Claude
3adebb731f
Old project/workflow names and browser settings migrate on load; /funpack redirects to /fun. Co-Authored-By: Claude Sonnet 5.5 <noreply@anthropic.com> Claude-Session: https://claude.ai/code/session_016acRss69eH1235eRdFTZHY
111 lines
4.6 KiB
Python
111 lines
4.6 KiB
Python
"""Every modifier, every setting, on a real tiny model: nothing is shipped that was never switched on.
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A module's own tests exercise the settings its author thought of. This one switches each module on and walks every
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setting through each of its choices (every enum option, a bool both ways, a number at its smallest, largest and
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default) on the real tiny H3 and LTX models, then runs a forward pass. A choice that was offered in Settings and
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raises, installs nothing, or makes the output non-finite is a path the app promised and does not keep.
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Weights are random and the model is four blocks wide, so this says nothing about quality: only that the path runs.
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"""
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import math
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import pytest
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import torch
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@pytest.fixture(autouse=True)
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def _needs_comfy(comfyui):
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"""Imports comfy."""
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def _variants(spec):
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"""(label, values) for the module on, then one setting changed at a time to each of its other choices."""
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base = {"enabled": True} if "enabled" in spec.settings else {}
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yield "default", base
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for key, s in spec.settings.items():
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if key == "enabled":
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continue
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kind = s["type"]
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if kind == "bool":
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choices = [not s["default"]]
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elif kind == "enum":
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choices = [o["value"] for o in s["options"] if o["value"] != s["default"]]
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elif kind in ("int", "float"):
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lo, hi = s.get("min"), s.get("max")
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choices = [v for v in (lo, hi) if v is not None and v != s["default"] and math.isfinite(v)]
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if kind == "int":
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choices = [int(v) for v in choices]
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else:
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choices = [] # free text, paths and colours have no edges to walk
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for value in choices:
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yield f"{key}={value!r}", {**base, key: value}
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def _cases():
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reg = _registry()
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for spec in sorted(reg.specs.values(), key=lambda s: s.id):
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if spec.provides.get("modifier") and spec.settings:
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for label, values in _variants(spec):
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yield pytest.param(spec.id, values, id=f"{spec.id}:{label}")
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def _registry():
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from core import registry
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return registry.current()
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def _apply(model, module_id, values):
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from modules.sampling.modifiers.nodes import FunUILoadModifiers
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settings = {"taste": {"key": "sweep"}, module_id: values}
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return FunUILoadModifiers.execute(model.patcher, settings).result
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def _finite(out):
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parts = out if isinstance(out, (list, tuple)) else [out]
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return all(torch.isfinite(p).all() for p in parts if torch.is_tensor(p))
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#: Failures that come from the stand-in model, not from the module: a four-block model has no blocks 31-40, and the
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#: LTX stand-in is not a model_base class with the windowing hook (the module's own tests patch that in). Likewise
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#: PTD has no adapter file on a test machine (its own tests build one).
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TINY_MODEL = ("no usable blocks", "map_context_window_to_modalities", "no PTD adapter file")
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def _install_failures(status):
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return [line for line in status.splitlines()
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if ("failed to install" in line or "could not be guarded" in line) and not any(t in line for t in TINY_MODEL)]
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def _stand_in_limit(status):
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return any("failed to install" in line and any(t in line for t in TINY_MODEL) for line in status.splitlines())
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@pytest.mark.parametrize("module_id,values", list(_cases()))
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def test_h3_every_choice_installs_and_runs(tiny_h3, module_id, values):
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spec = _registry().specs[module_id]
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patched, status = _apply(tiny_h3, module_id, values)
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assert not _install_failures(status), status
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if _stand_in_limit(status):
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pytest.skip("the four-block stand-in has no such blocks")
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if spec.requires and not set(spec.requires) <= _traits(patched, spec):
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pytest.skip(f"{module_id} is not offered for H3")
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assert _finite(tiny_h3.sample(patched)), f"{module_id} {values}: non-finite output"
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@pytest.mark.parametrize("module_id,values", list(_cases()))
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def test_ltx_every_choice_installs_and_runs(tiny_ltx, module_id, values):
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spec = _registry().specs[module_id]
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patched, status = _apply(tiny_ltx, module_id, values)
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assert not _install_failures(status), status
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if _stand_in_limit(status):
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pytest.skip("the stand-in model lacks what this module asks of a real one")
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if spec.requires and not set(spec.requires) <= _traits(patched, spec):
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pytest.skip(f"{module_id} is not offered for LTX")
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assert _finite(tiny_ltx.run(patched)), f"{module_id} {values}: non-finite output"
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def _traits(patched, spec):
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from core import traits as traits_mod
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return set(traits_mod.traits_of(patched, list(_registry().specs.values())))
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