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fix samplers config

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Vladimir Mandic
2023-07-05 11:00:29 -04:00
parent 65f036e42a
commit be0bfbcd27
4 changed files with 32 additions and 14 deletions
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modules/sd_models.py
+7 -7
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@@ -582,28 +582,28 @@ def load_diffuser(checkpoint_info=None, already_loaded_state_dict=None, timer=No
prior = diffusers.DiffusionPipeline.from_pretrained(prior_id, **diffusers_load_config)
sd_model = PriorPipeline(prior=prior, main=sd_model) # wrap sd_model
if hasattr(sd_model, "enable_sequential_cpu_offload"):
if shared.cmd_opts.lowvram or shared.opts.diffusers_seq_cpu_offload:
sd_model.enable_sequential_cpu_offload()
shared.log.debug('Diffusers: enable sequenctial CPU offload')
if hasattr(sd_model, "enable_model_cpu_offload"):
if shared.cmd_opts.medvram or shared.opts.diffusers_model_cpu_offload:
shared.log.debug('Diffusers: enable model CPU offload')
sd_model.enable_model_cpu_offload()
if hasattr(sd_model, "enable_sequential_cpu_offload"):
if shared.opts.diffusers_seq_cpu_offload:
sd_model.enable_sequential_cpu_offload()
shared.log.debug('Diffusers: enable sequential CPU offload')
if hasattr(sd_model, "enable_vae_slicing"):
if shared.opts.diffusers_vae_slicing:
if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_slicing:
shared.log.debug('Diffusers: enable VAE slicing')
sd_model.enable_vae_slicing()
else:
sd_model.disable_vae_slicing()
if hasattr(sd_model, "enable_vae_tiling"):
if shared.opts.diffusers_vae_tiling:
if shared.cmd_opts.lowvram or shared.opts.diffusers_vae_tiling:
shared.log.debug('Diffusers: enable VAE tiling')
sd_model.enable_vae_tiling()
else:
sd_model.disable_vae_tiling()
if hasattr(sd_model, "enable_attention_slicing"):
if shared.opts.diffusers_attention_slicing:
if shared.cmd_opts.lowvram or shared.opts.diffusers_attention_slicing:
shared.log.debug('Diffusers: enable attention slicing')
sd_model.enable_attention_slicing()
else:
modules/shared.py
+1 -1
View File
@@ -472,11 +472,11 @@ options_templates.update(options_section(('sampler-params', "Sampler Settings"),
"show_samplers": OptionInfo(["Euler a", "UniPC", "DEIS", "DDIM", "DPM 1S", "DPM 2M", "DPM++ 2M SDE", "DPM++ 2M SDE Karras", "DPM2 Karras", "DPM++ 2M Karras"], "Show samplers in user interface", gr.CheckboxGroup, lambda: {"choices": [x.name for x in list_samplers() if x.name != "PLMS"]}),
"fallback_sampler": OptionInfo("Euler a", "Secondary sampler", gr.Dropdown, lambda: {"choices": ["None"] + [x.name for x in list_samplers()]}),
"force_latent_sampler": OptionInfo("None", "Force latent upscaler sampler", gr.Dropdown, lambda: {"choices": ["None"] + [x.name for x in list_samplers()]}),
"always_batch_cond_uncond": OptionInfo(False, "Disable conditional batching enabled on low memory systems"),
}))
if backend == Backend.ORIGINAL:
options_templates.update(options_section(('sampler-params', "Sampler Settings"), {
"always_batch_cond_uncond": OptionInfo(False, "Disable conditional batching enabled on low memory systems"),
"enable_quantization": OptionInfo(True, "Enable samplers quantization for sharper and cleaner results"),
"eta_ancestral": OptionInfo(1.0, "Noise multiplier for ancestral samplers (eta)", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),
"eta_ddim": OptionInfo(0.0, "Noise multiplier for DDIM (eta)", gr.Slider, {"minimum": 0.0, "maximum": 1.0, "step": 0.01}),