# Environment setup Use separate Python 3.12.13 environments for Actor/Judge and Editor. ## One-command setup Create both environments for single-image inference: ```bash bash scripts/setup_envs.sh --profile inference ``` Create and verify the CPU release-test environment: ```bash bash scripts/setup_envs.sh --profile test ``` Create the training and test environments together after obtaining the FlashAttention wheel that matches Python, PyTorch, and CUDA: ```bash FLASH_ATTN_WHEEL=/absolute/path/to/validated_flash_attn.whl \ bash scripts/setup_envs.sh --profile all ``` Use `--profile training` to omit the CPU test environment, `--no-verify` to skip post-install checks, or `--dry-run` to inspect every command without changing the machine. The `training` and `all` profiles create `.env` from `.env.example` when needed, but local model and dataset paths still have to be filled in. ## Actor and Judge ```bash conda env create -f environment/actor-judge.yml conda activate mr_iqa_actor_judge python -m pip install --upgrade pip python -m pip install -r requirements/actor-judge.txt ``` Full training/evaluation requires a CUDA 13.0-compatible driver and eight visible NVIDIA GPUs. The launchers also require a prebuilt FlashAttention wheel. Configure it in your private `.env` using `.env.example`; the launcher validates the artifact automatically. Install that same wheel into the Actor/Judge environment before the first preflight: ```bash python -m pip install /path/to/validated_flash_attn.whl python -c 'import flash_attn; print(flash_attn.__version__)' ``` The wheel must match the Python, PyTorch, and CUDA ABI. ## Editor Conda setup: ```bash conda env create -f environment/editor.yml conda activate mr_iqa_editor python -m pip install --upgrade pip python -m pip install -r requirements/editor.txt ``` Set `DIFFUSERS_VENV` and `DIFFUSERS_MODEL_PATH` in `.env`. ## CPU release checks The repository's format, privacy, data-integrity, and contract tests do not load model weights or initialize CUDA: ```bash python -m venv .venv/release-test source .venv/release-test/bin/activate python -m pip install --upgrade pip python -m pip install -r requirements/test.txt python -m pip install torch==2.11.0 \ --index-url https://download.pytorch.org/whl/cpu bash scripts/test_release.sh ``` Use `bash scripts/test_release.sh --static` before installing test dependencies. The one-command test profile uses `environment/test.yml` and runs the same suite after installation. ## Configuration and provenance Copy `.env.example` to `.env` and fill in local paths. Never commit `.env` or tokens. Launchers validate configured artifacts automatically. Capture a sanitized runtime manifest alongside every run without recording a hostname, username, or local path: ```bash python environment/capture_runtime.py --role actor-judge > runtime-actor-judge.json python environment/capture_runtime.py --role editor > runtime-editor.json ```