53 lines
1.4 KiB
Markdown
53 lines
1.4 KiB
Markdown
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# Installation
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## Download the code:
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```
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git clone https://github.com/voldemortX/pytorch-auto-drive.git
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cd pytorch-auto-drive
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```
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## Requirements
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- Linux (recommended) or Windows (not fully tested, could have problems)
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- Python >= 3.6
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- CUDA >= 9.2 (for CUDA version < 9.2, the code is tested only with PyTorch 1.3 & CUDA 9.0 & CuDNN 7.6.0)
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- PyTorch >= 1.6 (2.x are not tested)
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- TorchVision >= 0.7.0
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- [mmcv-full](https://github.com/open-mmlab/mmcv) >= 1.3.5 (according to PyTorch/CUDA version)
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- Other pip dependencies: `pip install -r requirements.txt`
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The default Conda env (step-by-step):
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```
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conda create -n pad python=3.6
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conda activate pad
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conda install pytorch==1.6.0 torchvision==0.7.0 cudatoolkit=10.2 -c pytorch
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pip install mmcv-full==1.3.5 -f https://download.openmmlab.com/mmcv/dist/cu102/torch1.6.0/index.html
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pip install -r requirements.txt
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```
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## Prepare the code:
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```
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chmod 777 *.sh tools/shells/*.sh
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mkdir output
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```
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## Improve training speed with [Pillow-SIMD](https://github.com/uploadcare/pillow-simd) (optional, advanced):
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```
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pip uninstall pillow
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CC="cc -mavx2" pip install -U --force-reinstall pillow-simd
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```
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Note that you need to use ToTensor transform as late as possible for this speedup.
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## Enable tensorboard (optional):
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```
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tensorboard --logdir=<path to tb_logs>
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```
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`<path to tb_logs>` is usually `./checkpoints/tb_logs` if you did not customized `save_dir` in config file.
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