sjojok / vgos Goto Github PK
View Code? Open in Web Editor NEW[IJCAI 2023] Official code for the paper "VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs".
License: Other
[IJCAI 2023] Official code for the paper "VGOS: Voxel Grid Optimization for View Synthesis from Sparse Inputs".
License: Other
When I run the following command:
python run.py --config configs/llff/room.py --render_test_get_metric
I get the error below:
scene_rep_reconstruction (fine): iter 2000 / Loss: 0.004814889 / PSNR: 26.94 / Eps: 00:00:37
7%|██████████▋ | 1994/30000 [00:36<05:24, 86.27it/sTesting (756, 1008, 3) | 0/2 [00:00<?, ?it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.61it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 2/2 [00:01<00:00, 1.60it/sTesting (756, 1008, 3) | 0/6 [00:00<?, ?it/s]
100%|████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████████| 6/6 [00:19<00:00, 3.31s/it]
7%|██████████▋ | 1999/30000 [01:03<14:44, 31.64it/s]
Traceback (most recent call last):
File "run.py", line 1425, in
train(args, cfg, data_dict,writer)
File "run.py", line 1246, in train
scene_rep_reconstruction(
File "run.py", line 1152, in scene_rep_reconstruction
HW=HW[i_random_val],
IndexError: index 61 is out of bounds for axis 0 with size 41
wandb: Waiting for W&B process to finish... (failed 1).
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [84,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [85,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [86,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [87,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [88,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [89,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [90,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [91,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [92,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [93,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [94,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
../aten/src/ATen/native/cuda/IndexKernel.cu:92: operator(): block: [0,0,0], thread: [95,0,0] Assertion index >= -sizes[i] && index < sizes[i] && "index out of bounds"
failed.
Any clue of what is going wrong?
rgb_logit = self.rgbnet(rgb_feat)
return F.linear(input, self.weight, self.bias)
RuntimeError: CUDA error: CUBLAS_STATUS_EXECUTION_FAILED when calling cublasLtMatmul( ltHandle, computeDesc.descriptor(), &alpha_val, mat1_ptr, Adesc.descriptor(), mat2_ptr, Bdesc.descriptor(), &beta_val, result_ptr, Cdesc.descriptor(), result_ptr, Cdesc.descriptor(), &heuristicResult.algo, workspace.data_ptr(), workspaceSize, at::cuda::getCurrentCUDAStream())
It's a excellent work! I meet some problem in traing, could please help me solve it?
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