fix conds caching with extra network
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30bbb8bce3
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@ -32,6 +32,9 @@ class ExtraNetworkParams:
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else:
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self.positional.append(item)
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def __eq__(self, other):
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return self.items == other.items and self.positional == other.positional and self.named == other.named
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class ExtraNetwork:
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def __init__(self, name):
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@ -171,6 +171,7 @@ class StableDiffusionProcessing:
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self.prompts = None
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self.negative_prompts = None
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self.extra_network_data = None
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self.seeds = None
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self.subseeds = None
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@ -311,7 +312,7 @@ class StableDiffusionProcessing:
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self.all_prompts = [shared.prompt_styles.apply_styles_to_prompt(x, self.styles) for x in self.all_prompts]
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self.all_negative_prompts = [shared.prompt_styles.apply_negative_styles_to_prompt(x, self.styles) for x in self.all_negative_prompts]
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def get_conds_with_caching(self, function, required_prompts, steps, cache):
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def get_conds_with_caching(self, function, required_prompts, steps, cache, extra_network_data):
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"""
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Returns the result of calling function(shared.sd_model, required_prompts, steps)
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using a cache to store the result if the same arguments have been used before.
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@ -321,21 +322,21 @@ class StableDiffusionProcessing:
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have been used before. The second element is where the previously
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computed result is stored.
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"""
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if cache[0] is not None and (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info) == cache[0]:
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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]:
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return cache[1]
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with devices.autocast():
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cache[1] = function(shared.sd_model, required_prompts, steps)
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cache[0] = (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info)
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cache[0] = (required_prompts, steps, opts.CLIP_stop_at_last_layers, shared.sd_model.sd_checkpoint_info, extra_network_data)
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return cache[1]
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def setup_conds(self):
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sampler_config = sd_samplers.find_sampler_config(self.sampler_name)
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self.step_multiplier = 2 if sampler_config and sampler_config.options.get("second_order", False) else 1
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self.uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.negative_prompts, self.steps * self.step_multiplier, self.cached_uc)
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self.c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.prompts, self.steps * self.step_multiplier, self.cached_c)
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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)
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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)
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def parse_extra_network_prompts(self):
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self.prompts, extra_network_data = extra_networks.parse_prompts(self.prompts)
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@ -681,7 +682,6 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if state.job_count == -1:
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state.job_count = p.n_iter
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extra_network_data = None
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for n in range(p.n_iter):
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p.iteration = n
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@ -702,11 +702,11 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if len(p.prompts) == 0:
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break
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extra_network_data = p.parse_extra_network_prompts()
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p.extra_network_data = p.parse_extra_network_prompts()
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if not p.disable_extra_networks:
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with devices.autocast():
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extra_networks.activate(p, extra_network_data)
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extra_networks.activate(p, p.extra_network_data)
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if p.scripts is not None:
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p.scripts.process_batch(p, batch_number=n, prompts=p.prompts, seeds=p.seeds, subseeds=p.subseeds)
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@ -828,8 +828,8 @@ def process_images_inner(p: StableDiffusionProcessing) -> Processed:
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if opts.grid_save:
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images.save_image(grid, p.outpath_grids, "grid", p.all_seeds[0], p.all_prompts[0], opts.grid_format, info=infotext(), short_filename=not opts.grid_extended_filename, p=p, grid=True)
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if not p.disable_extra_networks and extra_network_data:
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extra_networks.deactivate(p, extra_network_data)
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if not p.disable_extra_networks and p.extra_network_data:
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extra_networks.deactivate(p, p.extra_network_data)
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devices.torch_gc()
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@ -1101,8 +1101,8 @@ class StableDiffusionProcessingTxt2Img(StableDiffusionProcessing):
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super().setup_conds()
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if self.enable_hr:
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self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.hr_negative_prompts, self.steps * self.step_multiplier, self.cached_uc)
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self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.hr_prompts, self.steps * self.step_multiplier, self.cached_c)
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self.hr_uc = self.get_conds_with_caching(prompt_parser.get_learned_conditioning, self.hr_negative_prompts, self.steps * self.step_multiplier, self.cached_uc, self.hr_extra_network_data)
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self.hr_c = self.get_conds_with_caching(prompt_parser.get_multicond_learned_conditioning, self.hr_prompts, self.steps * self.step_multiplier, self.cached_c, self.hr_extra_network_data)
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def parse_extra_network_prompts(self):
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res = super().parse_extra_network_prompts()
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