Merge branch 'v2.3' into lstein/enhance/autoconvert-vaes

Author: lstein

.github/CODEOWNERS

@@ -1,13 +1,13 @@
 # continuous integration
-/.github/workflows/ @mauwii @lstein @blessedcoolant
+/.github/workflows/  @lstein @blessedcoolant
 
 # documentation
-/docs/ @lstein @mauwii @blessedcoolant
-mkdocs.yml @mauwii @lstein
+/docs/ @lstein  @blessedcoolant
+mkdocs.yml  @lstein @ebr
 
 # installation and configuration
-/pyproject.toml @mauwii @lstein @ebr
-/docker/ @mauwii
+/pyproject.toml  @lstein @ebr
+/docker/ @lstein
 /scripts/ @ebr @lstein @blessedcoolant
 /installer/ @ebr @lstein 
 ldm/invoke/config @lstein @ebr
@@ -21,13 +21,13 @@ invokeai/configs @lstein @ebr  @blessedcoolant
 
 # generation and model management
 /ldm/*.py @lstein @blessedcoolant
-/ldm/generate.py @lstein @keturn
+/ldm/generate.py @lstein @gregghelt2
 /ldm/invoke/args.py @lstein @blessedcoolant
 /ldm/invoke/ckpt* @lstein @blessedcoolant
 /ldm/invoke/ckpt_generator @lstein @blessedcoolant
 /ldm/invoke/CLI.py @lstein @blessedcoolant
-/ldm/invoke/config @lstein @ebr @mauwii @blessedcoolant
-/ldm/invoke/generator @keturn @damian0815
+/ldm/invoke/config @lstein @ebr  @blessedcoolant
+/ldm/invoke/generator @gregghelt2 @damian0815
 /ldm/invoke/globals.py @lstein @blessedcoolant 
 /ldm/invoke/merge_diffusers.py @lstein @blessedcoolant
 /ldm/invoke/model_manager.py @lstein @blessedcoolant
@@ -36,17 +36,17 @@ invokeai/configs @lstein @ebr  @blessedcoolant
 /ldm/invoke/restoration @lstein @blessedcoolant
 
 # attention, textual inversion, model configuration
-/ldm/models @damian0815 @keturn @blessedcoolant
+/ldm/models @damian0815 @gregghelt2 @blessedcoolant
 /ldm/modules/textual_inversion_manager.py @lstein @blessedcoolant
-/ldm/modules/attention.py @damian0815 @keturn
-/ldm/modules/diffusionmodules @damian0815 @keturn
-/ldm/modules/distributions @damian0815 @keturn
-/ldm/modules/ema.py  @damian0815 @keturn
+/ldm/modules/attention.py @damian0815 @gregghelt2
+/ldm/modules/diffusionmodules @damian0815 @gregghelt2
+/ldm/modules/distributions @damian0815 @gregghelt2
+/ldm/modules/ema.py  @damian0815 @gregghelt2
 /ldm/modules/embedding_manager.py @lstein
-/ldm/modules/encoders @damian0815 @keturn
-/ldm/modules/image_degradation @damian0815 @keturn
-/ldm/modules/losses  @damian0815 @keturn
-/ldm/modules/x_transformer.py @damian0815 @keturn
+/ldm/modules/encoders @damian0815 @gregghelt2
+/ldm/modules/image_degradation @damian0815 @gregghelt2
+/ldm/modules/losses  @damian0815 @gregghelt2
+/ldm/modules/x_transformer.py @damian0815 @gregghelt2
 
 # Nodes
 apps/ @Kyle0654 @jpphoto

.gitignore

@@ -233,5 +233,3 @@ installer/install.sh
 installer/update.bat
 installer/update.sh
 
-# no longer stored in source directory
-models

docs/features/LORAS.md

@@ -41,6 +41,16 @@ Windows systems). If the `loras` folder does not already exist, just
 create it. The vast majority of LoRA models use the Kohya file format,
 which is a type of `.safetensors` file.
 
+!!! warning "LoRA Naming Restrictions"
+
+    InvokeAI will only recognize LoRA files that contain the
+    characters a-z, A-Z, 0-9 and the underscore character
+    _. Other characters, including the hyphen, will cause the
+    LoRA file not to load. These naming restrictions may be
+    relaxed in the future, but for now you will need to rename
+    files that contain hyphens, commas, brackets, and other
+    non-word characters.
+
 You may change where InvokeAI looks for the `loras` folder by passing the
 `--lora_directory` option to the `invoke.sh`/`invoke.bat` launcher, or
 by placing the option in `invokeai.init`. For example:

docs/features/index.md

@@ -33,6 +33,11 @@ title: Overview
         Restore mangled faces and make images larger with upscaling. Also see
         the [Embiggen Upscaling Guide](EMBIGGEN.md).
 
+    -   The [Using LoRA Models](LORAS.md)
+
+        Add custom subjects and styles using HuggingFace's repository of
+        embeddings.
+	
     -   The [Concepts Library](CONCEPTS.md)
 
         Add custom subjects and styles using HuggingFace's repository of

docs/installation/deprecated_documentation/INSTALL_LINUX.md

@@ -79,7 +79,7 @@ title: Manual Installation, Linux
         and obtaining an access token for downloading. It will then download and
         install the weights files for you.
 
-        Please look [here](../INSTALL_MANUAL.md) for a manual process for doing
+        Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing
         the same thing.
 
