DIS INFO: Number of params: 7.4773 M
+[04/18 16:14:12] S3DIS INFO: Param groups = {
+  "decay": {
+    "weight_decay": 0.0001,
+    "params": [
+      "encoder.encoder.0.0.convs.0.0.weight",
+      "encoder.encoder.1.0.convs.0.0.weight",
+      "encoder.encoder.1.1.convs.convs.0.0.weight",
+      "encoder.encoder.1.1.pwconv.0.0.weight",
+      "encoder.encoder.1.1.pwconv.1.0.weight",
+      "encoder.encoder.1.2.convs.convs.0.0.weight",
+      "encoder.encoder.1.2.pwconv.0.0.weight",
+      "encoder.encoder.1.2.pwconv.1.0.weight",
+      "encoder.encoder.1.3.gate",
+      "encoder.encoder.1.3.pwconv.0.weight",
+      "encoder.encoder.2.0.convs.0.0.weight",
+      "encoder.encoder.2.1.convs.convs.0.0.weight",
+      "encoder.encoder.2.1.pwconv.0.0.weight",
+      "encoder.encoder.2.1.pwconv.1.0.weight",
+      "encoder.encoder.2.2.convs.convs.0.0.weight",
+      "encoder.encoder.2.2.pwconv.0.0.weight",
+      "encoder.encoder.2.2.pwconv.1.0.weight",
+      "encoder.encoder.2.3.convs.convs.0.0.weight",
+      "encoder.encoder.2.3.pwconv.0.0.weight",
+      "encoder.encoder.2.3.pwconv.1.0.weight",
+      "encoder.encoder.2.4.convs.convs.0.0.weight",
+      "encoder.encoder.2.4.pwconv.0.0.weight",
+      "encoder.encoder.2.4.pwconv.1.0.weight",
+      "encoder.encoder.2.5.gate",
+      "encoder.encoder.2.5.pwconv.0.weight",
+      "encoder.encoder.3.0.convs.0.0.weight",
+      "encoder.encoder.3.1.convs.convs.0.0.weight",
+      "encoder.encoder.3.1.pwconv.0.0.weight",
+      "encoder.encoder.3.1.pwconv.1.0.weight",
+      "encoder.encoder.3.2.convs.convs.0.0.weight",
+      "encoder.encoder.3.2.pwconv.0.0.weight",
+      "encoder.encoder.3.2.pwconv.1.0.weight",
+      "encoder.encoder.3.3.gate",
+      "encoder.encoder.3.3.pwconv.0.weight",
+      "encoder.encoder.4.0.convs.0.0.weight",
+      "encoder.encoder.4.1.convs.convs.0.0.weight",
+      "encoder.encoder.4.1.pwconv.0.0.weight",
+      "encoder.encoder.4.1.pwconv.1.0.weight",
+      "encoder.encoder.4.2.convs.convs.0.0.weight",
+      "encoder.encoder.4.2.pwconv.0.0.weight",
+      "encoder.encoder.4.2.pwconv.1.0.weight",
+      "encoder.encoder.4.3.gate",
+      "encoder.encoder.4.3.pwconv.0.weight",
+      "decoder.decoder.0.0.convs.0.0.weight",
+      "decoder.decoder.0.0.convs.1.0.weight",
+      "decoder.decoder.1.0.convs.0.0.weight",
+      "decoder.decoder.1.0.convs.1.0.weight",
+      "decoder.decoder.2.0.convs.0.0.weight",
+      "decoder.decoder.2.0.convs.1.0.weight",
+      "decoder.decoder.3.0.convs.0.0.weight",
+      "decoder.decoder.3.0.convs.1.0.weight",
+      "head.head.0.0.weight",
+      "head.head.2.0.weight"
+    ],
+    "lr_scale": 1.0
+  },
+  "no_decay": {
+    "weight_decay": 0.0,
+    "params": [
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+      "encoder.encoder.1.0.convs.0.1.weight",
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+      "encoder.encoder.1.1.convs.convs.0.1.weight",
+      "encoder.encoder.1.1.convs.convs.0.1.bias",
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+      "encoder.encoder.1.3.a",
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+      "head.head.0.1.weight",
+      "head.head.0.1.bias",
+      "head.head.2.0.bias"
+    ],
+    "lr_scale": 1.0
+  }
+}
+[04/18 16:14:12] S3DIS INFO: 
+Totally 68 samples in val set
+[04/18 16:14:12] S3DIS INFO: length of validation dataset: 68
+[04/18 16:14:12] S3DIS INFO: number of classes of the dataset: 13
+[04/18 16:14:12] S3DIS INFO: Training from scratch
+[04/18 16:14:12] S3DIS INFO: 
+Totally 204 samples in train set
+[04/18 16:14:12] S3DIS INFO: length of training dataset: 6120
+[04/18 16:18:26] S3DIS INFO: Find a better ckpt @E1, val_miou 2.38 val_macc 7.28, val_oa 6.30
+mious: [ 2.59 10.1   5.43  0.03  0.52  4.07  1.15  4.42  0.59  0.14  0.29  0.31
+  1.29]
+[04/18 16:18:26] S3DIS INFO: Epoch 1 LR 0.000001 train_miou 2.66, val_miou 2.38, best val miou 2.38
+[04/18 16:18:26] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:22:32] S3DIS INFO: Find a better ckpt @E2, val_miou 34.16 val_macc 43.13, val_oa 74.65
+mious: [85.99 95.82 65.71  0.    0.   11.66  7.29 57.71 45.64  0.   42.59  0.
+ 31.64]
+[04/18 16:22:32] S3DIS INFO: Epoch 2 LR 0.010000 train_miou 31.80, val_miou 34.16, best val miou 34.16
+[04/18 16:22:32] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:26:43] S3DIS INFO: Find a better ckpt @E3, val_miou 38.02 val_macc 44.16, val_oa 77.59
+mious: [85.36 96.81 63.48  0.    0.    5.08  4.89 66.67 77.87  0.   58.37  0.
+ 35.77]
+[04/18 16:26:43] S3DIS INFO: Epoch 3 LR 0.019980 train_miou 42.75, val_miou 38.02, best val miou 38.02
+[04/18 16:26:43] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:30:54] S3DIS INFO: Find a better ckpt @E4, val_miou 39.52 val_macc 47.10, val_oa 80.18
+mious: [89.16 96.71 70.25  0.    0.   34.96  4.71 59.56 49.93  0.   64.87  0.
