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Fix DPM SDE and update IPEX defaults

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Disty0
2023-09-17 16:14:40 +03:00
parent 3389edf6f8
commit e0c8d37d5e
3 changed files with 5 additions and 5 deletions
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modules/intel/ipex/attention.py
+1 -1
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@@ -65,7 +65,7 @@ original_scaled_dot_product_attention = torch.nn.functional.scaled_dot_product_a
def scaled_dot_product_attention(query, key, value, attn_mask=None, dropout_p=0.0, is_causal=False):
#ARC GPUs can't allocate more than 4GB to a single block, Slice it:
shape_one, batch_size_attention, query_tokens, shape_four = query.shape
block_multiply = 2.4 if query.dtype == torch.float32 else 1.2
block_multiply = 3.6 if query.dtype == torch.float32 else 1.8
block_size = (shape_one * batch_size_attention * query_tokens * shape_four) / 1024 * block_multiply #MB
split_slice_size = batch_size_attention
if block_size >= 4000:
modules/processing_diffusers.py
+3 -3
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@@ -283,7 +283,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
recompile_model()
is_karras_compatible = shared.sd_model.__class__.__init__.__annotations__.get("scheduler", None) == diffusers.schedulers.scheduling_utils.KarrasDiffusionSchedulers
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.sampler_name) and (p.sampler_name != 'Default') and is_karras_compatible:
if ((not hasattr(shared.sd_model.scheduler, 'name')) or (p.sampler_name == 'DPM SDE') or (shared.sd_model.scheduler.name != p.sampler_name)) and (p.sampler_name != 'Default') and is_karras_compatible:
sampler = sd_samplers.all_samplers_map.get(p.sampler_name, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
@@ -380,7 +380,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
if latent_scale_mode is not None or p.hr_force:
p.ops.append('hires')
recompile_model(hires=True)
if (not hasattr(shared.sd_model.scheduler, 'name')) or (shared.sd_model.scheduler.name != p.latent_sampler) and (p.latent_sampler != 'Default') and is_karras_compatible:
if ((not hasattr(shared.sd_model.scheduler, 'name')) or (p.latent_sampler == 'DPM SDE') or (shared.sd_model.scheduler.name != p.latent_sampler)) and (p.latent_sampler != 'Default') and is_karras_compatible:
sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
@@ -416,7 +416,7 @@ def process_diffusers(p: StableDiffusionProcessing, seeds, prompts, negative_pro
shared.sd_model.to(devices.cpu)
devices.torch_gc()
if (not hasattr(shared.sd_refiner.scheduler, 'name')) or (shared.sd_refiner.scheduler.name != p.latent_sampler) and (p.latent_sampler != 'Default'):
if ((not hasattr(shared.sd_refiner.scheduler, 'name')) or (p.latent_sampler == 'DPM SDE') or (shared.sd_refiner.scheduler.name != p.latent_sampler)) and (p.latent_sampler != 'Default'):
sampler = sd_samplers.all_samplers_map.get(p.latent_sampler, None)
if sampler is None:
sampler = sd_samplers.all_samplers_map.get("UniPC")
modules/shared.py
+1 -1
View File
@@ -434,7 +434,7 @@ options_templates.update(options_section(('diffusers', "Diffusers Settings"), {
"diffusers_vae_upcast": OptionInfo("default", "VAE upcasting", gr.Radio, lambda: {"choices": ['default', 'true', 'false']}),
"diffusers_vae_slicing": OptionInfo(True, "Enable VAE slicing"),
"diffusers_vae_tiling": OptionInfo(False if cmd_opts.use_openvino else True, "Enable VAE tiling"),
"diffusers_attention_slicing": OptionInfo(False, "Enable attention slicing"),
"diffusers_attention_slicing": OptionInfo(True if devices.backend == "ipex" else False, "Enable attention slicing"),
"diffusers_model_load_variant": OptionInfo("default", "Diffusers model loading variant", gr.Radio, lambda: {"choices": ['default', 'fp32', 'fp16']}),
"diffusers_vae_load_variant": OptionInfo("default", "Diffusers VAE loading variant", gr.Radio, lambda: {"choices": ['default', 'fp32', 'fp16']}),
"diffusers_lora_loader": OptionInfo("diffusers", "Diffusers LoRA loading variant", gr.Radio, lambda: {"choices": ['diffusers', 'sequential apply', 'merge and apply']}),