 7.  Start generating images!

docs/installation/deprecated_documentation/INSTALL_WINDOWS.md

@@ -75,7 +75,7 @@ Note that you will need NVIDIA drivers, Python 3.10, and Git installed beforehan
           obtaining an access token for downloading. It will then download and install the
           weights files for you.
 
-          Please look [here](../INSTALL_MANUAL.md) for a manual process for doing the
+          Please look [here](../020_INSTALL_MANUAL.md) for a manual process for doing the
           same thing.
 
 8. Start generating images!

docs/requirements-mkdocs.txt

@@ -0,0 +1,5 @@
+mkdocs
+mkdocs-material>=8, <9
+mkdocs-git-revision-date-localized-plugin
+mkdocs-redirects==1.2.0
+

installer/lib/installer.py

@@ -243,16 +243,15 @@ def install_torch(self, extra_index_url=None, find_links=None):
 
         # Note that we're installing pinned versions of torch and
         # torchvision here, which *should* correspond to what is
-        # in pyproject.toml. This is to prevent torch 2.0 from
-        # being installed and immediately uninstalled and replaced with 1.13
+        # in pyproject.toml.
         pip = local[self.pip]
 
         (
             pip[
                 "install",
                 "--require-virtualenv",
-                "torch~=1.13.1",
-                "torchvision~=0.14.1",
+                "torch~=2.0.0",
+                "torchvision>=0.14.1",
                 "--force-reinstall",
                 "--find-links" if find_links is not None else None,
                 find_links,

invokeai/backend/invoke_ai_web_server.py

@@ -25,24 +25,23 @@
 import invokeai.frontend.dist as frontend
 from ldm.generate import Generate
 from ldm.invoke.args import Args, APP_ID, APP_VERSION, calculate_init_img_hash
-from ldm.invoke.concepts_lib import HuggingFaceConceptsLibrary
+from ldm.invoke.concepts_lib import get_hf_concepts_lib
 from ldm.invoke.conditioning import (
     get_tokens_for_prompt_object,
     get_prompt_structure,
     split_weighted_subprompts,
-    get_tokenizer,
 )
 from ldm.invoke.generator.diffusers_pipeline import PipelineIntermediateState
 from ldm.invoke.generator.inpaint import infill_methods
 from ldm.invoke.globals import (
     Globals,
     global_converted_ckpts_dir,
     global_models_dir,
-    global_lora_models_dir,
 )
 from ldm.invoke.pngwriter import PngWriter, retrieve_metadata
 from compel.prompt_parser import Blend
 from ldm.invoke.merge_diffusers import merge_diffusion_models
+from ldm.modules.lora_manager import LoraManager
 
 # Loading Arguments
 opt = Args()
@@ -524,20 +523,12 @@ def merge_diffusers_models(model_merge_info: dict):
         @socketio.on("getLoraModels")
         def get_lora_models():
             try:
-                lora_path = global_lora_models_dir()
-                loras = []
-                for root, _, files in os.walk(lora_path):
-                    models = [
-                        Path(root, x)
-                        for x in files
-                        if Path(x).suffix in [".ckpt", ".pt", ".safetensors"]
-                    ]
-                    loras = loras + models
-
+                model = self.generate.model
+                lora_mgr = LoraManager(model)
+                loras = lora_mgr.list_compatible_loras()
                 found_loras = []
-                for lora in sorted(loras, key=lambda s: s.stem.lower()):
-                    location = str(lora.resolve()).replace("\\", "/")
-                    found_loras.append({"name": lora.stem, "location": location})
+                for lora in sorted(loras, key=str.casefold):
+                    found_loras.append({"name":lora,"location":str(loras[lora])})
                 socketio.emit("foundLoras", found_loras)
             except Exception as e:
                 self.handle_exceptions(e)
@@ -547,7 +538,7 @@ def get_ti_triggers():
             try:
                 local_triggers = self.generate.model.textual_inversion_manager.get_all_trigger_strings()
                 locals = [{'name': x} for x in sorted(local_triggers, key=str.casefold)]
-                concepts = HuggingFaceConceptsLibrary().list_concepts(minimum_likes=5)
+                concepts = get_hf_concepts_lib().list_concepts(minimum_likes=5)
                 concepts = [{'name': f'<{x}>'} for x in sorted(concepts, key=str.casefold) if f'<{x}>' not in local_triggers]
                 socketio.emit("foundTextualInversionTriggers", {'local_triggers': locals, 'huggingface_concepts': concepts})
             except Exception as e:
@@ -1314,7 +1305,7 @@ def image_done(image, seed, first_seed, attention_maps_image=None):
                     None
                     if type(parsed_prompt) is Blend
                     else get_tokens_for_prompt_object(
-                        get_tokenizer(self.generate.model), parsed_prompt
+                        self.generate.model.tokenizer, parsed_prompt
                     )
                 )
                 attention_maps_image_base64_url = (

invokeai/configs/INITIAL_MODELS.yaml

@@ -80,7 +80,8 @@ trinart-2.0:
      repo_id: stabilityai/sd-vae-ft-mse
    recommended: False
 waifu-diffusion-1.4:
-   description: An SD-1.5 model trained on 680k anime/manga-style images (2.13 GB)
+   description: An SD-2.1 model trained on 5.4M anime/manga-style images (4.27 GB)
+   revision: main
    repo_id: hakurei/waifu-diffusion
    format: diffusers
    vae: