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-MLCommons Logo +MLCommons Logo

@@ -43,19 +43,23 @@ 3. We use pip to install the `algorithmic_efficiency`. *TL;DR to install the Jax version for GPU run:* + ```bash pip3 install -e '.[pytorch_cpu]' pip3 install -e '.[jax_gpu]' -f 'https://storage.googleapis.com/jax-releases/jax_cuda_releases.html' pip3 install -e '.[full]' ``` + *TL;DR to install the PyTorch version for GPU run:* + ```bash pip3 install -e '.[jax_cpu]' pip3 install -e '.[pytorch_gpu]' -f 'https://download.pytorch.org/whl/torch_stable.html' pip3 install -e '.[full]' ``` - #### Additional Details +#### Additional Details + ```bash pip3 install -e . ``` @@ -168,9 +172,11 @@ python3 submission_runner.py \ When using multiple GPUs on a single node it is recommended to use PyTorch's [distributed data parallel](https://pytorch.org/tutorials/intermediate/ddp_tutorial.html). To do so, simply replace `python3` by + ```bash torchrun --standalone --nnodes=1 --nproc_per_node=N_GPUS ``` + where `N_GPUS` is the number of available GPUs on the node. ## Rules