diff --git a/CHANGELOG.md b/CHANGELOG.md
index 2299fae21..6c729a613 100644
--- a/CHANGELOG.md
+++ b/CHANGELOG.md
@@ -1,6 +1,6 @@
 # Change Log for SD.Next
 
-## Update for 2024-02-16
+## Update for 2024-02-17
 
 - **Improvements**:
   - **IP Adapter** major refactor  
@@ -31,7 +31,8 @@
   - [DeepCache](https://github.com/horseee/DeepCache) model acceleration  
     it can produce massive speedups (2x-5x) with no overhead, but with some loss of quality  
     *settings -> compute -> model compile -> deep-cache* and *settings -> compute -> model compile -> cache interval*  
-  - [ZLUDA](https://github.com/vosen/ZLUDA) CUDA wrapper experimental support, thanks @lshqqytiger  
+  - [ZLUDA](https://github.com/vosen/ZLUDA) experimental support, thanks @lshqqytiger  
+    - ZLUDA is CUDA wrapper that can be used for GPUs without native support
     - best use case is *AMD GPUs on Windows*, see [wiki](https://github.com/vladmandic/automatic/wiki/ZLUDA) for details  
   - **Control**
     - when performing inpainting, you can specify processing resolution using **size->mask**  
@@ -66,6 +67,7 @@
   - update dependencies  
   - refactor txt2img/img2img api  
   - enhanced theme loader  
+  - add additional debug env variables  
 - **Fixes**:  
   - handle extensions that install conflicting versions of packages  
     `onnxruntime`, `opencv2-python`  
@@ -81,6 +83,7 @@
   - control fix resize causing runtime errors  
   - control fix processor override image after processor change  
   - control fix display grid with batch  
+  - control restore pipeline before running scripts/extensions  
   - handle pipelines that return dict instead of object  
   - lora use strict name matching if preferred option is by-filename  
   - fix inpaint mask only for diffusers  
diff --git a/modules/processing.py b/modules/processing.py
index 298268223..b11cbe60a 100644
--- a/modules/processing.py
+++ b/modules/processing.py
@@ -317,7 +317,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
                 return create_infotext(p, p.prompts, p.seeds, p.subseeds, index=index, all_negative_prompts=p.negative_prompts)
 
             if hasattr(shared.sd_model, 'restore_pipeline') and shared.sd_model.restore_pipeline is not None:
-                print('HERE')
                 shared.sd_model.restore_pipeline()
 
             for i, x_sample in enumerate(x_samples_ddim):
diff --git a/modules/processing_diffusers.py b/modules/processing_diffusers.py
index 1f31205d3..7a56c66ce 100644
--- a/modules/processing_diffusers.py
+++ b/modules/processing_diffusers.py
@@ -14,6 +14,7 @@ from modules.onnx_impl import preprocess_pipeline as preprocess_onnx_pipeline, c
 
 
 debug = shared.log.trace if os.environ.get('SD_DIFFUSERS_DEBUG', None) is not None else lambda *args, **kwargs: None
+debug_callback = shared.log.trace if os.environ.get('SD_CALLBACK_DEBUG', None) is not None else lambda *args, **kwargs: None
 debug('Trace: DIFFUSERS')
 
 
@@ -52,11 +53,9 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                 time.sleep(0.1)
 
     def diffusers_callback(pipe, step: int, timestep: int, kwargs: dict):
+        latents = kwargs.get('latents', None)
+        debug_callback(f'Callback: step={step} timestep={timestep} latents={latents.shape if latents is not None else None} kwargs={list(kwargs)}')
         shared.state.sampling_step = step
-        if shared.opts.nan_skip:
-            latents = kwargs.get('latents', None)
-            if latents is not None:
-                assert not torch.isnan(latents[..., 0, 0]).all(), f'NaN detected at step {step}: Skipping...'
         if shared.state.interrupted or shared.state.skipped:
             raise AssertionError('Interrupted...')
         if shared.state.paused:
@@ -65,8 +64,10 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                 if shared.state.interrupted or shared.state.skipped:
                     raise AssertionError('Interrupted...')
                 time.sleep(0.1)
-        if kwargs.get('latents', None) is None:
+        if latents is None:
             return kwargs
+        elif shared.opts.nan_skip:
+            assert not torch.isnan(latents[..., 0, 0]).all(), f'NaN detected at step {step}: Skipping...'
         if len(getattr(p, "ip_adapter_names", [])) > 0:
             ip_adapter_scales = list(p.ip_adapter_scales)
             ip_adapter_starts = list(p.ip_adapter_starts)
diff --git a/wiki b/wiki
index 569aa7a72..7654276a0 160000
--- a/wiki
+++ b/wiki
@@ -1 +1 @@
-Subproject commit 569aa7a72fdac20e4136333cfb66a27f63257a38
+Subproject commit 7654276a07723988aefc17da885de8686ee0c530