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Add slice_cond and per-model context window cond resizing (#12645)

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* Add slice_cond and per-model context window cond resizing

* Fix cond_value.size() call in context window cond resizing

* Expose additional advanced inputs for ContextWindowsManualNode

Necessary for WanAnimate context windows workflow, which needs cond_retain_index_list = 0 to work properly with its reference input.

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This commit is contained in:
drozbay
2026-03-19 21:42:42 -06:00
committed by GitHub
parent e4455fd43a
commit 589228e671
3 changed files with 87 additions and 3 deletions
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comfy/context_windows.py
+53 -1
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@@ -93,6 +93,50 @@ class IndexListCallbacks:
return {}
def slice_cond(cond_value, window: IndexListContextWindow, x_in: torch.Tensor, device, temporal_dim: int, temporal_scale: int=1, temporal_offset: int=0, retain_index_list: list[int]=[]):
if not (hasattr(cond_value, "cond") and isinstance(cond_value.cond, torch.Tensor)):
return None
cond_tensor = cond_value.cond
if temporal_dim >= cond_tensor.ndim:
return None
cond_size = cond_tensor.size(temporal_dim)
if temporal_scale == 1:
expected_size = x_in.size(window.dim) - temporal_offset
if cond_size != expected_size:
return None
if temporal_offset == 0 and temporal_scale == 1:
sliced = window.get_tensor(cond_tensor, device, dim=temporal_dim, retain_index_list=retain_index_list)
return cond_value._copy_with(sliced)
# skip leading latent positions that have no corresponding conditioning (e.g. reference frames)
if temporal_offset > 0:
indices = [i - temporal_offset for i in window.index_list[temporal_offset:]]
indices = [i for i in indices if 0 <= i]
else:
indices = list(window.index_list)
if not indices:
return None
if temporal_scale > 1:
scaled = []
for i in indices:
for k in range(temporal_scale):
si = i * temporal_scale + k
if si < cond_size:
scaled.append(si)
indices = scaled
if not indices:
return None
idx = tuple([slice(None)] * temporal_dim + [indices])
sliced = cond_tensor[idx].to(device)
return cond_value._copy_with(sliced)
@dataclass
class ContextSchedule:
name: str
@@ -177,10 +221,17 @@ class IndexListContextHandler(ContextHandlerABC):
new_cond_item[cond_key] = result
handled = True
break
if not handled and self._model is not None:
result = self._model.resize_cond_for_context_window(
cond_key, cond_value, window, x_in, device,
retain_index_list=self.cond_retain_index_list)
if result is not None:
new_cond_item[cond_key] = result
handled = True
if handled:
continue
if isinstance(cond_value, torch.Tensor):
if (self.dim < cond_value.ndim and cond_value(self.dim) == x_in.size(self.dim)) or \
if (self.dim < cond_value.ndim and cond_value.size(self.dim) == x_in.size(self.dim)) or \
(cond_value.ndim < self.dim and cond_value.size(0) == x_in.size(self.dim)):
new_cond_item[cond_key] = window.get_tensor(cond_value, device)
# Handle audio_embed (temporal dim is 1)
@@ -224,6 +275,7 @@ class IndexListContextHandler(ContextHandlerABC):
return context_windows
def execute(self, calc_cond_batch: Callable, model: BaseModel, conds: list[list[dict]], x_in: torch.Tensor, timestep: torch.Tensor, model_options: dict[str]):
self._model = model
self.set_step(timestep, model_options)
context_windows = self.get_context_windows(model, x_in, model_options)
enumerated_context_windows = list(enumerate(context_windows))