code/scripts/h800_setup_seggen.sh

#!/usr/bin/env bash
# Build the seggen conda env on h800 (L20Y / CUDA 12.8). torch installed FIRST (cu128)
# so SMP/MONAI don't pull a mismatched torch. Run detached; log to /tmp/seggen_env.log.
set -e
export https_proxy=http://10.140.15.68:3128 http_proxy=http://10.140.15.68:3128
CONDA=/data/temp/miniconda3
PROXY=http://10.140.15.68:3128

echo "[1] create env (python 3.11) -- conda-forge only, avoids defaults-channel ToS block"
$CONDA/bin/conda create -y -n seggen -c conda-forge --override-channels python=3.11 pip

PIP="$CONDA/envs/seggen/bin/pip"
echo "[2] torch cu128 (host CUDA 12.8, >2.6)"
$PIP install --proxy "$PROXY" torch torchvision --index-url https://download.pytorch.org/whl/cu128

echo "[3] seg stack (torch already present -> no reinstall)"
$PIP install --proxy "$PROXY" \
  segmentation-models-pytorch albumentations==2.0.8 monai medpy \
  opencv-python-headless numpy pyyaml timm einops ml-collections tqdm \
  diffusers==0.21.4 datasets==2.14.5

echo "[4] verify"
$CONDA/envs/seggen/bin/python - <<'PY'
import torch, segmentation_models_pytorch, monai, albumentations, timm, cv2
print("torch", torch.__version__, "| cuda", torch.version.cuda, "| avail", torch.cuda.is_available(), "| ndev", torch.cuda.device_count())
print("smp ok, monai ok, albumentations ok, timm ok, cv2", cv2.__version__)
PY
echo "SEGGEN_ENV_DONE"