+ 43.67]
+[04/18 16:30:54] S3DIS INFO: Epoch 4 LR 0.019956 train_miou 47.18, val_miou 39.52, best val miou 39.52
+[04/18 16:30:54] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:35:00] S3DIS INFO: Find a better ckpt @E5, val_miou 46.39 val_macc 54.33, val_oa 82.04
+mious: [87.86 96.   74.22  0.    0.   11.48 44.88 72.36 75.43  0.   63.21 38.68
+ 38.92]
+[04/18 16:35:00] S3DIS INFO: Epoch 5 LR 0.019921 train_miou 50.51, val_miou 46.39, best val miou 46.39
+[04/18 16:35:01] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:39:09] S3DIS INFO: Find a better ckpt @E6, val_miou 51.49 val_macc 59.84, val_oa 83.13
+mious: [87.88 96.61 73.52  0.    0.   48.15 29.87 73.13 79.96 14.09 67.41 54.66
+ 44.12]
+[04/18 16:39:09] S3DIS INFO: Epoch 6 LR 0.019877 train_miou 53.54, val_miou 51.49, best val miou 51.49
+[04/18 16:39:09] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:43:22] S3DIS INFO: Find a better ckpt @E7, val_miou 53.26 val_macc 60.34, val_oa 83.58
+mious: [90.48 97.05 72.5   0.   21.43 39.48 13.5  73.49 79.55 29.74 69.75 58.26
+ 47.15]
+[04/18 16:43:22] S3DIS INFO: Epoch 7 LR 0.019823 train_miou 56.14, val_miou 53.26, best val miou 53.26
+[04/18 16:43:22] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:47:31] S3DIS INFO: Find a better ckpt @E8, val_miou 53.30 val_macc 60.24, val_oa 83.62
+mious: [88.61 96.07 73.75  0.   17.49 45.94 15.95 69.95 70.72 37.11 68.46 61.97
+ 46.88]
+[04/18 16:47:31] S3DIS INFO: Epoch 8 LR 0.019759 train_miou 60.21, val_miou 53.30, best val miou 53.30
+[04/18 16:47:31] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:51:41] S3DIS INFO: Find a better ckpt @E9, val_miou 54.86 val_macc 64.87, val_oa 84.36
+mious: [90.44 96.78 75.8   0.01  4.73 36.79 57.39 70.09 74.65 30.69 66.78 62.38
+ 46.68]
+[04/18 16:51:41] S3DIS INFO: Epoch 9 LR 0.019686 train_miou 61.58, val_miou 54.86, best val miou 54.86
+[04/18 16:51:41] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 16:55:48] S3DIS INFO: Find a better ckpt @E10, val_miou 58.20 val_macc 69.64, val_oa 84.95
+mious: [90.21 97.57 77.37  0.   20.6  45.07 54.2  75.83 80.88 53.24 66.76 44.13
+ 50.71]
+[04/18 16:55:48] S3DIS INFO: Epoch 10 LR 0.019603 train_miou 64.42, val_miou 58.20, best val miou 58.20
+[04/18 16:55:48] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:00:02] S3DIS INFO: Find a better ckpt @E11, val_miou 58.72 val_macc 67.45, val_oa 85.25
+mious: [92.48 96.68 76.82  0.   25.65 49.75 47.51 71.02 75.44 51.4  65.08 62.16
+ 49.32]
+[04/18 17:00:02] S3DIS INFO: Epoch 11 LR 0.019511 train_miou 65.67, val_miou 58.72, best val miou 58.72
+[04/18 17:00:02] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:04:15] S3DIS INFO: Epoch 12 LR 0.019409 train_miou 66.87, val_miou 58.26, best val miou 58.72
+[04/18 17:08:22] S3DIS INFO: Find a better ckpt @E13, val_miou 58.79 val_macc 67.60, val_oa 84.57
+mious: [89.86 96.73 76.02  0.   20.51 52.74 50.15 67.61 85.26 51.86 63.8  59.87
+ 49.85]
+[04/18 17:08:22] S3DIS INFO: Epoch 13 LR 0.019298 train_miou 67.71, val_miou 58.79, best val miou 58.79
+[04/18 17:08:23] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:12:37] S3DIS INFO: Find a better ckpt @E14, val_miou 58.94 val_macc 66.62, val_oa 85.65
+mious: [91.42 97.23 78.52  0.   25.45 37.76 50.5  76.65 81.51 49.99 68.6  60.06
+ 48.5 ]
+[04/18 17:12:37] S3DIS INFO: Epoch 14 LR 0.019178 train_miou 69.26, val_miou 58.94, best val miou 58.94
+[04/18 17:12:37] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:16:44] S3DIS INFO: Find a better ckpt @E15, val_miou 62.05 val_macc 70.10, val_oa 86.01
+mious: [90.75 97.22 77.33  0.   26.75 50.85 55.16 77.99 84.53 61.98 67.68 67.36
+ 49.03]
+[04/18 17:16:44] S3DIS INFO: Epoch 15 LR 0.019049 train_miou 70.11, val_miou 62.05, best val miou 62.05
+[04/18 17:16:44] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:20:42] S3DIS INFO: Find a better ckpt @E16, val_miou 62.80 val_macc 70.46, val_oa 86.78
+mious: [92.04 97.11 77.99  0.   24.58 51.88 54.47 78.64 84.92 61.76 71.96 67.32
+ 53.66]
+[04/18 17:20:42] S3DIS INFO: Epoch 16 LR 0.018911 train_miou 70.87, val_miou 62.80, best val miou 62.80
+[04/18 17:20:43] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:24:41] S3DIS INFO: Epoch 17 LR 0.018764 train_miou 71.97, val_miou 55.43, best val miou 62.80
+[04/18 17:28:37] S3DIS INFO: Epoch 18 LR 0.018608 train_miou 73.03, val_miou 58.92, best val miou 62.80
+[04/18 17:32:32] S3DIS INFO: Epoch 19 LR 0.018444 train_miou 73.40, val_miou 60.23, best val miou 62.80
+[04/18 17:36:30] S3DIS INFO: Epoch 20 LR 0.018272 train_miou 74.32, val_miou 62.00, best val miou 62.80
+[04/18 17:40:33] S3DIS INFO: Find a better ckpt @E21, val_miou 63.78 val_macc 71.89, val_oa 87.11
+mious: [91.78 97.2  79.15  0.   30.26 53.07 64.48 77.33 85.74 62.6  70.22 64.22
+ 53.04]
+[04/18 17:40:33] S3DIS INFO: Epoch 21 LR 0.018091 train_miou 74.70, val_miou 63.78, best val miou 63.78
+[04/18 17:40:33] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:44:31] S3DIS INFO: Find a better ckpt @E22, val_miou 64.72 val_macc 73.34, val_oa 87.48
+mious: [92.16 97.56 79.19  0.   34.   49.57 59.81 80.   87.12 67.64 70.63 68.59
+ 55.14]
+[04/18 17:44:31] S3DIS INFO: Epoch 22 LR 0.017903 train_miou 75.23, val_miou 64.72, best val miou 64.72
+[04/18 17:44:31] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 17:48:28] S3DIS INFO: Epoch 23 LR 0.017706 train_miou 76.21, val_miou 62.56, best val miou 64.72
+[04/18 17:52:25] S3DIS INFO: Epoch 24 LR 0.017502 train_miou 76.61, val_miou 61.64, best val miou 64.72
