Merge pull request #4338 from vladmandic/kanvas

fix cn

Author: vladmandic

modules/devices.py

@@ -429,14 +429,14 @@ def set_cudnn_params():
             torch.use_deterministic_algorithms(opts.cudnn_deterministic)
             if opts.cudnn_deterministic:
                 os.environ.setdefault('CUBLAS_WORKSPACE_CONFIG', ':4096:8')
-                log.debug('Torch cuDNN: deterministic=True')
+                log.debug(f'Torch cuDNN: deterministic={opts.cudnn_deterministic}')
             torch.backends.cudnn.benchmark = opts.cudnn_benchmark
             if opts.cudnn_benchmark:
-                log.debug('Torch cuDNN: benchmark=True')
+                log.debug(f'Torch cuDNN: benchmark={opts.cudnn_benchmark}')
             torch.backends.cudnn.benchmark_limit = opts.cudnn_benchmark_limit
             torch.backends.cudnn.allow_tf32 = True
         except Exception as e:
-            log.warning(f'Torch cudnn: {e}')
+            log.warning(f'Torch cuDNN: {e}')
 
 
 def override_ipex_math():

modules/processing_diffusers.py

@@ -252,7 +252,7 @@ def process_hires(p: processing.StableDiffusionProcessing, output):
         # hires runs on original pipeline
         if hasattr(shared.sd_model, 'restore_pipeline') and (shared.sd_model.restore_pipeline is not None) and (not shared.opts.control_hires):
             shared.sd_model.restore_pipeline()
-        if (getattr(shared.sd_model, 'controlnet', None) is not None) and ((isinstance(shared.sd_model.controlnet, list) and len(shared.sd_model.controlnet) > 1)) or ('Multi' in type(shared.sd_model.controlnet).__name__):
+        if (getattr(shared.sd_model, 'controlnet', None) is not None) and (((isinstance(shared.sd_model.controlnet, list) and len(shared.sd_model.controlnet) > 1)) or ('Multi' in type(shared.sd_model.controlnet).__name__)):
             shared.log.warning(f'Process: control={type(shared.sd_model.controlnet)} not supported in hires')
             return output