From fca42949a3593c5a2f646e30cc99be2c02566aa2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Thu, 3 Aug 2023 07:18:55 +0300
Subject: rework torchsde._brownian.brownian_interval replacement to use
 device.randn_local and respect the NV setting.

---
 modules/sd_samplers_common.py | 12 ++++++------
 1 file changed, 6 insertions(+), 6 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 763829f1..5deda761 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -2,10 +2,8 @@ from collections import namedtuple
 import numpy as np
 import torch
 from PIL import Image
-from modules import devices, processing, images, sd_vae_approx, sd_samplers, sd_vae_taesd
-
+from modules import devices, processing, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared
 from modules.shared import opts, state
-import modules.shared as shared
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
 
@@ -85,11 +83,13 @@ class InterruptedException(BaseException):
     pass
 
 
-if opts.randn_source == "CPU":
+def replace_torchsde_browinan():
     import torchsde._brownian.brownian_interval
 
     def torchsde_randn(size, dtype, device, seed):
-        generator = torch.Generator(devices.cpu).manual_seed(int(seed))
-        return torch.randn(size, dtype=dtype, device=devices.cpu, generator=generator).to(device)
+        return devices.randn_local(seed, size).to(device=device, dtype=dtype)
 
     torchsde._brownian.brownian_interval._randn = torchsde_randn
+
+
+replace_torchsde_browinan()
-- 
cgit v1.2.3


From 75336dfc84cae280036bc52a6805eb10d9ae30ba Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 13:38:52 +0800
Subject: add TAESD for i2i and t2i

---
 modules/sd_samplers_common.py | 38 +++++++++++++++++++++++++++++++++-----
 1 file changed, 33 insertions(+), 5 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 5deda761..5a45e8eb 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -23,19 +23,29 @@ def setup_img2img_steps(p, steps=None):
 approximation_indexes = {"Full": 0, "Approx NN": 1, "Approx cheap": 2, "TAESD": 3}
 
 
-def single_sample_to_image(sample, approximation=None):
+def samples_to_images_tensor(sample, approximation=None, model=None):
+    '''latents -> images [-1, 1]'''
     if approximation is None:
         approximation = approximation_indexes.get(opts.show_progress_type, 0)
 
     if approximation == 2:
-        x_sample = sd_vae_approx.cheap_approximation(sample) * 0.5 + 0.5
+        x_sample = sd_vae_approx.cheap_approximation(sample)
     elif approximation == 1:
-        x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach() * 0.5 + 0.5
+        x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype)).detach()
     elif approximation == 3:
         x_sample = sample * 1.5
-        x_sample = sd_vae_taesd.model()(x_sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach()
+        x_sample = sd_vae_taesd.decoder_model()(x_sample.to(devices.device, devices.dtype)).detach()
+        x_sample = x_sample * 2 - 1
     else:
-        x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] * 0.5 + 0.5
+        if model is None:
+            model = shared.sd_model
+        x_sample = model.decode_first_stage(sample)
+    
+    return x_sample
+
+
+def single_sample_to_image(sample, approximation=None):
+    x_sample = samples_to_images_tensor(sample.unsqueeze(0), approximation)[0] * 0.5 + 0.5
 
     x_sample = torch.clamp(x_sample, min=0.0, max=1.0)
     x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
@@ -52,6 +62,24 @@ def samples_to_image_grid(samples, approximation=None):
     return images.image_grid([single_sample_to_image(sample, approximation) for sample in samples])
 
 
+def images_tensor_to_samples(image, approximation=None, model=None):
+    '''image[0, 1] -> latent'''
+    if approximation is None:
+        approximation = approximation_indexes.get(opts.sd_vae_encode_method, 0)
+
+    if approximation == 3:
+        image = image.to(devices.device, devices.dtype)
+        x_latent = sd_vae_taesd.encoder_model()(image) / 1.5
+    else:
+        if model is None:
+            model = shared.sd_model
+        image = image.to(shared.device, dtype=devices.dtype_vae)
+        image = image * 2 - 1
+        x_latent = model.get_first_stage_encoding(model.encode_first_stage(image))
+
+    return x_latent
+
+
 def store_latent(decoded):
     state.current_latent = decoded
 
-- 
cgit v1.2.3


From c134a480164bef017cd4b33fae57a31a86556beb Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 13:40:20 +0800
Subject: Fix code style

---
 modules/sd_samplers_common.py | 4 ++--
 1 file changed, 2 insertions(+), 2 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 5a45e8eb..d444cac1 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, sd_samplers, sd_vae_taesd, shared
+from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared
 from modules.shared import opts, state
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
@@ -40,7 +40,7 @@ def samples_to_images_tensor(sample, approximation=None, model=None):
         if model is None:
             model = shared.sd_model
         x_sample = model.decode_first_stage(sample)
-    
+
     return x_sample
 
