test_models.py

#!/usr/bin/env python3
"""Architecture-factory tests. Skipped automatically when torch is unavailable.

Run with ``python3 test_models.py``. Validates that every torchvision backbone
builds, runs a forward pass, and returns both heads at input resolution, and
that an unknown architecture is rejected.
"""
import sys


def main():
    try:
        import torch
    except ImportError:
        print("torch not installed; skipping model architecture tests")
        return

    from models import DEFAULT_ARCH, available_architectures, build_model

    architectures = available_architectures()
    assert DEFAULT_ARCH in architectures
    assert {"deeplabv3_mobilenet_v3_large", "deeplabv3_resnet50", "segformer_b2"} <= set(architectures)

    for arch in ("deeplabv3_mobilenet_v3_large", "deeplabv3_resnet50"):
        model = build_model(arch, 10, pretrained_backbone=False).eval()
        with torch.inference_mode():
            output = model(torch.zeros(1, 3, 128, 128))
        assert output["semantic"].shape == (1, 10, 128, 128), (arch, output["semantic"].shape)
        assert output["drywall"].shape == (1, 2, 128, 128), (arch, output["drywall"].shape)
        print(f"ok  {arch}")

    try:
        build_model("not_a_real_arch", 10)
    except ValueError:
        print("ok  unknown architecture rejected")
    else:
        raise AssertionError("unknown architecture should raise ValueError")

    print("model architecture tests passed")


if __name__ == "__main__":
    main()