+[04/18 17:56:22] S3DIS INFO: Epoch 25 LR 0.017291 train_miou 77.32, val_miou 62.85, best val miou 64.72
+[04/18 18:00:33] S3DIS INFO: Epoch 26 LR 0.017073 train_miou 77.23, val_miou 64.09, best val miou 64.72
+[04/18 18:04:32] S3DIS INFO: Find a better ckpt @E27, val_miou 65.31 val_macc 72.43, val_oa 87.07
+mious: [90.58 97.73 77.25  0.   29.87 53.48 63.32 78.83 84.72 73.1  72.27 74.06
+ 53.81]
+[04/18 18:04:32] S3DIS INFO: Epoch 27 LR 0.016847 train_miou 78.02, val_miou 65.31, best val miou 65.31
+[04/18 18:04:32] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 18:08:29] S3DIS INFO: Epoch 28 LR 0.016615 train_miou 78.54, val_miou 63.92, best val miou 65.31
+[04/18 18:12:26] S3DIS INFO: Epoch 29 LR 0.016376 train_miou 78.56, val_miou 63.93, best val miou 65.31
+[04/18 18:16:24] S3DIS INFO: Epoch 30 LR 0.016131 train_miou 79.25, val_miou 64.89, best val miou 65.31
+[04/18 18:20:23] S3DIS INFO: Find a better ckpt @E31, val_miou 65.33 val_macc 72.49, val_oa 87.57
+mious: [92.36 97.72 79.09  0.   28.8  51.49 65.16 78.82 89.29 69.29 70.17 70.6
+ 56.52]
+[04/18 18:20:23] S3DIS INFO: Epoch 31 LR 0.015880 train_miou 79.44, val_miou 65.33, best val miou 65.33
+[04/18 18:20:23] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 18:24:18] S3DIS INFO: Find a better ckpt @E32, val_miou 66.32 val_macc 73.65, val_oa 87.43
+mious: [91.92 97.63 78.86  0.   35.08 54.83 59.36 79.6  87.25 75.29 74.64 72.64
+ 55.12]
+[04/18 18:24:18] S3DIS INFO: Epoch 32 LR 0.015623 train_miou 79.93, val_miou 66.32, best val miou 66.32
+[04/18 18:24:19] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 18:28:17] S3DIS INFO: Epoch 33 LR 0.015361 train_miou 79.98, val_miou 65.19, best val miou 66.32
+[04/18 18:32:24] S3DIS INFO: Epoch 34 LR 0.015093 train_miou 80.49, val_miou 65.73, best val miou 66.32
+[04/18 18:36:28] S3DIS INFO: Epoch 35 LR 0.014820 train_miou 80.86, val_miou 64.56, best val miou 66.32
+[04/18 18:40:42] S3DIS INFO: Find a better ckpt @E36, val_miou 66.89 val_macc 75.34, val_oa 88.83
+mious: [93.78 97.61 80.25  0.   39.11 55.67 69.62 79.64 86.49 61.58 74.26 72.77
+ 58.76]
+[04/18 18:40:42] S3DIS INFO: Epoch 36 LR 0.014543 train_miou 80.92, val_miou 66.89, best val miou 66.89
+[04/18 18:40:42] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 18:44:53] S3DIS INFO: Epoch 37 LR 0.014261 train_miou 81.45, val_miou 66.84, best val miou 66.89
+[04/18 18:49:02] S3DIS INFO: Epoch 38 LR 0.013974 train_miou 81.78, val_miou 65.71, best val miou 66.89
+[04/18 18:53:10] S3DIS INFO: Find a better ckpt @E39, val_miou 67.01 val_macc 73.91, val_oa 87.74
+mious: [91.08 97.71 80.52  0.   42.32 52.88 71.15 78.77 88.37 72.48 71.56 70.7
+ 53.64]
+[04/18 18:53:10] S3DIS INFO: Epoch 39 LR 0.013684 train_miou 81.49, val_miou 67.01, best val miou 67.01
+[04/18 18:53:11] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 18:57:20] S3DIS INFO: Epoch 40 LR 0.013391 train_miou 81.77, val_miou 66.61, best val miou 67.01
+[04/18 19:01:32] S3DIS INFO: Epoch 41 LR 0.013094 train_miou 82.41, val_miou 65.06, best val miou 67.01
+[04/18 19:05:40] S3DIS INFO: Find a better ckpt @E42, val_miou 67.82 val_macc 75.14, val_oa 88.96
+mious: [93.33 97.72 81.44  0.   38.28 56.56 68.31 77.77 88.57 73.06 75.55 74.41
+ 56.71]
+[04/18 19:05:40] S3DIS INFO: Epoch 42 LR 0.012794 train_miou 82.63, val_miou 67.82, best val miou 67.82
+[04/18 19:05:40] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 19:09:38] S3DIS INFO: Epoch 43 LR 0.012491 train_miou 82.76, val_miou 66.22, best val miou 67.82
+[04/18 19:13:32] S3DIS INFO: Epoch 44 LR 0.012185 train_miou 82.96, val_miou 66.76, best val miou 67.82
+[04/18 19:17:28] S3DIS INFO: Epoch 45 LR 0.011878 train_miou 82.78, val_miou 67.04, best val miou 67.82
+[04/18 19:21:24] S3DIS INFO: Find a better ckpt @E46, val_miou 68.21 val_macc 75.51, val_oa 88.73
+mious: [92.35 97.74 81.44  0.   41.1  55.35 67.62 81.   89.05 78.02 74.92 70.82
+ 57.38]
+[04/18 19:21:24] S3DIS INFO: Epoch 46 LR 0.011569 train_miou 83.32, val_miou 68.21, best val miou 68.21
+[04/18 19:21:24] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 19:25:18] S3DIS INFO: Epoch 47 LR 0.011258 train_miou 83.50, val_miou 66.39, best val miou 68.21
+[04/18 19:29:15] S3DIS INFO: Epoch 48 LR 0.010946 train_miou 83.54, val_miou 67.83, best val miou 68.21
+[04/18 19:33:09] S3DIS INFO: Epoch 49 LR 0.010633 train_miou 83.62, val_miou 67.78, best val miou 68.21
+[04/18 19:37:04] S3DIS INFO: Epoch 50 LR 0.010319 train_miou 83.87, val_miou 66.84, best val miou 68.21
+[04/18 19:41:03] S3DIS INFO: Epoch 51 LR 0.010005 train_miou 84.08, val_miou 66.92, best val miou 68.21
+[04/18 19:44:57] S3DIS INFO: Epoch 52 LR 0.009691 train_miou 84.38, val_miou 67.56, best val miou 68.21
+[04/18 19:48:51] S3DIS INFO: Epoch 53 LR 0.009377 train_miou 83.99, val_miou 67.73, best val miou 68.21
+[04/18 19:52:50] S3DIS INFO: Epoch 54 LR 0.009064 train_miou 84.21, val_miou 67.12, best val miou 68.21
+[04/18 19:56:45] S3DIS INFO: Epoch 55 LR 0.008752 train_miou 84.59, val_miou 65.94, best val miou 68.21
+[04/18 20:00:38] S3DIS INFO: Epoch 56 LR 0.008441 train_miou 84.82, val_miou 67.99, best val miou 68.21
+[04/18 20:04:30] S3DIS INFO: Epoch 57 LR 0.008132 train_miou 84.67, val_miou 67.68, best val miou 68.21
+[04/18 20:08:31] S3DIS INFO: Epoch 58 LR 0.007825 train_miou 84.89, val_miou 67.08, best val miou 68.21
+[04/18 20:12:26] S3DIS INFO: Find a better ckpt @E59, val_miou 68.30 val_macc 74.88, val_oa 89.05
+mious: [93.53 97.78 81.3   0.   31.14 56.04 71.76 79.26 89.09 76.97 75.81 77.12