 
-- 
cgit v1.2.3


From f0c1063a707a4a43823b0ed00e2a8eeb22a9ed0a Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Fri, 4 Aug 2023 09:09:09 +0300
Subject: resolve some of circular import issues for kohaku

---
 modules/sd_samplers_common.py | 10 ++++++++--
 1 file changed, 8 insertions(+), 2 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 5deda761..b3d344e7 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, sd_samplers, sd_vae_taesd, shared
+from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared
 from modules.shared import opts, state
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
@@ -35,7 +35,7 @@ def single_sample_to_image(sample, approximation=None):
         x_sample = sample * 1.5
         x_sample = sd_vae_taesd.model()(x_sample.to(devices.device, devices.dtype).unsqueeze(0))[0].detach()
     else:
-        x_sample = processing.decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] * 0.5 + 0.5
+        x_sample = decode_first_stage(shared.sd_model, sample.unsqueeze(0))[0] * 0.5 + 0.5
 
     x_sample = torch.clamp(x_sample, min=0.0, max=1.0)
     x_sample = 255. * np.moveaxis(x_sample.cpu().numpy(), 0, 2)
@@ -44,6 +44,12 @@ def single_sample_to_image(sample, approximation=None):
     return Image.fromarray(x_sample)
 
 
+def decode_first_stage(model, x):
+    x = model.decode_first_stage(x.to(devices.dtype_vae))
+
+    return x
+
+
 def sample_to_image(samples, index=0, approximation=None):
     return single_sample_to_image(samples[index], approximation)
 
-- 
cgit v1.2.3


From 1f6bfdea80f58f292aeebb9a001689a118d71c01 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 14:38:52 +0800
Subject: move the modified decode into smapler_common

---
 modules/sd_samplers_common.py | 6 +++---
 1 file changed, 3 insertions(+), 3 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 2cfa4ac6..7269514f 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -55,9 +55,9 @@ def single_sample_to_image(sample, approximation=None):
 
 
 def decode_first_stage(model, x):
-    x = model.decode_first_stage(x.to(devices.dtype_vae))
-
-    return x
+    x = x.to(devices.dtype_vae)
+    approx_index = approximation_indexes.get(opts.sd_vae_decode_method, 0)
+    return samples_to_images_tensor(x, approx_index, model)
 
 
 def sample_to_image(samples, index=0, approximation=None):
-- 
cgit v1.2.3


From 094c416a801b16c7d8e1944e2e9fae2c9e98bf12 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 17:53:16 +0800
Subject: change all encode

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 7269514f..42a29fc9 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -75,7 +75,7 @@ def images_tensor_to_samples(image, approximation=None, model=None):
 
     if approximation == 3:
         image = image.to(devices.device, devices.dtype)
-        x_latent = sd_vae_taesd.encoder_model()(image) / 1.5
+        x_latent = sd_vae_taesd.encoder_model()(image)
     else:
         if model is None:
             model = shared.sd_model
-- 
cgit v1.2.3


From 6346d8eeaa17ba0f7e41618908519f6e9bfe07e0 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 17:53:30 +0800
Subject: Revert "change all encode"

This reverts commit 094c416a801b16c7d8e1944e2e9fae2c9e98bf12.
---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 42a29fc9..7269514f 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -75,7 +75,7 @@ def images_tensor_to_samples(image, approximation=None, model=None):
 
     if approximation == 3:
         image = image.to(devices.device, devices.dtype)
-        x_latent = sd_vae_taesd.encoder_model()(image)
+        x_latent = sd_vae_taesd.encoder_model()(image) / 1.5
     else:
         if model is None:
             model = shared.sd_model
-- 
cgit v1.2.3


From 073342c8878adc208be1eaab2705ba865d7b3ea1 Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Fri, 4 Aug 2023 17:55:52 +0800
Subject: remove noneed scale

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 7269514f..42a29fc9 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -75,7 +75,7 @@ def images_tensor_to_samples(image, approximation=None, model=None):
 
     if approximation == 3:
         image = image.to(devices.device, devices.dtype)
-        x_latent = sd_vae_taesd.encoder_model()(image) / 1.5
+        x_latent = sd_vae_taesd.encoder_model()(image)
     else:
         if model is None:
             model = shared.sd_model
-- 
cgit v1.2.3


From aa42c0ff8e51c1dde50a313aa2c12b357b287b50 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 6 Aug 2023 07:41:17 +0300
Subject: repair broken live previews if using VAE with half

