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Merge pull request #11757 from AUTOMATIC1111/sdxl

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SD XL support
This commit is contained in:
AUTOMATIC1111
2023-07-16 12:04:53 +03:00
committed by GitHub
parent 9d3dd64fe9 14cf434bc3
commit 0198eaec45
22 changed files with 586 additions and 113 deletions
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27
modules/processing.py
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@@ -330,8 +330,21 @@ class StableDiffusionProcessing:
caches is a list with items described above.
"""
cached_params = (
required_prompts,
steps,
opts.CLIP_stop_at_last_layers,
shared.sd_model.sd_checkpoint_info,
extra_network_data,
opts.sdxl_crop_left,
opts.sdxl_crop_top,
self.width,
self.height,
)
for cache in caches:
if cache[0] is not None and (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info, extra_network_data) == cache[0]:
if cache[0] is not None and cached_params == cache[0]:
return cache[1]
cache = caches[0]
@@ -339,14 +352,17 @@ class StableDiffusionProcessing:
with devices.autocast():
cache[1] = function(shared.sd_model, required_prompts, steps)
cache[0] = (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info, extra_network_data)
cache[0] = cached_params
return cache[1]
def setup_conds(self):
prompts = prompt_parser.SdConditioning(self.prompts, width=self.width, height=self.height)
negative_prompts = prompt_parser.SdConditioning(self.negative_prompts, width=self.width, height=self.height, is_negative_prompt=True)
sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.negative_prompts, self.steps * self.step_multiplier, [self.cached_uc], self.extra_network_data)
self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.prompts, self.steps * self.step_multiplier, [self.cached_c], self.extra_network_data)
self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, negative_prompts, self.steps * self.step_multiplier, [self.cached_uc], self.extra_network_data)
self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, prompts, self.steps * self.step_multiplier, [self.cached_c], self.extra_network_data)
def parse_extra_network_prompts(self):
self.prompts, self.extra_network_data = extra_networks.parse_prompts(self.prompts)
@@ -523,8 +539,7 @@ def create_random_tensors(shape, seeds, subseeds=None, subseed_strength=0.0, see
def decode_first_stage(model, x):
with devices.autocast(disable=x.dtype == devices.dtype_vae):
x = model.decode_first_stage(x)
x = model.decode_first_stage(x.to(devices.dtype_vae))
return x