The two-pass shift regrew the frames it dropped, and the invented ending consistently came out with worse or missing movement — not worth paying steps for. What is left is the part that works: generate the scene exactly as normal, anchor pinned at full strength the whole way, then cut the opening off the finished clip. Nothing is regrown, so the scene comes out that much shorter and the audio is cropped to match. Six knobs collapse into one INT, cut_opening_frames (0 = off), in the Editor under Chain Sampler ▸ Timing & Seed rather than Experimental. Gone with the shift: the mid-schedule split, the rewind re-noise (_renoise_to_sigma), the tail refill modes, the fresh-audio reset, and the schedule_context/continue_from_state plumbing that existed only so a split scene would not re-time the sampler inside each half. second_pass is untouched — it never used any of that machinery. Co-Authored-By: Claude Opus 5 <noreply@anthropic.com>
161 lines
7.1 KiB
Python
161 lines
7.1 KiB
Python
"""cut_opening_frames — "fake t2v": generate with the real untouched i2v anchor, then cut it.
|
|
|
|
The point of the feature is that the anchor is NOT weakened on the way in (ALG blurs it and
|
|
loses character detail; Best-FaceID overlap tokens approximate it and lose some too) — it is
|
|
pinned at full strength for the whole schedule and the opening is then cut off the FINISHED
|
|
clip. Nothing is regrown to replace it (regrowing was tried and the invented ending came out
|
|
with worse or missing movement), so the invariants worth testing are:
|
|
|
|
1. The clip really does get SHORTER — no tail is invented, no joint is blended, and every
|
|
surviving frame is the original untouched one.
|
|
2. Video and audio still describe the same duration. Audio timing comes from the audio
|
|
stream's own index, so cropping the two by different amounts desyncs the clip silently.
|
|
3. The pin goes with the frame it belonged to.
|
|
4. The cut can never consume the whole clip, and never mutates its input.
|
|
5. The t2v guard: no pinned anchor means there is nothing to cut out.
|
|
"""
|
|
import sys
|
|
import types
|
|
from pathlib import Path
|
|
|
|
import pytest
|
|
import torch
|
|
|
|
sys.path.insert(0, str(Path(__file__).resolve().parents[1]))
|
|
|
|
for _name in (
|
|
"comfy", "comfy.k_diffusion", "comfy.k_diffusion.sampling",
|
|
"comfy.model_sampling", "comfy.nested_tensor", "comfy.sample",
|
|
"comfy.samplers", "comfy.utils",
|
|
):
|
|
sys.modules.setdefault(_name, types.ModuleType(_name))
|
|
sys.modules["comfy.nested_tensor"].NestedTensor = object
|
|
|
|
import samplers # noqa: E402
|
|
|
|
|
|
class _FakeNested(list):
|
|
"""Minimal stand-in for comfy's NestedTensor: enough for _is_nested + unbind."""
|
|
is_nested = True
|
|
|
|
def unbind(self):
|
|
return list(self)
|
|
|
|
|
|
@pytest.fixture
|
|
def nested_stub():
|
|
"""Give the module a usable NestedTensor for the packed AV latents.
|
|
|
|
Snapshot/restore: these comfy stubs are SHARED module objects across every test module,
|
|
so leaving mutations behind changes other files' results depending on collection order.
|
|
"""
|
|
comfy_mod = sys.modules["comfy"]
|
|
nested_mod = sys.modules["comfy.nested_tensor"]
|
|
saved = (nested_mod.NestedTensor, getattr(comfy_mod, "nested_tensor", None))
|
|
nested_mod.NestedTensor = _FakeNested
|
|
comfy_mod.nested_tensor = nested_mod # attribute access, not just sys.modules
|
|
yield
|
|
nested_mod.NestedTensor = saved[0]
|
|
if saved[1] is None:
|
|
delattr(comfy_mod, "nested_tensor")
|
|
else:
|
|
comfy_mod.nested_tensor = saved[1]
|
|
|
|
|
|
def _node():
|
|
return samplers.FunPackLTXAVSceneChainSampler()
|
|
|
|
|
|
def _latent(frames=10):
|
|
video = torch.arange(frames, dtype=torch.float32).view(1, 1, frames, 1, 1).repeat(1, 4, 1, 2, 2)
|
|
return {"samples": video, "noise_mask": torch.zeros_like(video)}
|
|
|
|
|
|
def _av_latent(video_frames=10, audio_frames=20):
|
|
"""A packed-style AV latent: video [B,C,F,H,W] + audio [B,C,T] at its own rate."""