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 42a29fc9..39586b40 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -39,7 +39,7 @@ def samples_to_images_tensor(sample, approximation=None, model=None):
     else:
         if model is None:
             model = shared.sd_model
-        x_sample = model.decode_first_stage(sample)
+        x_sample = model.decode_first_stage(sample.to(model.first_stage_model.dtype))
 
     return x_sample
 
-- 
cgit v1.2.3


From f1975b0213f5be400889ec04b3891d1cb571fe20 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 6 Aug 2023 17:01:07 +0300
Subject: initial refiner support

---
 modules/sd_samplers_common.py | 19 ++++++++++++++++++-
 1 file changed, 18 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 39586b40..3f3e83e3 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, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared
+from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared, sd_models
 from modules.shared import opts, state
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
@@ -127,3 +127,20 @@ def replace_torchsde_browinan():
 
 
 replace_torchsde_browinan()
+
+
+def apply_refiner(sampler):
+    completed_ratio = sampler.step / sampler.steps
+    if completed_ratio > shared.opts.sd_refiner_switch_at and shared.sd_model.sd_checkpoint_info.title != shared.opts.sd_refiner_checkpoint:
+        refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint)
+        if refiner_checkpoint_info is None:
+            raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}')
+
+        with sd_models.SkipWritingToConfig():
+            sd_models.reload_model_weights(info=refiner_checkpoint_info)
+
+        devices.torch_gc()
+
+        sampler.update_inner_model()
+
+        sampler.p.setup_conds()
-- 
cgit v1.2.3


From 5a0db84b6c7322082c7532df11a29a95a59a612b Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 6 Aug 2023 17:53:33 +0300
Subject: add infotext add proper support for recalculating conds in
 k-diffusion samplers remove support for compvis samplers

---
 modules/sd_samplers_common.py | 29 ++++++++++++++++++++---------
 1 file changed, 20 insertions(+), 9 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 3f3e83e3..92bf0ca1 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -131,16 +131,27 @@ replace_torchsde_browinan()
 
 def apply_refiner(sampler):
     completed_ratio = sampler.step / sampler.steps
-    if completed_ratio > shared.opts.sd_refiner_switch_at and shared.sd_model.sd_checkpoint_info.title != shared.opts.sd_refiner_checkpoint:
-        refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint)
-        if refiner_checkpoint_info is None:
-            raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}')
 
-        with sd_models.SkipWritingToConfig():
-            sd_models.reload_model_weights(info=refiner_checkpoint_info)
+    if completed_ratio <= shared.opts.sd_refiner_switch_at:
+        return False
+
+    if shared.sd_model.sd_checkpoint_info.title == shared.opts.sd_refiner_checkpoint:
+        return False
+
+    refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint)
+    if refiner_checkpoint_info is None:
+        raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}')
+
+    sampler.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
+    sampler.p.extra_generation_params['Refiner switch at'] = shared.opts.sd_refiner_switch_at
+
+    with sd_models.SkipWritingToConfig():
+        sd_models.reload_model_weights(info=refiner_checkpoint_info)
+
+    devices.torch_gc()
+    sampler.p.setup_conds()
+    sampler.update_inner_model()
 
-        devices.torch_gc()
+    return True
 
-        sampler.update_inner_model()
 
-        sampler.p.setup_conds()
-- 
cgit v1.2.3


From 8285a149d8c488ae6c7a566eb85fb5e825145464 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Tue, 8 Aug 2023 19:20:11 +0300
Subject: add CFG denoiser implementation for DDIM, PLMS and UniPC (this is the
 commit when you can run both old and new implementations to compare them)

---
 modules/sd_samplers_common.py | 140 +++++++++++++++++++++++++++++++++++++++++-
 1 file changed, 139 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 39586b40..adda963b 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -1,9 +1,11 @@
-from collections import namedtuple
+import inspect
+from collections import namedtuple, deque
 import numpy as np
 import torch
 from PIL import Image
 from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, shared
 from modules.shared import opts, state
+import k_diffusion.sampling
 
 SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
 
@@ -127,3 +129,139 @@ def replace_torchsde_browinan():
 
