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d13a83d | 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27 28 29 30 31 32 33 34 35 36 37 38 39 40 41 42 43 44 45 46 47 48 49 50 51 52 53 54 55 56 57 58 59 60 61 62 63 64 65 66 67 68 69 70 71 72 73 74 75 76 77 78 79 80 81 82 83 84 85 86 87 88 89 90 91 92 93 94 95 96 97 98 99 100 101 | # 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
```
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