Merged changes from master

README.md

@@ -1,7 +1,11 @@
-# Stable Diffusion web UI
-A browser interface based on Gradio library for Stable Diffusion.
+# Stable Diffusion web UI with OpenVINO™ Acceleration
+A browser interface based on Gradio library for Stable Diffusion with OpenVINO™ Acceleration Script.
 
-![](screenshot.png)
+This repo is a fork of [AUTOMATIC1111/stable-diffusion-webui](https://github.com/AUTOMATIC1111/stable-diffusion-webui) which includes OpenVINO support through a [custom script](https://github.com/openvinotoolkit/stable-diffusion-webui/blob/master/scripts/openvino_accelerate.py) to run it on Intel CPUs and Intel GPUs.
+
+See wiki page for [Installation-on-Intel-Silicon](https://github.com/openvinotoolkit/stable-diffusion-webui/wiki/Installation-on-Intel-Silicon)
+
+![](screenshot_OpenVINO.png)
 
 ## Features
 [Detailed feature showcase with images](https://github.com/AUTOMATIC1111/stable-diffusion-webui/wiki/Features):

first-time-runner.bat

@@ -0,0 +1,21 @@
+@echo off
+
+set "filePath=%cd%\webui-user.bat"
+
+
+(
+    echo @echo off
+    echo.  
+    echo set GIT=
+    echo set VENV_DIR=
+    echo set COMMANDLINE_ARGS=--skip-torch-cuda-test --precision full --no-half 
+    echo set PYTORCH_TRACING_MODE=TORCHFX
+    echo.   
+    echo call webui.bat
+
+) > %filepath%
+
+
+call webui-user.bat
+
+pause

requirements.txt

@@ -32,4 +32,4 @@ torchdiffeq
 torchsde
 transformers==4.30.0
 diffusers==0.18.2
-openvino==2023.1.0.dev20230728
+openvino==2023.1.0.dev20230811

requirements_versions.txt

@@ -1,4 +1,4 @@
-GitPython==3.1.30
+GitPython==3.1.32
 Pillow==9.5.0
 accelerate==0.18.0
 basicsr==1.4.2
@@ -30,5 +30,5 @@ torchdiffeq==0.2.3
 torchsde==0.2.5
 transformers==4.30.0
 diffusers==0.18.2
-openvino==2023.1.0.dev20230728
+openvino==2023.1.0.dev20230811
 

scripts/openvino_accelerate.py

@@ -14,23 +14,25 @@ import modules
 import modules.paths as paths
 import modules.scripts as scripts
 
-from modules import images, devices, extra_networks, masking, shared
+from modules import images, devices, extra_networks, masking, shared, sd_models_config
 from modules.processing import (
     StableDiffusionProcessing, Processed, apply_overlay, apply_color_correction,
     get_fixed_seed, create_infotext, setup_color_correction,
     process_images
 )
-from modules.sd_models import CheckpointInfo
+from modules.sd_models import CheckpointInfo, get_checkpoint_state_dict
 from modules.shared import opts, state
+from modules.ui_common import create_refresh_button
+from modules.timer import Timer
 
 from PIL import Image, ImageOps
 from pathlib import Path
 from types import MappingProxyType
-from typing import Callable, Optional
+from typing import Optional
 
 from openvino.frontend import FrontEndManager
 from openvino.frontend.pytorch.fx_decoder import TorchFXPythonDecoder
-from openvino.frontend.pytorch.torchdynamo import backend #, compile # noqa: F401
+from openvino.frontend.pytorch.torchdynamo import backend # noqa: F401
 from openvino.frontend.pytorch.torchdynamo.partition import Partitioner
 from openvino.runtime import Core, Type, PartialShape, serialize
 