 
 replace_torchsde_browinan()
+
+
+class TorchHijack:
+    def __init__(self, sampler_noises):
+        # Using a deque to efficiently receive the sampler_noises in the same order as the previous index-based
+        # implementation.
+        self.sampler_noises = deque(sampler_noises)
+
+    def __getattr__(self, item):
+        if item == 'randn_like':
+            return self.randn_like
+
+        if hasattr(torch, item):
+            return getattr(torch, item)
+
+        raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'")
+
+    def randn_like(self, x):
+        if self.sampler_noises:
+            noise = self.sampler_noises.popleft()
+            if noise.shape == x.shape:
+                return noise
+
+        return devices.randn_like(x)
+
+
+class Sampler:
+    def __init__(self, funcname):
+        self.funcname = funcname
+        self.func = funcname
+        self.extra_params = []
+        self.sampler_noises = None
+        self.stop_at = None
+        self.eta = None
+        self.config = None  # set by the function calling the constructor
+        self.last_latent = None
+        self.s_min_uncond = None
+        self.s_churn = 0.0
+        self.s_tmin = 0.0
+        self.s_tmax = float('inf')
+        self.s_noise = 1.0
+
+        self.eta_option_field = 'eta_ancestral'
+        self.eta_infotext_field = 'Eta'
+
+        self.conditioning_key = shared.sd_model.model.conditioning_key
+
+        self.model_wrap = None
+        self.model_wrap_cfg = None
+
+    def callback_state(self, d):
+        step = d['i']
+
+        if self.stop_at is not None and step > self.stop_at:
+            raise InterruptedException
+
+        state.sampling_step = step
+        shared.total_tqdm.update()
+
+    def launch_sampling(self, steps, func):
+        state.sampling_steps = steps
+        state.sampling_step = 0
+
+        try:
+            return func()
+        except RecursionError:
+            print(
+                'Encountered RecursionError during sampling, returning last latent. '
+                'rho >5 with a polyexponential scheduler may cause this error. '
+                'You should try to use a smaller rho value instead.'
+            )
+            return self.last_latent
+        except InterruptedException:
+            return self.last_latent
+
+    def number_of_needed_noises(self, p):
+        return p.steps
+
+    def initialize(self, p) -> dict:
+        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.model_wrap_cfg.image_cfg_scale = getattr(p, 'image_cfg_scale', None)
+        self.eta = p.eta if p.eta is not None else getattr(opts, self.eta_option_field, 0.0)
+        self.s_min_uncond = getattr(p, 's_min_uncond', 0.0)
+
+        k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
+
+        extra_params_kwargs = {}
+        for param_name in self.extra_params:
+            if hasattr(p, param_name) and param_name in inspect.signature(self.func).parameters:
+                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[self.eta_infotext_field] = self.eta
+
+            extra_params_kwargs['eta'] = self.eta
+
+        if len(self.extra_params) > 0:
+            s_churn = getattr(opts, 's_churn', p.s_churn)
+            s_tmin = getattr(opts, 's_tmin', p.s_tmin)
+            s_tmax = getattr(opts, 's_tmax', p.s_tmax) or self.s_tmax # 0 = inf
+            s_noise = getattr(opts, 's_noise', p.s_noise)
+
+            if s_churn != self.s_churn:
+                extra_params_kwargs['s_churn'] = s_churn
+                p.s_churn = s_churn
+                p.extra_generation_params['Sigma churn'] = s_churn
+            if s_tmin != self.s_tmin:
+                extra_params_kwargs['s_tmin'] = s_tmin
+                p.s_tmin = s_tmin
+                p.extra_generation_params['Sigma tmin'] = s_tmin
+            if s_tmax != self.s_tmax:
+                extra_params_kwargs['s_tmax'] = s_tmax
+                p.s_tmax = s_tmax
+                p.extra_generation_params['Sigma tmax'] = s_tmax
+            if s_noise != self.s_noise:
+                extra_params_kwargs['s_noise'] = s_noise
+                p.s_noise = s_noise
+                p.extra_generation_params['Sigma noise'] = s_noise
+
+        return extra_params_kwargs
+
+    def create_noise_sampler(self, x, sigmas, p):
+        """For DPM++ SDE: manually create noise sampler to enable deterministic results across different batch sizes"""
+        if shared.opts.no_dpmpp_sde_batch_determinism:
+            return None
+
+        from k_diffusion.sampling import BrownianTreeNoiseSampler
+        sigma_min, sigma_max = sigmas[sigmas > 0].min(), sigmas.max()
+        current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
+        return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)
+
+
+
-- 
cgit v1.2.3


From f8ff8c0638997fd0aef217db1505598846f14782 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Tue, 8 Aug 2023 22:09:40 +0300
Subject: merge errors

---
 modules/sd_samplers_common.py | 6 +++++-
 1 file changed, 5 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 15f27970..fa3614ff 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -202,8 +202,9 @@ class Sampler:
 
         self.conditioning_key = shared.sd_model.model.conditioning_key
 
-        self.model_wrap = None
+        self.p = None
         self.model_wrap_cfg = None
+        self.sampler_extra_args = None
 
     def callback_state(self, d):
         step = d['i']
@@ -215,6 +216,7 @@ class Sampler:
         shared.total_tqdm.update()
 
     def launch_sampling(self, steps, func):
+        self.model_wrap_cfg.steps = steps
         state.sampling_steps = steps
         state.sampling_step = 0
 
@@ -234,6 +236,8 @@ class Sampler:
         return p.steps
 
     def initialize(self, p) -> dict:
+        self.p = p
+        self.model_wrap_cfg.p = p
         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
-- 
cgit v1.2.3


