Two stages: the latent upscaler list is read again when Settings open

Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com>
Claude-Session: https://claude.ai/code/session_01Tw9fjVWCMpMsh4XkZmnKnh

modules/sampling/two_stage/__init__.py

@@ -86,4 +86,4 @@ def install(patcher, values, key):
     return f"first {steps} step(s) at {size:.0%} of the size" + (f", enlarged by {resize}" if resize else "")
 
 
-PROVIDES = {"modifier": install}
+PROVIDES = {"modifier": install, "setting_options": lambda: {"upscaler": _options()}}

modules/sampling/two_stage/tests/test_two_stage.py

@@ -142,3 +142,14 @@ def test_the_upscaler_follows_the_latents_dtype(upscaler_file):
     video = torch.randn(1, 24, 2, 4, 4, device="cpu", dtype=torch.bfloat16)
     out = stages.enlarge(video, 8, 8, net)
     assert out.dtype == torch.bfloat16 and out.device == video.device
+
+
+def test_the_upscaler_list_is_read_again_when_settings_open(upscaler_file, tmp_path):
+    from modules.sampling import two_stage
+    from safetensors.torch import save_file
+    assert [o["value"] for o in two_stage.PROVIDES["setting_options"]()["upscaler"]] == [upscaler_file]
+    save_file({"x": torch.zeros(1)}, str(tmp_path / "later.safetensors"))
+    import folder_paths
+    folder_paths.filename_list_cache.pop("latent_upscale_models", None)
+    now = [o["value"] for o in two_stage.PROVIDES["setting_options"]()["upscaler"]]
+    assert "later.safetensors" in now