+ 58.1 ]
+[04/18 20:12:26] S3DIS INFO: Epoch 59 LR 0.007519 train_miou 85.03, val_miou 68.30, best val miou 68.30
+[04/18 20:12:27] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 20:16:22] S3DIS INFO: Find a better ckpt @E60, val_miou 69.17 val_macc 75.70, val_oa 89.22
+mious: [93.58 97.83 81.7   0.   36.63 56.59 72.35 80.04 89.3  79.15 75.85 77.4
+ 58.84]
+[04/18 20:16:22] S3DIS INFO: Epoch 60 LR 0.007216 train_miou 85.14, val_miou 69.17, best val miou 69.17
+[04/18 20:16:23] S3DIS INFO: Found the best model and saved in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 20:20:18] S3DIS INFO: Epoch 61 LR 0.006916 train_miou 85.25, val_miou 67.47, best val miou 69.17
+[04/18 20:24:16] S3DIS INFO: Epoch 62 LR 0.006619 train_miou 85.24, val_miou 68.20, best val miou 69.17
+[04/18 20:28:10] S3DIS INFO: Epoch 63 LR 0.006326 train_miou 85.47, val_miou 68.79, best val miou 69.17
+[04/18 20:32:08] S3DIS INFO: Epoch 64 LR 0.006036 train_miou 85.61, val_miou 67.89, best val miou 69.17
+[04/18 20:36:09] S3DIS INFO: Epoch 65 LR 0.005749 train_miou 85.64, val_miou 67.51, best val miou 69.17
+[04/18 20:40:07] S3DIS INFO: Epoch 66 LR 0.005467 train_miou 85.88, val_miou 67.93, best val miou 69.17
+[04/18 20:44:05] S3DIS INFO: Epoch 67 LR 0.005190 train_miou 85.79, val_miou 68.34, best val miou 69.17
+[04/18 20:48:01] S3DIS INFO: Epoch 68 LR 0.004917 train_miou 85.95, val_miou 67.36, best val miou 69.17
+[04/18 20:52:00] S3DIS INFO: Epoch 69 LR 0.004649 train_miou 86.07, val_miou 68.29, best val miou 69.17
+[04/18 20:55:54] S3DIS INFO: Epoch 70 LR 0.004387 train_miou 86.17, val_miou 67.93, best val miou 69.17
+[04/18 20:59:50] S3DIS INFO: Epoch 71 LR 0.004130 train_miou 86.10, val_miou 68.10, best val miou 69.17
+[04/18 21:03:39] S3DIS INFO: Epoch 72 LR 0.003879 train_miou 86.36, val_miou 68.13, best val miou 69.17
+[04/18 21:07:32] S3DIS INFO: Epoch 73 LR 0.003634 train_miou 86.32, val_miou 67.56, best val miou 69.17
+[04/18 21:11:32] S3DIS INFO: Epoch 74 LR 0.003395 train_miou 86.49, val_miou 67.63, best val miou 69.17
+[04/18 21:15:23] S3DIS INFO: Epoch 75 LR 0.003163 train_miou 86.36, val_miou 67.57, best val miou 69.17
+[04/18 21:19:21] S3DIS INFO: Epoch 76 LR 0.002937 train_miou 86.68, val_miou 68.30, best val miou 69.17
+[04/18 21:23:14] S3DIS INFO: Epoch 77 LR 0.002719 train_miou 86.64, val_miou 68.65, best val miou 69.17
+[04/18 21:27:10] S3DIS INFO: Epoch 78 LR 0.002508 train_miou 86.78, val_miou 68.39, best val miou 69.17
+[04/18 21:31:05] S3DIS INFO: Epoch 79 LR 0.002304 train_miou 86.70, val_miou 68.54, best val miou 69.17
+[04/18 21:34:59] S3DIS INFO: Epoch 80 LR 0.002107 train_miou 86.89, val_miou 67.88, best val miou 69.17
+[04/18 21:38:53] S3DIS INFO: Epoch 81 LR 0.001919 train_miou 86.87, val_miou 68.72, best val miou 69.17
+[04/18 21:42:49] S3DIS INFO: Epoch 82 LR 0.001738 train_miou 87.05, val_miou 68.54, best val miou 69.17
+[04/18 21:46:47] S3DIS INFO: Epoch 83 LR 0.001566 train_miou 87.10, val_miou 68.75, best val miou 69.17
+[04/18 21:50:40] S3DIS INFO: Epoch 84 LR 0.001402 train_miou 87.13, val_miou 68.31, best val miou 69.17
+[04/18 21:54:35] S3DIS INFO: Epoch 85 LR 0.001246 train_miou 87.03, val_miou 68.70, best val miou 69.17
+[04/18 21:58:34] S3DIS INFO: Epoch 86 LR 0.001099 train_miou 87.13, val_miou 69.11, best val miou 69.17
+[04/18 22:02:34] S3DIS INFO: Epoch 87 LR 0.000961 train_miou 87.18, val_miou 68.87, best val miou 69.17
+[04/18 22:06:28] S3DIS INFO: Epoch 88 LR 0.000832 train_miou 87.22, val_miou 68.36, best val miou 69.17
+[04/18 22:10:24] S3DIS INFO: Epoch 89 LR 0.000712 train_miou 87.14, val_miou 68.63, best val miou 69.17
+[04/18 22:14:22] S3DIS INFO: Epoch 90 LR 0.000601 train_miou 87.17, val_miou 68.60, best val miou 69.17
+[04/18 22:18:18] S3DIS INFO: Epoch 91 LR 0.000499 train_miou 87.38, val_miou 68.86, best val miou 69.17
+[04/18 22:22:16] S3DIS INFO: Epoch 92 LR 0.000407 train_miou 87.20, val_miou 68.53, best val miou 69.17
+[04/18 22:26:14] S3DIS INFO: Epoch 93 LR 0.000324 train_miou 87.20, val_miou 68.88, best val miou 69.17
+[04/18 22:30:09] S3DIS INFO: Epoch 94 LR 0.000251 train_miou 87.20, val_miou 68.62, best val miou 69.17
+[04/18 22:34:07] S3DIS INFO: Epoch 95 LR 0.000187 train_miou 87.27, val_miou 68.69, best val miou 69.17
+[04/18 22:38:02] S3DIS INFO: Epoch 96 LR 0.000133 train_miou 87.26, val_miou 68.82, best val miou 69.17
+[04/18 22:41:54] S3DIS INFO: Epoch 97 LR 0.000089 train_miou 87.29, val_miou 68.75, best val miou 69.17
+[04/18 22:45:51] S3DIS INFO: Epoch 98 LR 0.000054 train_miou 87.30, val_miou 68.76, best val miou 69.17
+[04/18 22:49:50] S3DIS INFO: Epoch 99 LR 0.000030 train_miou 87.36, val_miou 68.86, best val miou 69.17
+[04/18 22:54:02] S3DIS INFO: Epoch 100 LR 0.000015 train_miou 87.32, val_miou 68.60, best val miou 69.17
+[04/18 22:54:02] S3DIS INFO: Best ckpt @E60,  val_oa 89.22, val_macc 75.70, val_miou 69.17, 
+iou per cls is: [93.58 97.83 81.7   0.   36.63 56.59 72.35 80.04 89.3  79.15 75.85 77.4
+ 58.84]
+[04/18 22:54:02] S3DIS INFO: Successful Loading the ckpt from log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/checkpoint/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth
+[04/18 22:54:02] S3DIS INFO: ckpts @ 60 epoch( {'best_val': 69.17314910888672} )
+[04/18 22:54:02] S3DIS INFO: Test [0]/[68] cloud
+[04/18 22:54:13] S3DIS INFO: [0]/[68] cloud,  test_oa , test_macc, test_miou: 92.96 97.36 88.19, 
+iou per cls is: [ 97.82  99.2   82.76 100.   100.   100.    97.56   0.   100.   100.
