suppress ENSD infotext for samplers that don't use it

modules/processing.py

@@ -13,7 +13,7 @@ from skimage import exposure
 from typing import Any, Dict, List
 
 import modules.sd_hijack
-from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts
+from modules import devices, prompt_parser, masking, sd_samplers, lowvram, generation_parameters_copypaste, extra_networks, sd_vae_approx, scripts, sd_samplers_common
 from modules.sd_hijack import model_hijack
 from modules.shared import opts, cmd_opts, state
 import modules.shared as shared
@@ -480,6 +480,10 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
     clip_skip = getattr(p, 'clip_skip', opts.CLIP_stop_at_last_layers)
     enable_hr = getattr(p, 'enable_hr', False)
 
+    uses_ensd = opts.eta_noise_seed_delta != 0
+    if uses_ensd:
+        uses_ensd = sd_samplers_common.is_sampler_using_eta_noise_seed_delta(p)
+
     generation_params = {
         "Steps": p.steps,
         "Sampler": p.sampler_name,
@@ -496,17 +500,16 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Denoising strength": getattr(p, 'denoising_strength', None),
         "Conditional mask weight": getattr(p, "inpainting_mask_weight", shared.opts.inpainting_mask_weight) if p.is_using_inpainting_conditioning else None,
         "Clip skip": None if clip_skip <= 1 else clip_skip,
-        "ENSD": None if opts.eta_noise_seed_delta == 0 else opts.eta_noise_seed_delta,
+        "ENSD": opts.eta_noise_seed_delta if uses_ensd else None,
         "Token merging ratio": None if opts.token_merging_ratio == 0 else opts.token_merging_ratio,
         "Token merging ratio hr": None if not enable_hr or opts.token_merging_ratio_hr == 0 else opts.token_merging_ratio_hr,
         "Init image hash": getattr(p, 'init_img_hash', None),
         "RNG": opts.randn_source if opts.randn_source != "GPU" else None,
         "NGMS": None if p.s_min_uncond == 0 else p.s_min_uncond,
+        **p.extra_generation_params,
         "Version": program_version() if opts.add_version_to_infotext else None,
     }
 
-    generation_params.update(p.extra_generation_params)
-
     generation_params_text = ", ".join([k if k == v else f'{k}: {generation_parameters_copypaste.quote(v)}' for k, v in generation_params.items() if v is not None])
 
     negative_prompt_text = f"\nNegative prompt: {p.all_negative_prompts[index]}" if p.all_negative_prompts[index] else ""

modules/sd_samplers.py

@@ -14,12 +14,18 @@ samplers_for_img2img = []
 samplers_map = {}
 
 
-def create_sampler(name, model):
+def find_sampler_config(name):
     if name is not None:
         config = all_samplers_map.get(name, None)
     else:
         config = all_samplers[0]
 
+    return config
+
+
+def create_sampler(name, model):
+    config = find_sampler_config(name)
+
     assert config is not None, f'bad sampler name: {name}'
 
     sampler = config.constructor(model)

modules/sd_samplers_common.py

@@ -2,7 +2,7 @@ from collections import namedtuple
 import numpy as np
 import torch
 from PIL import Image
-from modules import devices, processing, images, sd_vae_approx
+from modules import devices, processing, images, sd_vae_approx, sd_samplers
 
 from modules.shared import opts, state
 import modules.shared as shared
@@ -58,6 +58,25 @@ def store_latent(decoded):
             shared.state.assign_current_image(sample_to_image(decoded))
 
