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
104 lines
3.8 KiB
Python
104 lines
3.8 KiB
Python
"""Shadow negative on a real H3 forward.
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The sampling run is ComfyUI's CFGGuider in real life; here the OUTER_SAMPLE
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wrapper is called the way comfy/samplers.py calls it -- an executor whose
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class_obj is the guider, with `conds` already copied -- around a real forward.
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"""
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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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class _Guider:
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def __init__(self, negative):
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self.conds = {"positive": [{"cross_attn": torch.zeros(1, 5, 48)}],
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"negative": [] if negative is None else [{"cross_attn": negative}]}
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class _Executor:
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def __init__(self, guider, fn):
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self.class_obj, self._fn = guider, fn
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def __call__(self, *a, **k):
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return self._fn()
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def _sample(tiny, patched, negative, **run):
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from comfy.patcher_extension import WrappersMP
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result = {}
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def go():
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result["out"] = tiny.run(patched, **run)
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wrappers = [w for ws in patched.wrappers.get(WrappersMP.OUTER_SAMPLE, {}).values() for w in ws]
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call = go
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for w in wrappers:
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call = (lambda w, inner: (lambda: w(_Executor(_Guider(negative), inner))))(w, call)
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call()
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return result["out"]
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def _load(tiny, **values):
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from modules.sampling.modifiers.nodes import FunUILoadModifiers
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return FunUILoadModifiers.execute(
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tiny.patcher, {"shadow_negative": {"enabled": True, "end": 1.0, **values}}).result
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def test_it_pushes_the_picture_when_there_is_a_negative(tiny_h3):
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base = tiny_h3.run()
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patched, status = _load(tiny_h3, video_scale=4.0, alpha=1.0)
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assert "shadow_negative: picture 4" in status
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out = _sample(tiny_h3, patched, torch.randn(1, 4, 48))
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assert not torch.allclose(out[0], base[0]), "installed and changed nothing (v4's bug)"
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# sound push is 1 = off, but attention mixes modalities through later blocks
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assert torch.isfinite(out[0]).all() and torch.isfinite(out[1]).all()
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def test_with_no_negative_prompt_the_output_is_untouched(tiny_h3):
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base = tiny_h3.run()
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patched, _ = _load(tiny_h3, video_scale=4.0, alpha=1.0)
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out = _sample(tiny_h3, patched, None)
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assert torch.allclose(out[0], base[0])
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def test_a_different_negative_gives_a_different_result(tiny_h3):
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patched, _ = _load(tiny_h3, video_scale=4.0, alpha=1.0)
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a = _sample(tiny_h3, patched, torch.randn(1, 4, 48))
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b = _sample(tiny_h3, patched, torch.randn(1, 4, 48))
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assert not torch.allclose(a[0], b[0]), "the negative text does not reach the push"
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def test_outside_the_step_window_it_does_nothing(tiny_h3):
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base_late = tiny_h3.run(sigma=0.3, sigmas=torch.tensor([1.0, 0.7, 0.3, 0.0]))
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patched, _ = _load(tiny_h3, video_scale=4.0, alpha=1.0, start=0.0, end=0.4)
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late = _sample(tiny_h3, patched, torch.randn(1, 4, 48),
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sigma=0.3, sigmas=torch.tensor([1.0, 0.7, 0.3, 0.0]))
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assert torch.allclose(late[0], base_late[0])
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def test_compose_leaves_a_block_another_feature_holds(tiny_h3):
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from core import dit_hooks
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held = tiny_h3.patcher.clone()
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ran = []
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dit_hooks.add_block_hook(held, "other", 2,
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lambda a, e: (ran.append(1), e["original_block"](a))[1])
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from modules.sampling import shadow_negative as m
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note = m.install(held, {**{k: v["default"] for k, v in m.SETTINGS.items()},
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"enabled": True, "compose": True, "end": 1.0}, key="funui.sn")
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assert "leaves block(s) 2" in note
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_sample(tiny_h3, held, torch.randn(1, 4, 48))
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assert ran == [1]
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def test_it_runs_on_an_i2v_scene_with_a_pinned_first_frame(tiny_h3):
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mask = tiny_h3.pinned_first_frame()
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base = tiny_h3.run(denoise_mask=mask)
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patched, _ = _load(tiny_h3, video_scale=4.0, alpha=1.0)
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out = _sample(tiny_h3, patched, torch.randn(1, 4, 48), denoise_mask=mask)
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assert not torch.allclose(out[0], base[0]), "per-token mod rows made it stand down"
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