From 1aefb5025929818b2a96cbb6148fcc2db7b947ec Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Tue, 8 Aug 2023 22:17:25 +0300
Subject: add None refiner option

---
 modules/sd_samplers_common.py | 3 +++
 1 file changed, 3 insertions(+)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index fa3614ff..b6ad6830 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -137,6 +137,9 @@ def apply_refiner(sampler):
     if completed_ratio <= shared.opts.sd_refiner_switch_at:
         return False
 
+    if shared.opts.sd_refiner_checkpoint == "None":
+        return False
+
     if shared.sd_model.sd_checkpoint_info.title == shared.opts.sd_refiner_checkpoint:
         return False
 
-- 
cgit v1.2.3


From 0d5dc9a6e7f6362e423a06bf0e75dd5854025394 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Wed, 9 Aug 2023 08:43:31 +0300
Subject: rework RNG to use generators instead of generating noises beforehand

---
 modules/sd_samplers_common.py | 24 ++++++++++++------------
 1 file changed, 12 insertions(+), 12 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index adda963b..97bc0804 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -1,5 +1,5 @@
 import inspect
-from collections import namedtuple, deque
+from collections import namedtuple
 import numpy as np
 import torch
 from PIL import Image
@@ -132,10 +132,15 @@ replace_torchsde_browinan()
 
 
 class TorchHijack:
-    def __init__(self, sampler_noises):
-        # Using a deque to efficiently receive the sampler_noises in the same order as the previous index-based
-        # implementation.
-        self.sampler_noises = deque(sampler_noises)
+    """This is here to replace torch.randn_like of k-diffusion.
+
+    k-diffusion has random_sampler argument for most samplers, but not for all, so
+    this is needed to properly replace every use of torch.randn_like.
+
+    We need to replace to make images generated in batches to be same as images generated individually."""
+
+    def __init__(self, p):
+        self.rng = p.rng
 
     def __getattr__(self, item):
         if item == 'randn_like':
@@ -147,12 +152,7 @@ class TorchHijack:
         raise AttributeError(f"'{type(self).__name__}' object has no attribute '{item}'")
 
     def randn_like(self, x):
-        if self.sampler_noises:
-            noise = self.sampler_noises.popleft()
-            if noise.shape == x.shape:
-                return noise
-
-        return devices.randn_like(x)
+        return self.rng.next()
 
 
 class Sampler:
@@ -215,7 +215,7 @@ class Sampler:
         self.eta = p.eta if p.eta is not None else getattr(opts, self.eta_option_field, 0.0)
         self.s_min_uncond = getattr(p, 's_min_uncond', 0.0)
 
-        k_diffusion.sampling.torch = TorchHijack(self.sampler_noises if self.sampler_noises is not None else [])
+        k_diffusion.sampling.torch = TorchHijack(p)
 
         extra_params_kwargs = {}
         for param_name in self.extra_params:
-- 
cgit v1.2.3


From 64311faa6848d641cc452115e4e1eb47d2a7b519 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sat, 12 Aug 2023 12:39:59 +0300
Subject: put refiner into main UI, into the new accordions section add VAE
 from main model into infotext, not from refiner model option to make scripts
 UI without gr.Group fix inconsistencies with refiner when usings samplers
 that do more denoising than steps

---
 modules/sd_samplers_common.py | 40 +++++++++++++++++++++++-----------------
 1 file changed, 23 insertions(+), 17 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 35c4d657..85f3c7e0 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -7,7 +7,16 @@ from modules import devices, images, sd_vae_approx, sd_samplers, sd_vae_taesd, s
 from modules.shared import opts, state
 import k_diffusion.sampling
 
-SamplerData = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
+
+SamplerDataTuple = namedtuple('SamplerData', ['name', 'constructor', 'aliases', 'options'])
+
+
+class SamplerData(SamplerDataTuple):
+    def total_steps(self, steps):
+        if self.options.get("second_order", False):
+            steps = steps * 2
+
+        return steps
 
 
 def setup_img2img_steps(p, steps=None):
@@ -131,31 +140,26 @@ def replace_torchsde_browinan():
 replace_torchsde_browinan()
 
 
-def apply_refiner(sampler):
-    completed_ratio = sampler.step / sampler.steps
+def apply_refiner(cfg_denoiser):
+    completed_ratio = cfg_denoiser.step / cfg_denoiser.total_steps
+    refiner_switch_at = cfg_denoiser.p.refiner_switch_at
+    refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
 
-    if completed_ratio <= shared.opts.sd_refiner_switch_at:
+    if refiner_switch_at is not None and completed_ratio <= refiner_switch_at:
         return False
 