 
+def is_sampler_using_eta_noise_seed_delta(p):
+    """returns whether sampler from config will use eta noise seed delta for image creation"""
+
+    sampler_config = sd_samplers.find_sampler_config(p.sampler_name)
+
+    eta = p.eta
+
+    if eta is None and p.sampler is not None:
+        eta = p.sampler.eta
+
+    if eta is None and sampler_config is not None:
+        eta = 0 if sampler_config.options.get("default_eta_is_0", False) else 1.0
+
+    if eta == 0:
+        return False
+
+    return sampler_config.options.get("uses_ensd", False)
+
+
 class InterruptedException(BaseException):
     pass
 

modules/sd_samplers_compvis.py

@@ -11,7 +11,7 @@ import modules.models.diffusion.uni_pc
 
 
 samplers_data_compvis = [
-    sd_samplers_common.SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {}),
+    sd_samplers_common.SamplerData('DDIM', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.ddim.DDIMSampler, model), [], {"default_eta_is_0": True, "uses_ensd": True}),
     sd_samplers_common.SamplerData('PLMS', lambda model: VanillaStableDiffusionSampler(ldm.models.diffusion.plms.PLMSSampler, model), [], {}),
     sd_samplers_common.SamplerData('UniPC', lambda model: VanillaStableDiffusionSampler(modules.models.diffusion.uni_pc.UniPCSampler, model), [], {}),
 ]
@@ -134,7 +134,11 @@ class VanillaStableDiffusionSampler:
         self.update_step(x)
 
     def initialize(self, p):
+        if self.is_ddim:
             self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim
+        else:
+            self.eta = 0.0
+
         if self.eta != 0.0:
             p.extra_generation_params["Eta DDIM"] = self.eta
 

modules/sd_samplers_kdiffusion.py

@@ -11,21 +11,21 @@ from modules.script_callbacks import CFGDenoisedParams, cfg_denoised_callback
 from modules.script_callbacks import AfterCFGCallbackParams, cfg_after_cfg_callback
 
 samplers_k_diffusion = [
-    ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {}),
+    ('Euler a', 'sample_euler_ancestral', ['k_euler_a', 'k_euler_ancestral'], {"uses_ensd": True}),
     ('Euler', 'sample_euler', ['k_euler'], {}),
     ('LMS', 'sample_lms', ['k_lms'], {}),
     ('Heun', 'sample_heun', ['k_heun'], {}),
     ('DPM2', 'sample_dpm_2', ['k_dpm_2'], {'discard_next_to_last_sigma': True}),
-    ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {'discard_next_to_last_sigma': True}),
-    ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {}),
+    ('DPM2 a', 'sample_dpm_2_ancestral', ['k_dpm_2_a'], {'discard_next_to_last_sigma': True, "uses_ensd": True}),
+    ('DPM++ 2S a', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a'], {"uses_ensd": True}),
     ('DPM++ 2M', 'sample_dpmpp_2m', ['k_dpmpp_2m'], {}),
     ('DPM++ SDE', 'sample_dpmpp_sde', ['k_dpmpp_sde'], {}),
-    ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {}),
-    ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {}),
+    ('DPM fast', 'sample_dpm_fast', ['k_dpm_fast'], {"uses_ensd": True}),
+    ('DPM adaptive', 'sample_dpm_adaptive', ['k_dpm_ad'], {"uses_ensd": True}),
     ('LMS Karras', 'sample_lms', ['k_lms_ka'], {'scheduler': 'karras'}),
-    ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True}),
-    ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True}),
-    ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras'}),
+    ('DPM2 Karras', 'sample_dpm_2', ['k_dpm_2_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}),
+    ('DPM2 a Karras', 'sample_dpm_2_ancestral', ['k_dpm_2_a_ka'], {'scheduler': 'karras', 'discard_next_to_last_sigma': True, "uses_ensd": True}),
+    ('DPM++ 2S a Karras', 'sample_dpmpp_2s_ancestral', ['k_dpmpp_2s_a_ka'], {'scheduler': 'karras', "uses_ensd": True}),
     ('DPM++ 2M Karras', 'sample_dpmpp_2m', ['k_dpmpp_2m_ka'], {'scheduler': 'karras'}),
     ('DPM++ SDE Karras', 'sample_dpmpp_sde', ['k_dpmpp_sde_ka'], {'scheduler': 'karras'}),
 ]