suppress ENSD infotext for samplers that don't use it

5 files changed, 48 insertions, 16 deletions

diff --git a/modules/processing.py b/modules/processing.py
index 94fe2625..15806f78 100644
--- a/modules/processing.py
+++ b/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 ""

diff --git a/modules/sd_samplers.py b/modules/sd_samplers.py
index 4f1bf21d..f22aad8f 100644
--- a/modules/sd_samplers.py
+++ b/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)

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index bc074238..92880caf 100644
--- a/modules/sd_samplers_common.py
+++ b/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

 

diff --git a/modules/sd_samplers_compvis.py b/modules/sd_samplers_compvis.py
index b1ee3be7..bdae8b40 100644
--- a/modules/sd_samplers_compvis.py
+++ b/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):

-        self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim

+        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

 

diff --git a/modules/sd_samplers_kdiffusion.py b/modules/sd_samplers_kdiffusion.py
index 61f23ad7..5455561a 100644
--- a/modules/sd_samplers_kdiffusion.py
+++ b/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'}),

 ]