| ============================================ |
| Activated conda environment: da2 |
| CUDA_HOME: /home/ywan0794/miniconda3/envs/da2 |
| ============================================ |
| === GPU Info === |
| Tue May 12 18:06:35 2026 |
| +-----------------------------------------------------------------------------------------+ |
| | NVIDIA-SMI 550.163.01 Driver Version: 550.163.01 CUDA Version: 12.4 | |
| |-----------------------------------------+------------------------+----------------------+ |
| | GPU Name Persistence-M | Bus-Id Disp.A | Volatile Uncorr. ECC | |
| | Fan Temp Perf Pwr:Usage/Cap | Memory-Usage | GPU-Util Compute M. | |
| | | | MIG M. | |
| |=========================================+========================+======================| |
| | 0 NVIDIA H100 NVL Off | 00000000:E1:00.0 Off | 0 | |
| | N/A 36C P0 60W / 400W | 14MiB / 95830MiB | 0% Default | |
| | | | Disabled | |
| +-----------------------------------------+------------------------+----------------------+ |
| |
| +-----------------------------------------------------------------------------------------+ |
| | Processes: | |
| | GPU GI CI PID Type Process name GPU Memory | |
| | ID ID Usage | |
| |=========================================================================================| |
| | 0 N/A N/A 4274 G /usr/lib/xorg/Xorg 4MiB | |
| +-----------------------------------------------------------------------------------------+ |
| CUDA available: True |
| GPU count: 1 |
| GPU name: NVIDIA H100 NVL |
| ============================================ |
| Starting MoGe Subset Sanity Eval (DA2 public vitb) at Tue May 12 06:06:55 PM AEST 2026 |
| Config: /home/ywan0794/MoGe/configs/eval/subset_benchmarks.json |
| Output: eval_output/da2_public_vitb_subset_20260512_180655.json |
| ============================================ |
| xFormers not available |
| xFormers not available |
| Traceback (most recent call last): |
| File "/home/ywan0794/MoGe/moge/scripts/eval_baseline.py", line 165, in <module> |
| main() |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 1485, in __call__ |
| return self.main(*args, **kwargs) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 1406, in main |
| rv = self.invoke(ctx) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 1269, in invoke |
| return ctx.invoke(self.callback, **ctx.params) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 824, in invoke |
| return callback(*args, **kwargs) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/decorators.py", line 34, in new_func |
| return f(get_current_context(), *args, **kwargs) |
| File "/home/ywan0794/MoGe/moge/scripts/eval_baseline.py", line 42, in main |
| baseline : MGEBaselineInterface = baseline_cls.load.main(ctx.args, standalone_mode=False) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 1406, in main |
| rv = self.invoke(ctx) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 1269, in invoke |
| return ctx.invoke(self.callback, **ctx.params) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/click/core.py", line 824, in invoke |
| return callback(*args, **kwargs) |
| File "/home/ywan0794/MoGe/baselines/da_v2.py", line 50, in load |
| return Baseline(repo_path, backbone, num_tokens, device) |
| File "/home/ywan0794/MoGe/baselines/da_v2.py", line 36, in __init__ |
| model.load_state_dict(checkpoint) |
| File "/home/ywan0794/miniconda3/envs/da2/lib/python3.10/site-packages/torch/nn/modules/module.py", line 2629, in load_state_dict |
| raise RuntimeError( |
| RuntimeError: Error(s) in loading state_dict for DepthAnythingV2: |
| size mismatch for depth_head.projects.0.weight: copying a param with shape torch.Size([96, 768, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 768, 1, 1]). |
| size mismatch for depth_head.projects.0.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.projects.1.weight: copying a param with shape torch.Size([192, 768, 1, 1]) from checkpoint, the shape in current model is torch.Size([512, 768, 1, 1]). |
| size mismatch for depth_head.projects.1.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([512]). |
| size mismatch for depth_head.projects.2.weight: copying a param with shape torch.Size([384, 768, 1, 1]) from checkpoint, the shape in current model is torch.Size([1024, 768, 1, 1]). |
| size mismatch for depth_head.projects.2.bias: copying a param with shape torch.Size([384]) from checkpoint, the shape in current model is torch.Size([1024]). |
| size mismatch for depth_head.projects.3.weight: copying a param with shape torch.Size([768, 768, 1, 1]) from checkpoint, the shape in current model is torch.Size([1024, 768, 1, 1]). |
| size mismatch for depth_head.projects.3.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]). |
| size mismatch for depth_head.resize_layers.0.weight: copying a param with shape torch.Size([96, 96, 4, 4]) from checkpoint, the shape in current model is torch.Size([256, 256, 4, 4]). |
| size mismatch for depth_head.resize_layers.0.bias: copying a param with shape torch.Size([96]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.resize_layers.1.weight: copying a param with shape torch.Size([192, 192, 2, 2]) from checkpoint, the shape in current model is torch.Size([512, 512, 2, 2]). |