+ 100.   100.    69.12]
+[04/18 22:54:13] S3DIS INFO: Test [1]/[68] cloud
+[04/18 22:54:20] S3DIS INFO: [1]/[68] cloud,  test_oa , test_macc, test_miou: 93.77 97.70 87.96, 
+iou per cls is: [ 96.15  99.22  85.82 100.   100.   100.    88.33   0.   100.   100.
+ 100.   100.    73.95]
+[04/18 22:54:20] S3DIS INFO: Test [2]/[68] cloud
+[04/18 22:54:36] S3DIS INFO: [2]/[68] cloud,  test_oa , test_macc, test_miou: 89.85 87.36 77.07, 
+iou per cls is: [ 96.21  99.01  77.63 100.     9.14  74.99  97.89  93.69  96.08 100.
+   0.    95.28  61.97]
+[04/18 22:54:36] S3DIS INFO: Test [3]/[68] cloud
+[04/18 22:56:11] S3DIS INFO: [3]/[68] cloud,  test_oa , test_macc, test_miou: 94.04 92.39 88.69, 
+iou per cls is: [ 96.26  97.73  88.36 100.    67.9  100.    83.51  93.45  92.85  99.77
+  84.49  75.49  73.21]
+[04/18 22:56:11] S3DIS INFO: Test [4]/[68] cloud
+[04/18 22:56:48] S3DIS INFO: [4]/[68] cloud,  test_oa , test_macc, test_miou: 94.10 92.53 66.42, 
+iou per cls is: [95.69 99.52 82.29  0.   75.33 83.13 94.33 86.49 95.69  0.    0.   80.68
+ 70.33]
+[04/18 22:56:48] S3DIS INFO: Test [5]/[68] cloud
+[04/18 23:00:10] S3DIS INFO: [5]/[68] cloud,  test_oa , test_macc, test_miou: 80.19 78.44 34.88, 
+iou per cls is: [86.9  98.86 50.01  0.   41.81  1.83 25.26  0.    0.   49.89 68.23  0.
+ 30.7 ]
+[04/18 23:00:10] S3DIS INFO: Test [6]/[68] cloud
+[04/18 23:00:35] S3DIS INFO: [6]/[68] cloud,  test_oa , test_macc, test_miou: 98.51 98.58 98.01, 
+iou per cls is: [ 98.36  99.38  97.28 100.   100.   100.    83.2  100.   100.   100.
+ 100.   100.    95.91]
+[04/18 23:00:35] S3DIS INFO: Test [7]/[68] cloud
+[04/18 23:00:48] S3DIS INFO: [7]/[68] cloud,  test_oa , test_macc, test_miou: 98.26 98.31 90.34, 
+iou per cls is: [ 96.42  99.04  97.08 100.   100.   100.    81.95 100.   100.   100.
+ 100.   100.     0.  ]
+[04/18 23:00:48] S3DIS INFO: Test [8]/[68] cloud
+[04/18 23:01:01] S3DIS INFO: [8]/[68] cloud,  test_oa , test_macc, test_miou: 98.17 97.47 96.61, 
+iou per cls is: [ 97.49  99.34  96.84 100.   100.   100.    76.47 100.   100.   100.
+ 100.   100.    85.76]
+[04/18 23:01:01] S3DIS INFO: Test [9]/[68] cloud
+[04/18 23:01:30] S3DIS INFO: [9]/[68] cloud,  test_oa , test_macc, test_miou: 90.07 90.63 68.21, 
+iou per cls is: [ 98.23  99.23  88.47 100.     0.     0.01  28.7  100.     0.   100.
+ 100.   100.    72.14]
+[04/18 23:01:30] S3DIS INFO: Test [10]/[68] cloud
+[04/18 23:01:39] S3DIS INFO: [10]/[68] cloud,  test_oa , test_macc, test_miou: 95.38 95.96 71.91, 
+iou per cls is: [ 98.51  98.88  93.   100.   100.   100.    56.02   0.   100.     0.
+   0.   100.    88.39]
+[04/18 23:01:39] S3DIS INFO: Test [11]/[68] cloud
+[04/18 23:02:11] S3DIS INFO: [11]/[68] cloud,  test_oa , test_macc, test_miou: 85.10 81.43 60.06, 
+iou per cls is: [ 98.32  99.12  69.19 100.     0.11   0.31  40.57   0.   100.   100.
+   0.   100.    73.16]
+[04/18 23:02:11] S3DIS INFO: Test [12]/[68] cloud
+[04/18 23:07:14] S3DIS INFO: [12]/[68] cloud,  test_oa , test_macc, test_miou: 90.74 94.81 55.26, 
+iou per cls is: [ 94.84  98.86  84.1    0.     0.   100.    51.08   0.     0.   100.
+ 100.     0.    89.47]
+[04/18 23:07:14] S3DIS INFO: Test [13]/[68] cloud
+[04/18 23:07:35] S3DIS INFO: [13]/[68] cloud,  test_oa , test_macc, test_miou: 97.43 96.86 88.56, 
+iou per cls is: [ 98.21  97.79  95.72 100.   100.   100.    70.35 100.   100.   100.
+   0.   100.    89.27]
+[04/18 23:07:35] S3DIS INFO: Test [14]/[68] cloud
+[04/18 23:07:49] S3DIS INFO: [14]/[68] cloud,  test_oa , test_macc, test_miou: 94.81 83.47 51.74, 
+iou per cls is: [ 97.65  99.46  95.71   0.   100.   100.    83.62   0.     0.    91.53
+   1.73   0.     2.9 ]
+[04/18 23:07:49] S3DIS INFO: Test [15]/[68] cloud
+[04/18 23:09:34] S3DIS INFO: [15]/[68] cloud,  test_oa , test_macc, test_miou: 96.52 90.69 80.06, 
+iou per cls is: [ 99.1   99.65  95.17 100.   100.   100.    59.2    0.   100.    68.17
+  64.66 100.    54.8 ]
+[04/18 23:09:34] S3DIS INFO: Test [16]/[68] cloud
+[04/18 23:09:47] S3DIS INFO: [16]/[68] cloud,  test_oa , test_macc, test_miou: 95.08 96.71 87.31, 
+iou per cls is: [ 97.59  99.15  90.65 100.   100.   100.    77.41 100.   100.   100.