-    if shared.opts.sd_refiner_checkpoint == "None":
+    if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
         return False
 
-    if shared.sd_model.sd_checkpoint_info.title == shared.opts.sd_refiner_checkpoint:
-        return False
-
-    refiner_checkpoint_info = sd_models.get_closet_checkpoint_match(shared.opts.sd_refiner_checkpoint)
-    if refiner_checkpoint_info is None:
-        raise Exception(f'Could not find checkpoint with name {shared.opts.sd_refiner_checkpoint}')
-
-    sampler.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
-    sampler.p.extra_generation_params['Refiner switch at'] = shared.opts.sd_refiner_switch_at
+    cfg_denoiser.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
+    cfg_denoiser.p.extra_generation_params['Refiner switch at'] = refiner_switch_at
 
     with sd_models.SkipWritingToConfig():
         sd_models.reload_model_weights(info=refiner_checkpoint_info)
 
     devices.torch_gc()
-    sampler.p.setup_conds()
-    sampler.update_inner_model()
+    cfg_denoiser.p.setup_conds()
+    cfg_denoiser.update_inner_model()
 
     return True
 
@@ -192,7 +196,7 @@ class Sampler:
         self.sampler_noises = None
         self.stop_at = None
         self.eta = None
-        self.config = None  # set by the function calling the constructor
+        self.config: SamplerData = None  # set by the function calling the constructor
         self.last_latent = None
         self.s_min_uncond = None
         self.s_churn = 0.0
@@ -208,6 +212,7 @@ class Sampler:
         self.p = None
         self.model_wrap_cfg = None
         self.sampler_extra_args = None
+        self.options = {}
 
     def callback_state(self, d):
         step = d['i']
@@ -220,6 +225,7 @@ class Sampler:
 
     def launch_sampling(self, steps, func):
         self.model_wrap_cfg.steps = steps
+        self.model_wrap_cfg.total_steps = self.config.total_steps(steps)
         state.sampling_steps = steps
         state.sampling_step = 0
 
-- 
cgit v1.2.3


From b293ed30610c040e621e1840d63047ae298f0650 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sat, 12 Aug 2023 12:54:32 +0300
Subject: make it possible to use hires fix together with refiner

---
 modules/sd_samplers_common.py | 3 +++
 1 file changed, 3 insertions(+)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 85f3c7e0..40c7aae0 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -151,6 +151,9 @@ def apply_refiner(cfg_denoiser):
     if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
         return False
 
+    if getattr(cfg_denoiser.p, "enable_hr", False) and not cfg_denoiser.p.is_hr_pass:
+        return False
+
     cfg_denoiser.p.extra_generation_params['Refiner'] = refiner_checkpoint_info.short_title
     cfg_denoiser.p.extra_generation_params['Refiner switch at'] = refiner_switch_at
 
-- 
cgit v1.2.3


From fa9370b7411166c19e8e386400dc4e6082f47b2d Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 06:07:30 +0300
Subject: add refiner to StableDiffusionProcessing class write out correct
 model name in infotext, rather than the refiner model

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 40c7aae0..380cdd5f 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -145,7 +145,7 @@ def apply_refiner(cfg_denoiser):
     refiner_switch_at = cfg_denoiser.p.refiner_switch_at
     refiner_checkpoint_info = cfg_denoiser.p.refiner_checkpoint_info
 
-    if refiner_switch_at is not None and completed_ratio <= refiner_switch_at:
+    if refiner_switch_at is not None and completed_ratio < refiner_switch_at:
         return False
 
     if refiner_checkpoint_info is None or shared.sd_model.sd_checkpoint_info == refiner_checkpoint_info:
-- 
cgit v1.2.3


From 599f61a1e0bddf463dd3c6adb84509b3d9db1941 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Sun, 13 Aug 2023 08:24:16 +0300
Subject: use dataclass for StableDiffusionProcessing

---
 modules/sd_samplers_common.py | 5 ++++-
 1 file changed, 4 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 380cdd5f..09d1e11e 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -305,5 +305,8 @@ class Sampler:
         current_iter_seeds = p.all_seeds[p.iteration * p.batch_size:(p.iteration + 1) * p.batch_size]
         return BrownianTreeNoiseSampler(x, sigma_min, sigma_max, seed=current_iter_seeds)
 
+    def sample(self, p, x, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
+        raise NotImplementedError()
 
-
+    def sample_img2img(self, p, x, noise, conditioning, unconditional_conditioning, steps=None, image_conditioning=None):
+        raise NotImplementedError()
-- 
cgit v1.2.3


From 822597db49218de17e105e62075096284dfcfd41 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 04:16:48 -0400
Subject: Encode batches separately