@@ -114,7 +116,7 @@ def openvino_fx(subgraph, example_inputs):
                     example_inputs_reordered = []
                     if (os.path.isfile(maybe_fs_cached_name + ".txt")):
                         f = open(maybe_fs_cached_name + ".txt", "r")
-                        for idx, input_data in enumerate(example_inputs):
+                        for input_data in example_inputs:
                             shape = f.readline()
                             if (str(input_data.size()) != shape):
                                 for idx1, input_data1 in enumerate(example_inputs):
@@ -130,7 +132,7 @@ def openvino_fx(subgraph, example_inputs):
                             args_reordered = []
                             if (os.path.isfile(maybe_fs_cached_name + ".txt")):
                                 f = open(maybe_fs_cached_name + ".txt", "r")
-                                for idx, input_data in enumerate(args):
+                                for input_data in args:
                                     shape = f.readline()
                                     if (str(input_data.size()) != shape):
                                         for idx1, input_data1 in enumerate(args):
@@ -163,6 +165,7 @@ def openvino_fx(subgraph, example_inputs):
             return res
         return _call
     except Exception as e:
+        print(e)
         return compile_fx(subgraph, example_inputs)
 
 def check_fully_supported(self, graph_module: GraphModule) -> bool:
@@ -315,7 +318,7 @@ def cached_model_name(model_hash_str, device, args, cache_root, reversed = False
         return None
 
     inputs_str = ""
-    for idx, input_data in enumerate(args):
+    for input_data in args:
         if reversed:
             inputs_str = "_" + str(input_data.type()) + str(input_data.size())[11:-1].replace(" ", "") + inputs_str
         else:
@@ -380,7 +383,7 @@ def openvino_compile(gm: GraphModule, *args, model_hash_str: str = None, file_na
 
         input_shapes = []
         input_types = []
-        for idx, input_data in enumerate(args):
+        for input_data in args:
             input_types.append(input_data.type())
             input_shapes.append(input_data.size())
 
@@ -394,7 +397,7 @@ def openvino_compile(gm: GraphModule, *args, model_hash_str: str = None, file_na
             serialize(om, file_name + ".xml", file_name + ".bin")
             if (model_state.cn_model != "None"):
                 f = open(file_name + ".txt", "w")
-                for idx, input_data in enumerate(args):
+                for input_data in args:
                     f.write(str(input_data.size()))
                     f.write("\n")
                 f.close()
@@ -572,7 +575,7 @@ def set_scheduler(sd_model, sampler_name):
 
     return sd_model.scheduler
 
-def get_diffusers_sd_model(local_config, model_config, sampler_name, enable_caching, openvino_device, mode):
+def get_diffusers_sd_model(model_config, sampler_name, enable_caching, openvino_device, mode):
     if (model_state.recompile == 1):
         model_state.partition_id = 0
         torch._dynamo.reset()
@@ -580,11 +583,16 @@ def get_diffusers_sd_model(local_config, model_config, sampler_name, enable_cach
         curr_dir_path = os.getcwd()
         checkpoint_name = shared.opts.sd_model_checkpoint.split(" ")[0]
         checkpoint_path = os.path.join(curr_dir_path, 'models', 'Stable-diffusion', checkpoint_name)
-        if local_config:
+        checkpoint_info = CheckpointInfo(checkpoint_path)
+        timer = Timer()
+        state_dict = get_checkpoint_state_dict(checkpoint_info, timer)
+        checkpoint_config = sd_models_config.find_checkpoint_config(state_dict, checkpoint_info)
+        print("OpenVINO Script:  created model from config : " + checkpoint_config)
+        if model_config != "None":
             local_config_file = os.path.join(curr_dir_path, 'configs', model_config)
             sd_model = StableDiffusionPipeline.from_single_file(checkpoint_path, local_config_file=local_config_file, load_safety_checker=False)
         else:
-            sd_model = StableDiffusionPipeline.from_single_file(checkpoint_path, load_safety_checker=False, torch_dtype=torch.float32)
+            sd_model = StableDiffusionPipeline.from_single_file(checkpoint_path, local_config_file=checkpoint_config, load_safety_checker=False, torch_dtype=torch.float32)
         if (mode == 1):
             sd_model = StableDiffusionImg2ImgPipeline(**sd_model.components)
         elif (mode == 2):
@@ -594,6 +602,7 @@ def get_diffusers_sd_model(local_config, model_config, sampler_name, enable_cach
             sd_model = StableDiffusionControlNetPipeline(**sd_model.components, controlnet=controlnet)
             sd_model.controlnet = torch.compile(sd_model.controlnet, backend="openvino_fx")
         checkpoint_info = CheckpointInfo(checkpoint_path)
+
         sd_model.sd_checkpoint_info = checkpoint_info
         sd_model.sd_model_hash = checkpoint_info.calculate_shorthash()
         sd_model.safety_checker = None
@@ -700,8 +709,7 @@ def init_new(self, all_prompts, all_seeds, all_subseeds):
     else:
         raise RuntimeError(f"bad number of images passed: {len(imgs)}; expecting {self.batch_size} or less")
 