+ 100.     0.    70.18]
+[04/18 23:09:47] S3DIS INFO: Test [17]/[68] cloud
+[04/18 23:10:10] S3DIS INFO: [17]/[68] cloud,  test_oa , test_macc, test_miou: 94.91 97.08 80.66, 
+iou per cls is: [ 98.6   99.31  90.72 100.   100.   100.    81.97 100.   100.   100.
+   0.     0.    78.  ]
+[04/18 23:10:10] S3DIS INFO: Test [18]/[68] cloud
+[04/18 23:10:15] S3DIS INFO: [18]/[68] cloud,  test_oa , test_macc, test_miou: 96.42 90.62 89.85, 
+iou per cls is: [ 96.75  99.42  93.07 100.   100.   100.    78.45 100.   100.   100.
+ 100.   100.     0.42]
+[04/18 23:10:15] S3DIS INFO: Test [19]/[68] cloud
+[04/18 23:10:41] S3DIS INFO: [19]/[68] cloud,  test_oa , test_macc, test_miou: 97.09 88.32 71.56, 
+iou per cls is: [ 95.16  98.74  95.74   0.    80.18   0.25  72.47 100.   100.   100.
+   0.   100.    87.72]
+[04/18 23:10:41] S3DIS INFO: Test [20]/[68] cloud
+[04/18 23:11:00] S3DIS INFO: [20]/[68] cloud,  test_oa , test_macc, test_miou: 95.77 94.93 70.49, 
+iou per cls is: [ 99.81  98.    94.12 100.   100.   100.     0.    84.04  93.63 100.
+   0.     0.    46.74]
+[04/18 23:11:00] S3DIS INFO: Test [21]/[68] cloud
+[04/18 23:11:11] S3DIS INFO: [21]/[68] cloud,  test_oa , test_macc, test_miou: 92.45 90.56 71.18, 
+iou per cls is: [97.88 98.52 70.61  0.   57.58 80.7  93.47 91.61 93.76  0.   94.99 83.58
+ 62.68]
+[04/18 23:11:11] S3DIS INFO: Test [22]/[68] cloud
+[04/18 23:11:21] S3DIS INFO: [22]/[68] cloud,  test_oa , test_macc, test_miou: 93.22 88.97 76.93, 
+iou per cls is: [ 98.44  98.65  79.3    0.    15.16  84.06  91.26  81.01  95.13 100.
+  93.81  94.33  68.94]
+[04/18 23:11:21] S3DIS INFO: Test [23]/[68] cloud
+[04/18 23:11:32] S3DIS INFO: [23]/[68] cloud,  test_oa , test_macc, test_miou: 96.55 94.45 82.03, 
+iou per cls is: [ 97.67  97.68  85.32   0.    56.54  82.73  96.53  81.5   89.8  100.
+  97.48  95.97  85.15]
+[04/18 23:11:32] S3DIS INFO: Test [24]/[68] cloud
+[04/18 23:11:44] S3DIS INFO: [24]/[68] cloud,  test_oa , test_macc, test_miou: 88.76 87.27 81.81, 
+iou per cls is: [ 97.62  96.46  74.87 100.    39.21  77.65  91.33  80.53  70.12 100.
+  86.09 100.    49.67]
+[04/18 23:11:44] S3DIS INFO: Test [25]/[68] cloud
+[04/18 23:12:00] S3DIS INFO: [25]/[68] cloud,  test_oa , test_macc, test_miou: 91.25 89.74 77.03, 
+iou per cls is: [ 98.36  98.06  69.64   0.    37.85  82.91  84.57  84.5   95.17 100.
+  93.81  91.34  65.11]
+[04/18 23:12:00] S3DIS INFO: Test [26]/[68] cloud
+[04/18 23:12:25] S3DIS INFO: [26]/[68] cloud,  test_oa , test_macc, test_miou: 85.69 84.11 69.89, 
+iou per cls is: [ 94.56  97.95  65.78   0.     3.31  52.    93.33  70.89  90.26 100.
+  80.55  94.21  65.76]
+[04/18 23:12:25] S3DIS INFO: Test [27]/[68] cloud
+[04/18 23:12:53] S3DIS INFO: [27]/[68] cloud,  test_oa , test_macc, test_miou: 90.40 90.38 77.73, 
+iou per cls is: [ 96.12  98.37  75.6    0.    45.49  80.91  88.    84.93  95.72 100.
+  88.39  92.78  64.18]
+[04/18 23:12:53] S3DIS INFO: Test [28]/[68] cloud
+[04/18 23:13:04] S3DIS INFO: [28]/[68] cloud,  test_oa , test_macc, test_miou: 92.17 87.81 75.10, 
+iou per cls is: [ 98.63  98.12  90.62   0.    77.78 100.    95.38  89.61  90.49 100.
+  14.8   73.54  47.39]
+[04/18 23:13:04] S3DIS INFO: Test [29]/[68] cloud
+[04/18 23:13:18] S3DIS INFO: [29]/[68] cloud,  test_oa , test_macc, test_miou: 87.32 89.97 69.74, 
+iou per cls is: [ 97.49  98.69  89.59   0.     0.   100.    44.09  65.68 100.   100.
+  60.94 100.    50.09]
+[04/18 23:13:18] S3DIS INFO: Test [30]/[68] cloud
+[04/18 23:13:43] S3DIS INFO: [30]/[68] cloud,  test_oa , test_macc, test_miou: 94.62 88.59 70.58, 
+iou per cls is: [ 99.28  98.71  88.45   0.    32.27   0.    91.01  97.25  92.56 100.
+  93.28  42.49  82.28]
+[04/18 23:13:43] S3DIS INFO: Test [31]/[68] cloud
+[04/18 23:14:27] S3DIS INFO: [31]/[68] cloud,  test_oa , test_macc, test_miou: 87.38 92.03 71.74, 
+iou per cls is: [ 94.14  99.16  75.2    0.     0.   100.    85.4   91.44  93.93 100.
+  55.63  86.82  50.88]
+[04/18 23:14:27] S3DIS INFO: Test [32]/[68] cloud
+[04/18 23:14:40] S3DIS INFO: [32]/[68] cloud,  test_oa , test_macc, test_miou: 92.96 88.75 84.85, 
+iou per cls is: [ 98.25  98.1   76.49 100.    18.26  74.87  97.69  71.84  95.54 100.
+  91.26  93.91  86.85]
+[04/18 23:14:40] S3DIS INFO: Test [33]/[68] cloud
+[04/18 23:14:45] S3DIS INFO: [33]/[68] cloud,  test_oa , test_macc, test_miou: 89.00 91.68 67.68, 
+iou per cls is: [ 98.16  97.31  83.58   0.    45.78 100.    78.67  94.56  93.14 100.
