timesteps with hires

modules/processing_diffusers.py

@@ -488,7 +488,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
         desc='Base',
     )
     update_sampler(shared.sd_model)
-    shared.state.sampling_steps = base_args.get('num_inference_steps', p.steps)
+    shared.state.sampling_steps = base_args.get('num_inference_steps', None) or p.steps
     p.extra_generation_params['Pipeline'] = shared.sd_model.__class__.__name__
     if shared.opts.scheduler_eta is not None and shared.opts.scheduler_eta > 0 and shared.opts.scheduler_eta < 1:
         p.extra_generation_params["Sampler Eta"] = shared.opts.scheduler_eta
@@ -594,7 +594,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
             )
             update_sampler(shared.sd_model, second_pass=True)
             shared.state.job = 'hires'
-            shared.state.sampling_steps = hires_args['num_inference_steps']
+            shared.state.sampling_steps = hires_args.get('num_inference_steps', None) or p.steps
             try:
                 sd_models_compile.check_deepcache(enable=True)
                 output = shared.sd_model(**hires_args) # pylint: disable=not-callable
@@ -658,7 +658,7 @@ def process_diffusers(p: processing.StableDiffusionProcessing):
                 desc='Refiner',
             )
             update_sampler(shared.sd_refiner, second_pass=True)
-            shared.state.sampling_steps = refiner_args['num_inference_steps']
+            shared.state.sampling_steps = refiner_args.get('num_inference_steps', None) or p.steps
             try:
                 if 'requires_aesthetics_score' in shared.sd_refiner.config: # sdxl-model needs false and sdxl-refiner needs true
                     shared.sd_refiner.register_to_config(requires_aesthetics_score = getattr(shared.sd_refiner, 'tokenizer', None) is None)

modules/processing_helpers.py

@@ -438,8 +438,8 @@ def calculate_base_steps(p, use_denoise_start, use_refiner_start):
     return max(1, int(steps))
 
 def calculate_hires_steps(p):
-    if len(getattr(p, 'timesteps', [])) > 0:
-        return None
+    # if len(getattr(p, 'timesteps', [])) > 0:
+    #    return None
     if p.hr_second_pass_steps > 0:
         steps = (p.hr_second_pass_steps // p.denoising_strength) + 1
     elif p.denoising_strength > 0:
@@ -450,8 +450,8 @@ def calculate_hires_steps(p):
     return max(1, int(steps))
 
 def calculate_refiner_steps(p):
-    if len(getattr(p, 'timesteps', [])) > 0:
-        return None
+    # if len(getattr(p, 'timesteps', [])) > 0:
+    #    return None
     if "StableDiffusionXL" in shared.sd_refiner.__class__.__name__:
         if p.refiner_start > 0 and p.refiner_start < 1:
             #steps = p.refiner_steps // (1 - p.refiner_start) # SDXL with denoise strenght

modules/styles.py

@@ -80,19 +80,25 @@ def apply_wildcards_to_prompt(prompt, all_wildcards):
     if len(prompt) == 0:
         return prompt
     replaced = {}
+    t0 = time.time()
     for style_wildcards in all_wildcards:
         wildcards = [x.strip() for x in style_wildcards.replace('\n', ' ').split(";") if len(x.strip()) > 0]
         for wildcard in wildcards:
-            what, words = wildcard.split("=", 1)
-            words = [x.strip() for x in words.split(",") if len(x.strip()) > 0]
-            word = random.choice(words)
-            prompt = prompt.replace(what, word)
-            replaced[what] = word
-    t0 = time.time()
-    prompt, replaced, not_found = apply_file_wildcards(prompt, [], [])
+            try:
+                what, words = wildcard.split("=", 1)
+                words = [x.strip() for x in words.split(",") if len(x.strip()) > 0]
+                word = random.choice(words)
+                prompt = prompt.replace(what, word)
+                replaced[what] = word
+            except Exception as e:
+                shared.log.error(f'Wildcards: wildcard="{wildcard}" error={e}')
     t1 = time.time()
-    if len(replaced) > 0 or len(not_found) > 0:
-        shared.log.info(f'Wildcards applied: {replaced} missing: {not_found} path="{shared.opts.wildcards_dir}" time={t1-t0:.2f}')
+    prompt, replaced_file, not_found = apply_file_wildcards(prompt, [], [])
+    t2 = time.time()
+    if replaced:
+        shared.log.info(f'Wildcards applied: {replaced} path="{shared.opts.wildcards_dir}" type=style time={t1-t0:.2f}')
+    if len(replaced_file) > 0 or len(not_found) > 0:
+        shared.log.info(f'Wildcards applied: {replaced_file} missing: {not_found} path="{shared.opts.wildcards_dir}" type=file time={t2-t2:.2f} ')
     return prompt