Significantly reduces VRAM.
This makes encoding more inline with how decoding currently functions.
---
 modules/sd_samplers_common.py | 10 +++++++++-
 1 file changed, 9 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 09d1e11e..f9d034ca 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -92,7 +92,15 @@ def images_tensor_to_samples(image, approximation=None, model=None):
             model = shared.sd_model
         image = image.to(shared.device, dtype=devices.dtype_vae)
         image = image * 2 - 1
-        x_latent = model.get_first_stage_encoding(model.encode_first_stage(image))
+        if len(image) > 1:
+            x_latent = torch.stack([
+                model.get_first_stage_encoding(
+                    model.encode_first_stage(torch.unsqueeze(img, 0))
+                )[0]
+                for img in image
+            ])
+        else:
+            x_latent = model.get_first_stage_encoding(model.encode_first_stage(image))
 
     return x_latent
 
-- 
cgit v1.2.3


From d1a70c3f0534b88665d55bdac1e6b48a63f7f035 Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Sun, 13 Aug 2023 08:22:24 -0400
Subject: Add s_noise param to more samplers

---
 modules/sd_samplers_common.py | 8 ++++----
 1 file changed, 4 insertions(+), 4 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 09d1e11e..d2fb21f4 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -276,19 +276,19 @@ class Sampler:
             s_tmax = getattr(opts, 's_tmax', p.s_tmax) or self.s_tmax # 0 = inf
             s_noise = getattr(opts, 's_noise', p.s_noise)
 
-            if s_churn != self.s_churn:
+            if 's_churn' in extra_params_kwargs and s_churn != self.s_churn:
                 extra_params_kwargs['s_churn'] = s_churn
                 p.s_churn = s_churn
                 p.extra_generation_params['Sigma churn'] = s_churn
-            if s_tmin != self.s_tmin:
+            if 's_tmin' in extra_params_kwargs and s_tmin != self.s_tmin:
                 extra_params_kwargs['s_tmin'] = s_tmin
                 p.s_tmin = s_tmin
                 p.extra_generation_params['Sigma tmin'] = s_tmin
-            if s_tmax != self.s_tmax:
+            if 's_tmax' in extra_params_kwargs and s_tmax != self.s_tmax:
                 extra_params_kwargs['s_tmax'] = s_tmax
                 p.s_tmax = s_tmax
                 p.extra_generation_params['Sigma tmax'] = s_tmax
-            if s_noise != self.s_noise:
+            if 's_noise' in extra_params_kwargs and s_noise != self.s_noise:
                 extra_params_kwargs['s_noise'] = s_noise
                 p.s_noise = s_noise
                 p.extra_generation_params['Sigma noise'] = s_noise
-- 
cgit v1.2.3


From 45be87afc6b173ebda94f427b8d396a2842ddf3c Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Mon, 14 Aug 2023 21:48:05 +0300
Subject: correctly add Eta DDIM to infotext when it's 1.0 and do not add it
 when it's 0.0.

---
 modules/sd_samplers_common.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 07fc4434..8886de7e 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -217,6 +217,7 @@ class Sampler:
 
         self.eta_option_field = 'eta_ancestral'
         self.eta_infotext_field = 'Eta'
+        self.eta_default = 1.0
 
         self.conditioning_key = shared.sd_model.model.conditioning_key
 
@@ -273,7 +274,7 @@ class Sampler:
                 extra_params_kwargs[param_name] = getattr(p, param_name)
 
         if 'eta' in inspect.signature(self.func).parameters:
-            if self.eta != 1.0:
+            if self.eta != self.eta_default:
                 p.extra_generation_params[self.eta_infotext_field] = self.eta
 
             extra_params_kwargs['eta'] = self.eta
-- 
cgit v1.2.3


From d9ddc5d4cd9e707c018d245572310ca6f6cdf1ef Mon Sep 17 00:00:00 2001
From: Kohaku-Blueleaf <59680068+KohakuBlueleaf@users.noreply.github.com>
Date: Wed, 16 Aug 2023 11:21:12 +0800
Subject: Remove wrong scale

---
 modules/sd_samplers_common.py | 3 +--
 1 file changed, 1 insertion(+), 2 deletions(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 8886de7e..7dc79ea8 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -44,8 +44,7 @@ def samples_to_images_tensor(sample, approximation=None, model=None):
     elif approximation == 1:
         x_sample = sd_vae_approx.model()(sample.to(devices.device, devices.dtype)).detach()
     elif approximation == 3:
-        x_sample = sample * 1.5
-        x_sample = sd_vae_taesd.decoder_model()(x_sample.to(devices.device, devices.dtype)).detach()
+        x_sample = sd_vae_taesd.decoder_model()(sample.to(devices.device, devices.dtype)).detach()
         x_sample = x_sample * 2 - 1
     else:
         if model is None:
-- 
cgit v1.2.3