-
-def process_images_openvino(p: StableDiffusionProcessing, local_config, model_config, sampler_name, enable_caching, openvino_device, mode) -> Processed:
+def process_images_openvino(p: StableDiffusionProcessing, model_config, sampler_name, enable_caching, openvino_device, mode) -> Processed:
     """this is the main loop that both txt2img and img2img use; it calls func_init once inside all the scopes and func_sample once per batch"""
 
     if (mode == 0 and p.enable_hr):
@@ -756,7 +764,6 @@ def process_images_openvino(p: StableDiffusionProcessing, local_config, model_co
             )
             p.scripts.postprocess(p, control_res)
             control_image = control_images[0]
-            #cn_model = "lllyasviel/" + cn_model
             mode = 3
 
     infotexts = []
@@ -800,7 +807,7 @@ def process_images_openvino(p: StableDiffusionProcessing, local_config, model_co
                 model_state.cn_model = cn_model
                 model_state.model_hash = shared.sd_model.sd_model_hash
 
-            shared.sd_diffusers_model = get_diffusers_sd_model(local_config, model_config, sampler_name, enable_caching, openvino_device, mode)
+            shared.sd_diffusers_model = get_diffusers_sd_model(model_config, sampler_name, enable_caching, openvino_device, mode)
             shared.sd_diffusers_model.scheduler = set_scheduler(shared.sd_diffusers_model, sampler_name)
 
             extra_network_data = p.parse_extra_network_prompts()
@@ -1000,15 +1007,20 @@ class Script(scripts.Script):
 
     def ui(self, is_img2img):
         core = Core()
-        config_dir_list = os.listdir(os.path.join(os.getcwd(), 'configs'))
 
+        def get_config_list():
+            config_dir_list = os.listdir(os.path.join(os.getcwd(), 'configs'))
             config_list = []
+            config_list.append("None")
             for file in config_dir_list:
                 if file.endswith('.yaml'):
                     config_list.append(file)
+            return config_list
+
+        with gr.Row():
+            model_config = gr.Dropdown(label="Select a local config for the model from the configs directory of the webui root", choices=get_config_list(), value="None", visible=True)
+            create_refresh_button(model_config, get_config_list, lambda: {"choices": get_config_list()},"refresh_model_config")
 
-        local_config = gr.Checkbox(label="Use a local inference config file", value=False)
-        model_config = gr.Dropdown(label="Select a config for the model (Below config files are listed from the configs directory of the WebUI root)", choices=config_list, value="v1-inference.yaml", visible=False)
         openvino_device = gr.Dropdown(label="Select a device", choices=list(core.available_devices), value=model_state.device)
         override_sampler = gr.Checkbox(label="Override the sampling selection from the main UI (Recommended as only below sampling methods have been validated for OpenVINO)", value=True)
         sampler_name = gr.Radio(label="Select a sampling method", choices=["Euler a", "Euler", "LMS", "Heun", "DPM++ 2M", "LMS Karras", "DPM++ 2M Karras", "DDIM", "PLMS"], value="Euler a")
@@ -1026,13 +1038,6 @@ class Script(scripts.Script):
         So it's normal for the first inference after a settings change to be slower, while subsequent inferences use the optimized compiled model and run faster.
         """)
 
