make the program read Eta and Eta DDIM from generation parameters

modules/generation_parameters_copypaste.py

@@ -293,6 +293,8 @@ infotext_to_setting_name_mapping = [
     ('Model hash', 'sd_model_checkpoint'),
     ('ENSD', 'eta_noise_seed_delta'),
     ('Noise multiplier', 'initial_noise_multiplier'),
+    ('Eta', 'eta_ancestral'),
+    ('Eta DDIM', 'eta_ddim'),
 ]
 
 

modules/processing.py

@@ -455,7 +455,6 @@ def create_infotext(p, all_prompts, all_seeds, all_subseeds, comments=None, iter
         "Seed resize from": (None if p.seed_resize_from_w == 0 or p.seed_resize_from_h == 0 else f"{p.seed_resize_from_w}x{p.seed_resize_from_h}"),
         "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,
-        "Eta": (None if p.sampler is None or p.sampler.eta == p.sampler.default_eta else p.sampler.eta),
         "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,
     }

modules/sd_samplers_compvis.py

@@ -27,7 +27,6 @@ class VanillaStableDiffusionSampler:
         self.step = 0
         self.stop_at = None
         self.eta = None
-        self.default_eta = 0.0
         self.config = None
         self.last_latent = None
 
@@ -102,6 +101,8 @@ class VanillaStableDiffusionSampler:
 
     def initialize(self, p):
         self.eta = p.eta if p.eta is not None else shared.opts.eta_ddim
+        if self.eta != 0.0:
+            p.extra_generation_params["Eta DDIM"] = self.eta
 
         for fieldname in ['p_sample_ddim', 'p_sample_plms']:
             if hasattr(self.sampler, fieldname):

modules/sd_samplers_kdiffusion.py

@@ -2,7 +2,7 @@ from collections import deque
 import torch
 import inspect
 import k_diffusion.sampling
-from modules import prompt_parser, devices, sd_samplers_common, sd_samplers_compvis
+from modules import prompt_parser, devices, sd_samplers_common
 
 from modules.shared import opts, state
 import modules.shared as shared
@@ -164,7 +164,6 @@ class KDiffusionSampler:
         self.sampler_noises = None
         self.stop_at = None
         self.eta = None
-        self.default_eta = 1.0
         self.config = None
         self.last_latent = None
 
@@ -199,7 +198,7 @@ class KDiffusionSampler:
         self.model_wrap_cfg.mask = p.mask if hasattr(p, 'mask') else None
         self.model_wrap_cfg.nmask = p.nmask if hasattr(p, 'nmask') else None
         self.model_wrap_cfg.step = 0
-        self.eta = p.eta or opts.eta_ancestral
+        self.eta = p.eta if p.eta is not None else opts.eta_ancestral
 
         k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
 
@@ -209,6 +208,9 @@ class KDiffusionSampler:
                 extra_params_kwargs[param_name] = getattr(p, param_name)
 
         if 'eta' in inspect.signature(self.func).parameters:
+            if self.eta != 1.0:
+                p.extra_generation_params["Eta"] = self.eta
+
             extra_params_kwargs['eta'] = self.eta
 
         return extra_params_kwargs