From 3003b10e0ab84abb6298285e707b3618ceec51dc Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Thu, 17 Aug 2023 18:10:55 -0400
Subject: Attempt to resolve NaN issue with unstable VAEs in fp32 mk2

---
 modules/sd_samplers_common.py | 3 ++-
 1 file changed, 2 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 7dc79ea8..67deefa5 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -49,7 +49,8 @@ def samples_to_images_tensor(sample, approximation=None, model=None):
     else:
         if model is None:
             model = shared.sd_model
-        x_sample = model.decode_first_stage(sample.to(model.first_stage_model.dtype))
+        with devices.without_autocast(): # fixes an issue with unstable VAEs that are flaky even in fp32
+            x_sample = model.decode_first_stage(sample.to(model.first_stage_model.dtype))
 
     return x_sample
 
-- 
cgit v1.2.3


From 3ce5fb8e5c3a6577172e89e964d570f8b31a998b Mon Sep 17 00:00:00 2001
From: catboxanon <122327233+catboxanon@users.noreply.github.com>
Date: Thu, 17 Aug 2023 20:03:26 -0400
Subject: Add option for faster live interrupt

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 7dc79ea8..f0bc8e6a 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -36,7 +36,7 @@ approximation_indexes = {"Full": 0, "Approx NN": 1, "Approx cheap": 2, "TAESD":
 
 def samples_to_images_tensor(sample, approximation=None, model=None):
     '''latents -> images [-1, 1]'''
-    if approximation is None:
+    if approximation is None or (shared.state.interrupted and opts.live_preview_fast_interrupt):
         approximation = approximation_indexes.get(opts.show_progress_type, 0)
 
     if approximation == 2:
-- 
cgit v1.2.3


From 953c3eab7b3b952f7e96d728413a531d7fb521a2 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Mon, 21 Aug 2023 15:54:30 +0300
Subject: forbid Full live preview method for medvram and add a setting to undo
 the forbidding

---
 modules/sd_samplers_common.py | 7 ++++++-
 1 file changed, 6 insertions(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index feb1a9db..60fa161c 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -35,10 +35,15 @@ approximation_indexes = {"Full": 0, "Approx NN": 1, "Approx cheap": 2, "TAESD":
 
 
 def samples_to_images_tensor(sample, approximation=None, model=None):
-    '''latents -> images [-1, 1]'''
+    """Transforms 4-channel latent space images into 3-channel RGB image tensors, with values in range [-1, 1]."""
+
     if approximation is None or (shared.state.interrupted and opts.live_preview_fast_interrupt):
         approximation = approximation_indexes.get(opts.show_progress_type, 0)
 
+        from modules import lowvram
+        if approximation == 0 and lowvram.is_enabled(shared.sd_model) and not shared.opts.live_preview_allow_lowvram_full:
+            approximation = 1
+
     if approximation == 2:
         x_sample = sd_vae_approx.cheap_approximation(sample)
     elif approximation == 1:
-- 
cgit v1.2.3


From d7c9c6142071359470347564913feb5b7a6c5c13 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Tue, 22 Aug 2023 09:55:20 +0300
Subject: attemped solution to the uncommon hanging problem that is seemingly
 caused by live previews working on the tensor as denoising

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 60fa161c..64845ea4 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -111,7 +111,7 @@ def images_tensor_to_samples(image, approximation=None, model=None):
 
 
 def store_latent(decoded):
-    state.current_latent = decoded
+    state.current_latent = decoded.clone()
 
     if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
         if not shared.parallel_processing_allowed:
-- 
cgit v1.2.3


From a459075d26eecc38d6d58116e38f453450191460 Mon Sep 17 00:00:00 2001
From: AUTOMATIC1111 <16777216c@gmail.com>
Date: Tue, 22 Aug 2023 10:41:10 +0300
Subject: actual solution to the uncommon hanging problem that is seemingly
 caused by multiple progress requests working on same tensor

---
 modules/sd_samplers_common.py | 2 +-
 1 file changed, 1 insertion(+), 1 deletion(-)

(limited to 'modules/sd_samplers_common.py')

diff --git a/modules/sd_samplers_common.py b/modules/sd_samplers_common.py
index 64845ea4..60fa161c 100644
--- a/modules/sd_samplers_common.py
+++ b/modules/sd_samplers_common.py
@@ -111,7 +111,7 @@ def images_tensor_to_samples(image, approximation=None, model=None):
 
 
 def store_latent(decoded):
-    state.current_latent = decoded.clone()
+    state.current_latent = decoded
 
     if opts.live_previews_enable and opts.show_progress_every_n_steps > 0 and shared.state.sampling_step % opts.show_progress_every_n_steps == 0:
         if not shared.parallel_processing_allowed:
-- 
cgit v1.2.3