Upload setup_cluster.sh with huggingface_hub

setup_cluster.sh

@@ -0,0 +1,48 @@
+#!/bin/bash
+# Cluster environment setup for GR00T N1.7 training
+
+# --- Redirect caches to scratch ---
+export HOME=/var/tmp/szang
+export HF_HOME=/var/tmp/szang
+export TORCH_HOME=/var/tmp/szang
+export TRANSFORMERS_CACHE=/var/tmp/szang
+export UV_CACHE_DIR=/var/tmp/szang/.cache/uv
+mkdir -p /var/tmp/szang/.triton/autotune
+mkdir -p /var/tmp/szang/.cache/torch/kernels
+mkdir -p $UV_CACHE_DIR
+
+# --- Load modules ---
+module load gcc/10.5.0 cuda/11.8.0
+
+# --- Library paths ---
+export LD_LIBRARY_PATH=/global/scratch/users/ghr/Projects/szang/envs/video_act/lib:$LD_LIBRARY_PATH
+
+# --- NCCL settings ---
+export NCCL_P2P_DISABLE=1
+export NCCL_IB_DISABLE=1
+export NCCL_DEBUG=INFO
+export NCCL_NVLS_ENABLE=1
+export NCCL_P2P_LEVEL=NVL
+export NCCL_TIMEOUT=1200
+
+# --- Training settings ---
+export OMP_NUM_THREADS=4
+export TOKENIZERS_PARALLELISM=false
+
+# --- Activate venv ---
+cd /global/scratch/users/ghr/Projects/szang/GR00TN1.7
+source .venv/bin/activate
+
+# --- Verify ---
+nvcc --version && echo "CUDA_HOME: $CUDA_HOME"
+python -c "
+import torch
+print('PyTorch version:', torch.__version__)
+print('CUDA available:', torch.cuda.is_available())
+print('CUDA version:', torch.version.cuda)
+print('cuDNN version:', torch.backends.cudnn.version())
+print('GPU count:', torch.cuda.device_count())
+for i in range(torch.cuda.device_count()):
+    print(f'  GPU {i}: {torch.cuda.get_device_name(i)} ({torch.cuda.get_device_properties(i).total_mem / 1024**3:.1f} GB)')
+"
+python -c "import flash_attn; print('Flash Attention version:', flash_attn.__version__)"