|
|
video = torch.arange(video_frames, dtype=torch.float32).view(
|
|
1, 1, video_frames, 1, 1).repeat(1, 4, 1, 2, 2)
|
|
audio = torch.arange(audio_frames, dtype=torch.float32).view(1, 1, audio_frames).repeat(1, 4, 1)
|
|
return {"samples": _FakeNested([video, audio]), "noise_mask": torch.zeros_like(video)}
|
|
|
|
|
|
# ── the cut ─────────────────────────────────────────────────────────────────
|
|
|
|
def test_cut_shortens_the_clip_instead_of_regrowing_a_tail():
|
|
cut, dropped = _node()._cut_opening_latent(_latent(frames=10), 3)
|
|
assert dropped == 3
|
|
# 10 - 3, not 10: nothing is invented at the end, which is the whole point.
|
|
assert cut["samples"].shape[2] == 7
|
|
# And what survives is the ORIGINAL frames 3..9, untouched — no blend, no joint.
|
|
assert [int(v) for v in cut["samples"][0, 0, :, 0, 0]] == [3, 4, 5, 6, 7, 8, 9]
|
|
|
|
|
|
def test_cut_drops_the_pin_with_the_frame_it_belonged_to():
|
|
latent = _latent(frames=10)
|
|
assert "noise_mask" in latent
|
|
cut, _ = _node()._cut_opening_latent(latent, 1)
|
|
assert "noise_mask" not in cut
|
|
|
|
|
|
def test_cut_never_consumes_the_whole_clip():
|
|
cut, dropped = _node()._cut_opening_latent(_latent(frames=4), 99)
|
|
assert dropped == 3 # clamped to frames - 1
|
|
assert cut["samples"].shape[2] == 1
|
|
|
|
|
|
def test_zero_drop_is_a_no_op():
|
|
cut, dropped = _node()._cut_opening_latent(_latent(frames=6), 0)
|
|
assert dropped == 0
|
|
assert torch.equal(cut["samples"], _latent(frames=6)["samples"])
|
|
|
|
|
|
def test_source_latent_is_never_mutated():
|
|
latent = _latent(frames=8)
|
|
before = latent["samples"].clone()
|
|
_node()._cut_opening_latent(latent, 3)
|
|
assert torch.equal(latent["samples"], before)
|
|
|
|
|
|
# ── audio stays in sync ─────────────────────────────────────────────────────
|
|
|
|
def test_cut_keeps_audio_and_video_describing_the_same_duration(nested_stub):
|
|
"""Audio timing comes from the audio stream's own index and video's from its own RoPE,
|
|
so cropping them by different amounts of TIME desyncs the clip silently — no error,
|
|
just drifting sound. The kept lengths must stay in proportion."""
|
|
cut, _ = _node()._cut_opening_latent(_av_latent(10, 20), 3)
|
|
video, audio = cut["samples"].unbind()
|
|
assert video.shape[2] == 7 and audio.shape[2] == 14 # 7/10 == 14/20
|
|
# Cropped from the HEAD, matching the video — the tail is what survives.
|
|
assert [int(v) for v in audio[0, 0]] == list(range(6, 20))
|
|
|
|
|
|
def test_cut_keeps_proportion_when_the_rate_does_not_divide_evenly(nested_stub):
|
|
"""The rounding trap: deriving audio's KEPT length from the new video length keeps the
|
|
two in proportion; subtracting a separately-rounded drop can leave them a frame apart."""
|
|
for v_frames, a_frames, drop in ((10, 15, 3), (9, 14, 4), (13, 7, 5), (10, 21, 7)):
|
|
cut, _ = _node()._cut_opening_latent(_av_latent(v_frames, a_frames), drop)
|
|
video, audio = cut["samples"].unbind()
|
|
assert audio.shape[2] == max(1, round(a_frames * video.shape[2] / v_frames))
|
|
assert audio.shape[2] >= 1 and video.shape[2] >= 1
|
|
|
|
|
|
# ── the t2v guard ───────────────────────────────────────────────────────────
|
|
|
|
def test_pinned_frames_counts_the_anchor_prefix():
|
|
n = _node()
|
|
frames = 6
|
|
video = torch.zeros(1, 4, frames, 2, 2)
|
|
mask = torch.ones(1, 4, frames, 2, 2)
|
|
mask[:, :, :2] = 0.0 # two pinned anchor frames
|
|
assert n._anchor_pinned_frames({"samples": video, "noise_mask": mask}) == 2
|
|
|
|
|
|
def test_pinned_frames_is_zero_for_a_real_t2v_scene():
|
|
"""No anchor image attached — Easy Gen's default. Cutting would throw away real content,
|
|
so the caller must skip: this is the 'fake t2v' trick and it needs an anchor to fake with."""
|
|
n = _node()
|
|
video = torch.zeros(1, 4, 6, 2, 2)
|
|
assert n._anchor_pinned_frames({"samples": video, "noise_mask": torch.ones(1, 4, 6, 2, 2)}) == 0
|
|
assert n._anchor_pinned_frames({"samples": video}) == 0 # no mask at all
|
|
assert n._anchor_pinned_frames({"samples": None}) == 0 # unreadable -> refuse, don't raise
|