+  55.12   0.    33.51]
+[04/18 23:14:45] S3DIS INFO: Test [34]/[68] cloud
+[04/18 23:15:49] S3DIS INFO: [34]/[68] cloud,  test_oa , test_macc, test_miou: 92.10 91.86 78.60, 
+iou per cls is: [ 98.79  99.35  83.06   0.    80.   100.    83.94  92.81  90.31 100.
+  36.87  94.36  62.29]
+[04/18 23:15:49] S3DIS INFO: Test [35]/[68] cloud
+[04/18 23:16:00] S3DIS INFO: [35]/[68] cloud,  test_oa , test_macc, test_miou: 90.96 87.52 74.41, 
+iou per cls is: [ 96.6   98.12  76.11   0.     5.89  78.1   84.45  84.58  93.13 100.
+  90.22  94.15  65.93]
+[04/18 23:16:00] S3DIS INFO: Test [36]/[68] cloud
+[04/18 23:16:14] S3DIS INFO: [36]/[68] cloud,  test_oa , test_macc, test_miou: 91.09 89.21 75.12, 
+iou per cls is: [ 97.63  97.19  80.52   0.    35.11  74.88  78.85  85.96  89.89 100.
+  87.57  92.36  56.6 ]
+[04/18 23:16:14] S3DIS INFO: Test [37]/[68] cloud
+[04/18 23:16:55] S3DIS INFO: [37]/[68] cloud,  test_oa , test_macc, test_miou: 82.71 84.29 68.13, 
+iou per cls is: [96.92 95.04 54.55  0.   41.49 73.9  85.97 80.02 83.38 80.62 56.86 88.68
+ 48.3 ]
+[04/18 23:16:55] S3DIS INFO: Test [38]/[68] cloud
+[04/18 23:17:02] S3DIS INFO: [38]/[68] cloud,  test_oa , test_macc, test_miou: 90.19 92.14 71.88, 
+iou per cls is: [ 96.61  96.22  84.19   0.     0.    84.54  89.76  66.36  98.39 100.
+  85.38  78.69  54.27]
+[04/18 23:17:02] S3DIS INFO: Test [39]/[68] cloud
+[04/18 23:17:12] S3DIS INFO: [39]/[68] cloud,  test_oa , test_macc, test_miou: 87.74 88.53 82.74, 
+iou per cls is: [ 95.56  97.3   85.87 100.    68.72  80.3   88.43  79.45  95.53 100.
+  66.34  68.53  49.59]
+[04/18 23:17:12] S3DIS INFO: Test [40]/[68] cloud
+[04/18 23:17:23] S3DIS INFO: [40]/[68] cloud,  test_oa , test_macc, test_miou: 91.13 89.63 69.11, 
+iou per cls is: [96.03 99.18 81.15  0.   32.61 84.37 83.13 90.08 95.6   0.   84.77 92.07
+ 59.4 ]
+[04/18 23:17:23] S3DIS INFO: Test [41]/[68] cloud
+[04/18 23:17:34] S3DIS INFO: [41]/[68] cloud,  test_oa , test_macc, test_miou: 94.44 92.42 73.42, 
+iou per cls is: [97.08 99.11 88.83  0.   68.52 92.07 86.37 88.69 90.7   0.   90.34 92.42
+ 60.37]
+[04/18 23:17:34] S3DIS INFO: Test [42]/[68] cloud
+[04/18 23:18:19] S3DIS INFO: [42]/[68] cloud,  test_oa , test_macc, test_miou: 82.40 85.37 63.55, 
+iou per cls is: [96.77 98.14 57.58  0.   53.9  77.06 94.81 86.07 93.06  0.   31.61 89.59
+ 47.62]
+[04/18 23:18:19] S3DIS INFO: Test [43]/[68] cloud
+[04/18 23:18:28] S3DIS INFO: [43]/[68] cloud,  test_oa , test_macc, test_miou: 93.59 94.18 75.04, 
+iou per cls is: [ 98.1   98.58  75.45   0.     0.    80.92  96.3   82.06  95.14 100.
+  95.61  90.58  62.73]
+[04/18 23:18:28] S3DIS INFO: Test [44]/[68] cloud
+[04/18 23:18:33] S3DIS INFO: [44]/[68] cloud,  test_oa , test_macc, test_miou: 95.44 93.76 82.47, 
+iou per cls is: [ 94.64  97.22  94.36   0.   100.   100.    90.82  75.61  60.92 100.
+  95.    91.27  72.21]
+[04/18 23:18:33] S3DIS INFO: Test [45]/[68] cloud
+[04/18 23:18:47] S3DIS INFO: [45]/[68] cloud,  test_oa , test_macc, test_miou: 88.08 88.95 75.28, 
+iou per cls is: [ 97.51  99.52  60.66   0.    21.79  82.78  81.26  83.72  91.87 100.
+  88.14 100.    71.4 ]
+[04/18 23:18:47] S3DIS INFO: Test [46]/[68] cloud
+[04/18 23:18:57] S3DIS INFO: [46]/[68] cloud,  test_oa , test_macc, test_miou: 90.61 88.87 76.07, 
+iou per cls is: [ 95.95  99.54  77.71   0.    15.16  90.46  74.07  89.28  89.13 100.
+  81.41 100.    76.25]
+[04/18 23:18:57] S3DIS INFO: Test [47]/[68] cloud
+[04/18 23:19:13] S3DIS INFO: [47]/[68] cloud,  test_oa , test_macc, test_miou: 93.51 90.38 86.61, 
+iou per cls is: [ 96.52  99.69  84.36 100.    26.55  89.29  85.62  90.89  96.29 100.
+  88.82  95.48  72.47]
+[04/18 23:19:13] S3DIS INFO: Test [48]/[68] cloud
+[04/18 23:19:29] S3DIS INFO: [48]/[68] cloud,  test_oa , test_macc, test_miou: 85.92 87.31 73.11, 
+iou per cls is: [ 96.04  97.48  70.98   0.    32.66  85.15  75.31  77.78  97.7  100.
+  66.38  95.94  55.01]
+[04/18 23:19:29] S3DIS INFO: Test [49]/[68] cloud
+[04/18 23:19:44] S3DIS INFO: [49]/[68] cloud,  test_oa , test_macc, test_miou: 96.05 97.18 87.19, 
+iou per cls is: [ 98.56  95.88  93.63   0.   100.   100.    96.85  91.5   92.48 100.
+  89.69  94.87  79.95]
+[04/18 23:19:44] S3DIS INFO: Test [50]/[68] cloud
+[04/18 23:20:08] S3DIS INFO: [50]/[68] cloud,  test_oa , test_macc, test_miou: 92.38 92.78 86.55, 
+iou per cls is: [ 98.45  96.09  94.28 100.   100.   100.    82.49  74.28  95.71 100.
+  49.94  95.89  38.01]
+[04/18 23:20:08] S3DIS INFO: Test [51]/[68] cloud
+[04/18 23:22:01] S3DIS INFO: [51]/[68] cloud,  test_oa , test_macc, test_miou: 84.55 83.13 67.86, 
+iou per cls is: [ 78.57  98.58  81.78   0.     8.37 100.    63.03  69.87  84.57 100.
