diff options
Diffstat (limited to 'modules/processing.py')
| -rw-r--r--[-rwxr-xr-x] | modules/processing.py | 20 |
1 files changed, 12 insertions, 8 deletions
diff --git a/modules/processing.py b/modules/processing.py index f34ba48a..6d3c9365 100755..100644 --- a/modules/processing.py +++ b/modules/processing.py @@ -394,12 +394,14 @@ class StableDiffusionProcessing: self.main_prompt = self.all_prompts[0]
self.main_negative_prompt = self.all_negative_prompts[0]
- def cached_params(self, required_prompts, steps, extra_network_data):
+ def cached_params(self, required_prompts, steps, hires_steps, extra_network_data, use_old_scheduling):
"""Returns parameters that invalidate the cond cache if changed"""
return (
required_prompts,
steps,
+ hires_steps,
+ use_old_scheduling,
opts.CLIP_stop_at_last_layers,
shared.sd_model.sd_checkpoint_info,
extra_network_data,
@@ -409,7 +411,7 @@ class StableDiffusionProcessing: self.height,
)
- def get_conds_with_caching(self, function, required_prompts, steps, caches, extra_network_data):
+ def get_conds_with_caching(self, function, required_prompts, steps, caches, extra_network_data, hires_steps=None):
"""
Returns the result of calling function(shared.sd_model, required_prompts, steps)
using a cache to store the result if the same arguments have been used before.
@@ -422,7 +424,7 @@ class StableDiffusionProcessing: caches is a list with items described above.
"""
- cached_params = self.cached_params(required_prompts, steps, extra_network_data)
+ cached_params = self.cached_params(required_prompts, steps, hires_steps, extra_network_data, shared.opts.use_old_scheduling)
for cache in caches:
if cache[0] is not None and cached_params == cache[0]:
@@ -431,7 +433,7 @@ class StableDiffusionProcessing: cache = caches[0]
with devices.autocast():
- cache[1] = function(shared.sd_model, required_prompts, steps)
+ cache[1] = function(shared.sd_model, required_prompts, steps, hires_steps, shared.opts.use_old_scheduling)
cache[0] = cached_params
return cache[1]
@@ -443,8 +445,10 @@ class StableDiffusionProcessing: sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
total_steps = sampler_config.total_steps(self.steps) if sampler_config else self.steps
self.step_multiplier = total_steps // self.steps
- self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, total_steps, [self.cached_uc], self.extra_network_data)
- self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data)
+ self.firstpass_steps = total_steps
+
+ self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, total_steps, [self.cached_uc], self.extra_network_data, None)
+ self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, total_steps, [self.cached_c], self.extra_network_data, None )
def get_conds(self):
return self.c, self.uc
@@ -1279,8 +1283,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing): steps = self.hr_second_pass_steps or self.steps
total_steps = sampler_config.total_steps(steps) if sampler_config else steps
- self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, total_steps, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data)
- self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, total_steps, [self.cached_hr_c, self.cached_c], self.hr_extra_network_data)
+ self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, hr_negative_prompts, self.firstpass_steps, [self.cached_hr_uc, self.cached_uc], self.hr_extra_network_data, total_steps)
+ self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, hr_prompts, self.firstpass_steps, [self.cached_hr_c, self.cached_c], self.hr_extra_network_data, total_steps)
def setup_conds(self):
if self.is_hr_pass:
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