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Account for num_gpus rename in docs + test configs (#2332)

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* fix: num-gpus to num-devices

* fix: Update test_config1.yml

* fix: Update test_config2.yml
This commit is contained in:
Kate Yurkova 2023-08-12 14:09:44 +03:00 committed by GitHub
parent 4fe8e657d2
commit 5eb83e8acd
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3 changed files with 4 additions and 4 deletions
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4
docs/quickstart/first_nerf.md
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@ -123,7 +123,7 @@ ns-download-data nerfstudio --capture-name=aspen
```python
# 1 GPU (8192 rays per GPU per batch)
export CUDA_VISIBLE_DEVICES=0
ns-train nerfacto-big --vis viewer+wandb --machine.num-gpus 1 --pipeline.datamanager.train-num-rays-per-batch 4096 --data data/nerfstudio/aspen
ns-train nerfacto-big --vis viewer+wandb --machine.num-devices 1 --pipeline.datamanager.train-num-rays-per-batch 4096 --data data/nerfstudio/aspen
```
You would observe about ~70k rays / sec on NVIDIA V100.
@ -148,7 +148,7 @@ By having more GPUs in the training, you can allocate batch size to multiple GPU
```python
# 2 GPUs (4096 rays per GPU per batch, effectively 8192 rays per batch)
export CUDA_VISIBLE_DEVICES=0,1
ns-train nerfacto --vis viewer+wandb --machine.num-gpus 2 --pipeline.datamanager.train-num-rays-per-batch 4096 --data data/nerfstudio/aspen
ns-train nerfacto --vis viewer+wandb --machine.num-devices 2 --pipeline.datamanager.train-num-rays-per-batch 4096 --data data/nerfstudio/aspen
```
You would get improved throughput (~100k rays / sec on two NVIDIA V100).

2
tests/data/configs/test_config1.yml
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@ -37,7 +37,7 @@ logging: !!python/object:nerfstudio.configs.base_config.LoggingConfig
machine: !!python/object:nerfstudio.configs.base_config.MachineConfig
dist_url: auto
machine_rank: 0
num_gpus: 1
num_devices: 1
num_machines: 1
seed: 42
max_num_iterations: 30000

2
tests/data/configs/test_config2.yml
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@ -32,7 +32,7 @@ logging: !!python/object:nerfstudio.configs.base_config.LoggingConfig
machine: !!python/object:nerfstudio.configs.base_config.MachineConfig
dist_url: auto
machine_rank: 0
num_gpus: 1
num_devices: 1
num_machines: 1
seed: 42
max_num_iterations: 30000