+  70.65  69.15  57.58]
+[04/18 23:22:01] S3DIS INFO: Test [52]/[68] cloud
+[04/18 23:24:18] S3DIS INFO: [52]/[68] cloud,  test_oa , test_macc, test_miou: 76.86 86.42 51.79, 
+iou per cls is: [80.78 97.52 61.9   0.   53.6   0.   60.07 60.29 74.58 73.85 66.44  0.
+ 44.26]
+[04/18 23:24:18] S3DIS INFO: Test [53]/[68] cloud
+[04/18 23:24:32] S3DIS INFO: [53]/[68] cloud,  test_oa , test_macc, test_miou: 90.02 83.73 78.66, 
+iou per cls is: [ 93.12  98.06  91.05   0.   100.   100.    79.73  86.35  91.71 100.
+  41.74  90.22  50.58]
+[04/18 23:24:32] S3DIS INFO: Test [54]/[68] cloud
+[04/18 23:24:43] S3DIS INFO: [54]/[68] cloud,  test_oa , test_macc, test_miou: 95.25 92.28 80.86, 
+iou per cls is: [ 97.68  97.4   84.04   0.    42.32  83.85  94.71  86.27  96.47 100.
+  95.75  92.23  80.52]
+[04/18 23:24:43] S3DIS INFO: Test [55]/[68] cloud
+[04/18 23:26:53] S3DIS INFO: [55]/[68] cloud,  test_oa , test_macc, test_miou: 90.75 85.85 63.85, 
+iou per cls is: [ 97.64  96.97  87.36 100.    80.58   0.    71.33  75.62  81.44   0.
+  79.55   1.87  57.64]
+[04/18 23:26:53] S3DIS INFO: Test [56]/[68] cloud
+[04/18 23:27:32] S3DIS INFO: [56]/[68] cloud,  test_oa , test_macc, test_miou: 93.39 92.87 86.90, 
+iou per cls is: [ 97.26  98.03  78.34 100.    49.9   85.07  94.39  90.45  87.05 100.
+  86.58  86.53  76.14]
+[04/18 23:27:32] S3DIS INFO: Test [57]/[68] cloud
+[04/18 23:27:47] S3DIS INFO: [57]/[68] cloud,  test_oa , test_macc, test_miou: 89.07 89.44 75.53, 
+iou per cls is: [ 97.71  97.58  68.28   0.    30.89  57.13  90.11  89.39  96.12 100.
+  87.73 100.    66.96]
+[04/18 23:27:47] S3DIS INFO: Test [58]/[68] cloud
+[04/18 23:27:56] S3DIS INFO: [58]/[68] cloud,  test_oa , test_macc, test_miou: 95.35 95.95 78.14, 
+iou per cls is: [ 97.39  98.58  89.62   0.     0.    72.14  97.21  85.01  98.82 100.
+  90.96 100.    86.05]
+[04/18 23:27:56] S3DIS INFO: Test [59]/[68] cloud
+[04/18 23:28:06] S3DIS INFO: [59]/[68] cloud,  test_oa , test_macc, test_miou: 93.34 92.98 73.27, 
+iou per cls is: [ 98.01  97.85  79.23   0.     0.    58.52  93.39  82.98  79.66 100.
+  94.63  93.82  74.48]
+[04/18 23:28:06] S3DIS INFO: Test [60]/[68] cloud
+[04/18 23:28:21] S3DIS INFO: [60]/[68] cloud,  test_oa , test_macc, test_miou: 93.02 86.95 83.12, 
+iou per cls is: [ 98.21  98.09  74.25 100.     1.75  78.5   94.07  85.4   98.41 100.
+  93.88  87.57  70.39]
+[04/18 23:28:21] S3DIS INFO: Test [61]/[68] cloud
+[04/18 23:28:36] S3DIS INFO: [61]/[68] cloud,  test_oa , test_macc, test_miou: 91.39 91.61 73.51, 
+iou per cls is: [ 98.2   96.2   76.08   0.    37.93  46.96  96.36  89.11  91.86 100.
+  97.    94.2   31.76]
+[04/18 23:28:36] S3DIS INFO: Test [62]/[68] cloud
+[04/18 23:28:48] S3DIS INFO: [62]/[68] cloud,  test_oa , test_macc, test_miou: 93.66 95.18 75.60, 
+iou per cls is: [ 96.6   96.18  86.31   0.     0.    76.18  92.19  77.92  96.02  88.8
+  95.56 100.    77.  ]
+[04/18 23:28:48] S3DIS INFO: Test [63]/[68] cloud
+[04/18 23:28:55] S3DIS INFO: [63]/[68] cloud,  test_oa , test_macc, test_miou: 75.52 93.48 54.08, 
+iou per cls is: [ 93.71  97.95  87.54   0.     0.   100.     0.     0.   100.   100.
+   0.   100.    23.84]
+[04/18 23:28:55] S3DIS INFO: Test [64]/[68] cloud
+[04/18 23:29:03] S3DIS INFO: [64]/[68] cloud,  test_oa , test_macc, test_miou: 79.35 79.94 50.10, 
+iou per cls is: [ 77.04  96.31  72.6    0.    15.38   0.    75.12 100.     0.     0.
+  80.45 100.    34.46]
+[04/18 23:29:03] S3DIS INFO: Test [65]/[68] cloud
+[04/18 23:29:16] S3DIS INFO: [65]/[68] cloud,  test_oa , test_macc, test_miou: 79.89 91.38 63.40, 
+iou per cls is: [ 73.47  97.26  72.17 100.     0.   100.    74.72   0.   100.     0.
+  53.44 100.    53.08]
+[04/18 23:29:16] S3DIS INFO: Test [66]/[68] cloud
+[04/18 23:29:17] S3DIS INFO: [66]/[68] cloud,  test_oa , test_macc, test_miou: 81.80 93.81 66.40, 
+iou per cls is: [ 68.78  99.45  72.05 100.   100.   100.    77.99 100.     0.   100.
+   0.     0.    44.95]
+[04/18 23:29:17] S3DIS INFO: Test [67]/[68] cloud
+[04/18 23:29:26] S3DIS INFO: [67]/[68] cloud,  test_oa , test_macc, test_miou: 82.55 84.18 66.42, 
+iou per cls is: [ 89.99  98.68  89.79 100.   100.   100.    39.81  61.9   52.95 100.
+   0.     0.    30.29]
+[04/18 23:29:26] S3DIS INFO: Best ckpt @E60,  test_oa 90.26, test_macc 76.20, test_miou 69.96, 
+iou per cls is: [94.78 98.47 83.35  0.   36.57 60.27 73.63 81.85 90.15 76.44 76.44 78.33
+ 59.2 ]
+[04/18 23:29:26] S3DIS INFO: save results in log/s3dis/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73/s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73.csv

s3dis-train-pointnext_ctwc-l-ngpus1-20260418-161412-ktkcmkQxMWkZ39yDhG9q73_ckpt_best.pth

@@ -0,0 +1,3 @@
+version https://git-lfs.github.com/spec/v1
+oid sha256:33b111f6036958062afd6dc5986069a1ea35c10c4e57c9300f66d4b7e2e9cf4d
+size 90222418