| size mismatch for depth_head.resize_layers.1.bias: copying a param with shape torch.Size([192]) from checkpoint, the shape in current model is torch.Size([512]). |
| size mismatch for depth_head.resize_layers.3.weight: copying a param with shape torch.Size([768, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([1024, 1024, 3, 3]). |
| size mismatch for depth_head.resize_layers.3.bias: copying a param with shape torch.Size([768]) from checkpoint, the shape in current model is torch.Size([1024]). |
| size mismatch for depth_head.scratch.layer1_rn.weight: copying a param with shape torch.Size([128, 96, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.layer2_rn.weight: copying a param with shape torch.Size([128, 192, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 512, 3, 3]). |
| size mismatch for depth_head.scratch.layer3_rn.weight: copying a param with shape torch.Size([128, 384, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 1024, 3, 3]). |
| size mismatch for depth_head.scratch.layer4_rn.weight: copying a param with shape torch.Size([128, 768, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 1024, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet1.out_conv.weight: copying a param with shape torch.Size([128, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]). |
| size mismatch for depth_head.scratch.refinenet1.out_conv.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit1.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit1.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit1.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit1.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit2.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit2.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit2.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet1.resConfUnit2.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet2.out_conv.weight: copying a param with shape torch.Size([128, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]). |
| size mismatch for depth_head.scratch.refinenet2.out_conv.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit1.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit1.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit1.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit1.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit2.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit2.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit2.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet2.resConfUnit2.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet3.out_conv.weight: copying a param with shape torch.Size([128, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]). |
| size mismatch for depth_head.scratch.refinenet3.out_conv.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit1.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit1.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit1.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit1.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit2.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit2.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit2.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet3.resConfUnit2.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet4.out_conv.weight: copying a param with shape torch.Size([128, 128, 1, 1]) from checkpoint, the shape in current model is torch.Size([256, 256, 1, 1]). |
| size mismatch for depth_head.scratch.refinenet4.out_conv.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit1.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit1.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit1.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit1.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit2.conv1.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit2.conv1.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit2.conv2.weight: copying a param with shape torch.Size([128, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([256, 256, 3, 3]). |
| size mismatch for depth_head.scratch.refinenet4.resConfUnit2.conv2.bias: copying a param with shape torch.Size([128]) from checkpoint, the shape in current model is torch.Size([256]). |
| size mismatch for depth_head.scratch.output_conv1.weight: copying a param with shape torch.Size([64, 128, 3, 3]) from checkpoint, the shape in current model is torch.Size([128, 256, 3, 3]). |
| size mismatch for depth_head.scratch.output_conv1.bias: copying a param with shape torch.Size([64]) from checkpoint, the shape in current model is torch.Size([128]). |
| size mismatch for depth_head.scratch.output_conv2.0.weight: copying a param with shape torch.Size([32, 64, 3, 3]) from checkpoint, the shape in current model is torch.Size([32, 128, 3, 3]). |
| ============================================ |
| Evaluation completed at Tue May 12 06:07:22 PM AEST 2026 |
| ============================================ |
|
|