-        def local_config_change(choice):
-            if choice:
-                return gr.update(visible=True)
-            else:
-                return gr.update(visible=False)
-        local_config.change(local_config_change, local_config, model_config)
-
         def device_change(choice):
             if (model_state.device == choice):
                 return gr.update(value="Device selected is " + choice, visible=True)
@@ -1042,9 +1047,9 @@ class Script(scripts.Script):
                 return gr.update(value="Device changed to " + choice + ". Model will be re-compiled", visible=True)
         openvino_device.change(device_change, openvino_device, warmup_status)
 
-        return [local_config, model_config, openvino_device, override_sampler, sampler_name, enable_caching]
+        return [model_config, openvino_device, override_sampler, sampler_name, enable_caching]
 
-    def run(self, p, local_config, model_config, openvino_device, override_sampler, sampler_name, enable_caching):
+    def run(self, p, model_config, openvino_device, override_sampler, sampler_name, enable_caching):
         model_state.partition_id = 0
         os.environ["OPENVINO_TORCH_BACKEND_DEVICE"] = str(openvino_device)
 
@@ -1062,14 +1067,14 @@ class Script(scripts.Script):
         mode = 0
         if self.is_txt2img:
             mode = 0
-            processed = process_images_openvino(p, local_config, model_config, p.sampler_name, enable_caching, openvino_device, mode)
+            processed = process_images_openvino(p, model_config, p.sampler_name, enable_caching, openvino_device, mode)
         else:
             if p.image_mask is None:
                 mode = 1
             else:
                 mode = 2
             p.init = functools.partial(init_new, p)
-            processed = process_images_openvino(p, local_config, model_config, p.sampler_name, enable_caching, openvino_device, mode)
+            processed = process_images_openvino(p, model_config, p.sampler_name, enable_caching, openvino_device, mode)
         return processed
 
 

torch-install.bat

@@ -0,0 +1,12 @@
+@echo off
+
+
+start /wait cmd /k "%cd%\venv\Scripts\activate && pip install --pre torch==2.1.0.dev20230713+cpu torchvision==0.16.0.dev20230713+cpu -f https://download.pytorch.org/whl/nightly/cpu/torch_nightly.html && exit"
+
+echo torch 2.1.0 dev installation completed.
+
+powershell -executionpolicy bypass .\torch-install.ps1
+
+
+echo eval_frame.py modification completed. press any key to exit
+pause

torch-install.ps1

@@ -0,0 +1,51 @@
+$scriptDirectory = $PSScriptRoot
+Set-Location $scriptDirectory
+
+## modify webui-user.bat
+$filePath = $pwd.Path + "\webui-user.bat"
+
+$newContent = @"
+
+@echo off
+
+set PYTHON=
+set GIT=
+set VENV_DIR=
+set COMMANDLINE_ARGS=--skip-torch-cuda-test --precision full --no-half --skip-prepare-environment
+set PYTORCH_TRACING_MODE=TORCHFX
+
+call webui.bat
+
+"@
+$newContent | Set-Content -Path $filePath
+
+
+
+
+
+
+
+### modify eval_frame
+
+$eval_filePath = $pwd.Path + "\venv\Lib\site-packages\torch\_dynamo\eval_frame.py"
+
+
+
+#comment out the two lines to test torch.compile on windows
+$replacements = @{
+    "    if sys.platform == `"win32`":" = "#    if sys.platform == `"win32`":"
+    "        raise RuntimeError(`"Windows not yet supported for torch.compile`")" = "#        raise RuntimeError(`"Windows not yet supported for torch.compile`")"
+}
+
+
+$lines = Get-Content -Path $eval_filePath
+
+foreach ($search_Text in $replacements.Keys){
+    $replaceText = $replacements[$search_text]
+    $lines = $lines.Replace($search_Text , $replaceText)
+}
+
+
+#write content back to file
+$lines | Set-Content -Path $eval_filePath
+