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resolve merge issues

This commit is contained in:
AUTOMATIC1111 2023-08-10 17:04:59 +03:00
parent 70a01cd444
commit ac8a5d18d3
3 changed files with 8 additions and 4 deletions
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7
modules/sd_models.py
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@ -640,8 +640,11 @@ def reuse_model_from_already_loaded(sd_model, checkpoint_info, timer):
timer.record("send model to device") timer.record("send model to device")
model_data.set_sd_model(already_loaded) model_data.set_sd_model(already_loaded)
shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256 if not SkipWritingToConfig.skip:
shared.opts.data["sd_model_checkpoint"] = already_loaded.sd_checkpoint_info.title
shared.opts.data["sd_checkpoint_hash"] = already_loaded.sd_checkpoint_info.sha256
print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}") print(f"Using already loaded model {already_loaded.sd_checkpoint_info.title}: done in {timer.summary()}")
return model_data.sd_model return model_data.sd_model
elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit: elif shared.opts.sd_checkpoints_limit > 1 and len(model_data.loaded_sd_models) < shared.opts.sd_checkpoints_limit:

3
modules/sd_samplers_kdiffusion.py
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@ -1,8 +1,7 @@
import torch import torch
import inspect import inspect
import k_diffusion.sampling import k_diffusion.sampling
from modules import sd_samplers_common, sd_samplers_extra from modules import sd_samplers_common, sd_samplers_extra, sd_samplers_cfg_denoiser
from modules.sd_samplers_cfg_denoiser import CFGDenoiser
from modules.shared import opts from modules.shared import opts
import modules.shared as shared import modules.shared as shared

2
modules/shared_options.py
View File

@ -140,6 +140,8 @@ options_templates.update(options_section(('sd', "Stable Diffusion"), {
"upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"), "upcast_attn": OptionInfo(False, "Upcast cross attention layer to float32"),
"randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"), "randn_source": OptionInfo("GPU", "Random number generator source.", gr.Radio, {"choices": ["GPU", "CPU", "NV"]}).info("changes seeds drastically; use CPU to produce the same picture across different videocard vendors; use NV to produce same picture as on NVidia videocards"),
"tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"), "tiling": OptionInfo(False, "Tiling", infotext='Tiling').info("produce a tileable picture"),
"sd_refiner_checkpoint": OptionInfo("None", "Refiner checkpoint", gr.Dropdown, lambda: {"choices": ["None"] + shared_items.list_checkpoint_tiles()}, refresh=shared_items.refresh_checkpoints, infotext="Refiner").info("switch to another model in the middle of generation"),
"sd_refiner_switch_at": OptionInfo(1.0, "Refiner switch at", gr.Slider, {"minimum": 0.01, "maximum": 1.0, "step": 0.01}, infotext='Refiner switch at').info("fraction of sampling steps when the swtch to refiner model should happen; 1=never, 0.5=switch in the middle of generation"),
})) }))
options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), { options_templates.update(options_section(('sdxl', "Stable Diffusion XL"), {