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Fix for edge case of EasyCache when conditionings change during a sampling run #12020

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Merged
comfyanonymous merged 1 commit into from
Jan 22, 2026
Merged

Fix for edge case of EasyCache when conditionings change during a sampling run #12020

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9 changes: 7 additions & 2 deletions comfy_extras/nodes_easycache.py
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Original file line number Diff line number Diff line change
Expand Up @@ -29,8 +29,10 @@ def easycache_forward_wrapper(executor, *args, **kwargs):
do_easycache = easycache.should_do_easycache(sigmas)
if do_easycache:
easycache.check_metadata(x)
# if there isn't a cache diff for current conds, we cannot skip this step
can_apply_cache_diff = easycache.can_apply_cache_diff(uuids)
# if first cond marked this step for skipping, skip it and use appropriate cached values
if easycache.skip_current_step:
if easycache.skip_current_step and can_apply_cache_diff:
if easycache.verbose:
logging.info(f"EasyCache [verbose] - was marked to skip this step by {easycache.first_cond_uuid}. Present uuids: {uuids}")
return easycache.apply_cache_diff(x, uuids)
Expand All @@ -44,7 +46,7 @@ def easycache_forward_wrapper(executor, *args, **kwargs):
if easycache.has_output_prev_norm() and easycache.has_relative_transformation_rate():
approx_output_change_rate = (easycache.relative_transformation_rate * input_change) / easycache.output_prev_norm
easycache.cumulative_change_rate += approx_output_change_rate
if easycache.cumulative_change_rate < easycache.reuse_threshold:
if easycache.cumulative_change_rate < easycache.reuse_threshold and can_apply_cache_diff:
if easycache.verbose:
logging.info(f"EasyCache [verbose] - skipping step; cumulative_change_rate: {easycache.cumulative_change_rate}, reuse_threshold: {easycache.reuse_threshold}")
# other conds should also skip this step, and instead use their cached values
Expand Down Expand Up @@ -240,6 +242,9 @@ def subsample(self, x: torch.Tensor, uuids: list[UUID], clone: bool = True) -> t
return to_return.clone()
return to_return

def can_apply_cache_diff(self, uuids: list[UUID]) -> bool:
return all(uuid in self.uuid_cache_diffs for uuid in uuids)

def apply_cache_diff(self, x: torch.Tensor, uuids: list[UUID]):
if self.first_cond_uuid in uuids:
self.total_steps_skipped += 1
Expand Down