---

name: inference-and-evaluation description: "Build and debug MUNIT single-image, example-guided, batch translation, and IS/CIS evaluation commands." disable-model-invocation: true metadata: disco-role: operating license: NOASSERTION

Inference and Evaluation

Use this sub-skill when the user wants to translate images with a trained MUNIT or UNIT checkpoint, produce diverse samples, use an example style image, process an input folder, or reason about optional Inception Score / Conditional Inception Score metrics.

Responsibilities

• Construct safe commands for test.py single-image inference and test_batch.py folder inference without loading checkpoints or starting CUDA by default.
• Explain A-to-B versus B-to-A direction, random style sampling, synchronized style codes, example-guided style, num_style, and output naming.
• Diagnose missing checkpoint/config/input paths, style/config mismatches, output folder surprises, and old checkpoint conversion behavior.
• Distinguish core translation from optional IS/CIS metric computation and its additional Inception-model prerequisites.

Start Here

1. Confirm runtime and checkpoint prerequisites in ../environment-and-setup/; unmodified inference calls .cuda() and needs a compatible legacy runtime.

2. Validate the YAML and any input folders in ../data-and-configuration/ when the command uses a config or batch folder.

3. Read references/workflows.md for single-image, example-guided, and batch recipes.

4. Use a bundled command builder to print the command without executing it:

   python scripts/munit_inference_command.py --help
   python scripts/munit_inference_command.py \
     --repo-root /path/to/user/munit-checkout \
     --config configs/edges2shoes_folder.yaml \
     --input inputs/edges2shoes_edge.jpg \
     --checkpoint models/edges2shoes.pt \
     --output-folder outputs/edges2shoes \
     --a2b 1 \
     --num-style 10
   

5. For folder inference or metrics, use:

   python scripts/munit_batch_command.py --help
   

Route Elsewhere

• Installing the legacy PyTorch/CUDA stack or triaging import failures: ../environment-and-setup/.
• Editing configs, dataset folders, or list files: ../data-and-configuration/.
• Training checkpoints or resume behavior: ../training/.
• Changing model architecture, checkpoint key conversion, or modernizing source code: ../model-internals/.

Safety Gates

• Do not auto-download pretrained checkpoints, Inception models, datasets, or VGG assets.
• Do not run actual inference unless the user provides local asset paths, accepts CUDA/runtime requirements, and authorizes execution.
• Do not treat --help success as proof that a checkpoint can run; help checks validate parser coverage only.
• Do not claim CPU inference support for the unmodified scripts. They move models, inputs, styles, and tensors to CUDA.

Reference Map

• references/workflows.md - practical single-image, example-guided, batch, direction, and output recipes.
• references/cli-reference.md - exact test.py and test_batch.py flags and defaults.
• references/evaluation-metrics.md - IS/CIS metric prerequisites and interpretation boundaries.
• references/troubleshooting.md - symptom-driven fixes for checkpoint, style, direction, output, metric, and legacy-runtime failures.
• scripts/munit_inference_command.py - safe single-image/example-guided command builder.
• scripts/munit_batch_command.py - safe batch/metric command builder.