Comments (2)
log如下:
callbacks: {}
trainer:
benchmark: true
max_epochs: -1
gradient_clip_val: 1.0
val_check_interval: 1000
num_sanity_val_steps: 0
accumulate_grad_batches: 1
check_val_every_n_epoch: null
accelerator: gpu
devices: 1
Training: | | 0/? [00:00<?, ?it/s]
Training: 0%| | 0/1 [00:00<?, ?it/s]
Epoch 0: 0%| | 0/1 [00:00<?, ?it/s] not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
not all arguments converted during string formatting
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solved
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Related Issues (20)
- Training time? HOT 1
- RuntimeError: handle_0 INTERNAL ASSERT FAILED at "../c10/cuda/driver_api.cpp":15, please report a bug to PyTorch.` HOT 2
- How to Improve Texture Quality and is there a way to tweak the model generation part by providing the normal maps?
- Torch cache not releasing
- Command '['ninja', '-v']' returned non-zero exit status 1 HOT 1
- Loading diffusion model ... Error HOT 1
- IndexError: too many indices for tensor of dimension 2 HOT 1
- Using other multi view models? HOT 1
- Getting errors when running the demo.
- Improve texture quality HOT 2
- Train on nerf of stage 1 with custom dataset HOT 8
- Number of epochs before seeing a decrease in the loss HOT 5
- Cuda version error when duplicating space on Hugging Face
- could you provide the rendering scripts to evalutate ? HOT 10
- 8GB of models downloading every time I launch app.py
- can providing good quality of image will not impact quality HOT 2
- INTERNAL ASSERT FAILED after generating multiviews
- Training CUDA Out Of Memory error HOT 5
- How to get the quantitative results as reported in the paper HOT 1
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