From ba601f1bba03a9a63d52dfd52ce5911deb047edf Mon Sep 17 00:00:00 2001
From: blepping <blepping@tuta.io>
Date: Sun, 24 Aug 2025 00:32:11 -0600
Subject: [PATCH] Fix EasyCache/LazyCache crash when tensor shape/dtype/device
 changes during sampling

---
 comfy_extras/nodes_easycache.py | 15 +++++++++++++++
 1 file changed, 15 insertions(+)

diff --git a/comfy_extras/nodes_easycache.py b/comfy_extras/nodes_easycache.py
index e2b2efcd9..8ff673241 100644
--- a/comfy_extras/nodes_easycache.py
+++ b/comfy_extras/nodes_easycache.py
@@ -28,6 +28,7 @@ def easycache_forward_wrapper(executor, *args, **kwargs):
     input_change = None
     do_easycache = easycache.should_do_easycache(sigmas)
     if do_easycache:
+        easycache.check_metadata(x)
         # if first cond marked this step for skipping, skip it and use appropriate cached values
         if easycache.skip_current_step:
             if easycache.verbose:
@@ -92,6 +93,7 @@ def lazycache_predict_noise_wrapper(executor, *args, **kwargs):
     input_change = None
     do_easycache = easycache.should_do_easycache(timestep)
     if do_easycache:
+        easycache.check_metadata(x)
         if easycache.has_x_prev_subsampled():
             if easycache.has_x_prev_subsampled():
                 input_change = (easycache.subsample(x, clone=False) - easycache.x_prev_subsampled).flatten().abs().mean()
@@ -194,6 +196,7 @@ class EasyCacheHolder:
         # how to deal with mismatched dims
         self.allow_mismatch = True
         self.cut_from_start = True
+        self.state_metadata = None
 
     def is_past_end_timestep(self, timestep: float) -> bool:
         return not (timestep[0] > self.end_t).item()
@@ -283,6 +286,17 @@ class EasyCacheHolder:
     def has_first_cond_uuid(self, uuids: list[UUID]) -> bool:
         return self.first_cond_uuid in uuids
 
+    def check_metadata(self, x: torch.Tensor) -> bool:
+        metadata = (x.device, x.dtype, x.shape)
+        if self.state_metadata is None:
+            self.state_metadata = metadata
+            return True
+        if metadata == self.state_metadata:
+            return True
+        logging.warn(f"{self.name} - Tensor shape, dtype or device changed, resetting state")
+        self.reset()
+        return False
+
     def reset(self):
         self.relative_transformation_rate = 0.0
         self.cumulative_change_rate = 0.0
@@ -299,6 +313,7 @@ class EasyCacheHolder:
         del self.uuid_cache_diffs
         self.uuid_cache_diffs = {}
         self.total_steps_skipped = 0
+        self.state_metadata = None
         return self
 
     def clone(self):