Merge branch 'main' into patch-1

docs/CHANGELOG.md

@@ -4,6 +4,97 @@ title: Changelog
 
 # :octicons-log-16: **Changelog**
 
+## v2.3.0 <small>(15 January 2023)</small>	
+
+**Transition to diffusers
+
+Version 2.3 provides support for both the traditional `.ckpt` weight
+checkpoint files as well as the HuggingFace `diffusers` format. This
+introduces several changes you should know about.
+
+1. The models.yaml format has been updated. There are now two
+   different type of configuration stanza. The traditional ckpt
+   one will look like this, with a `format` of `ckpt` and a
+   `weights` field that points to the absolute or ROOTDIR-relative
+   location of the ckpt file.
+
+   ```
+   inpainting-1.5:
+      description: RunwayML SD 1.5 model optimized for inpainting (4.27 GB)
+      repo_id: runwayml/stable-diffusion-inpainting
+      format: ckpt
+      width: 512
+      height: 512
+      weights: models/ldm/stable-diffusion-v1/sd-v1-5-inpainting.ckpt
+      config: configs/stable-diffusion/v1-inpainting-inference.yaml
+      vae: models/ldm/stable-diffusion-v1/vae-ft-mse-840000-ema-pruned.ckpt
+   ```
+
+  A configuration stanza for a diffusers model hosted at HuggingFace will look like this,
+  with a `format` of `diffusers` and a `repo_id` that points to the
+  repository ID of the model on HuggingFace:
+
+  ```
+  stable-diffusion-2.1:
+  description: Stable Diffusion version 2.1 diffusers model (5.21 GB)
+  repo_id: stabilityai/stable-diffusion-2-1
+  format: diffusers
+  ```
+
+  A configuration stanza for a diffuers model stored locally should
+  look like this, with a `format` of `diffusers`, but a `path` field
+  that points at the directory that contains `model_index.json`:
+  
+  ```
+  waifu-diffusion:
+  description: Latest waifu diffusion 1.4
+  format: diffusers
+  path: models/diffusers/hakurei-haifu-diffusion-1.4
+  ```
+
+2. The format of the models directory has changed to mimic the
+   HuggingFace cache directory. By default, diffusers models are
+   now automatically downloaded and retrieved from the directory
+   `ROOTDIR/models/diffusers`, while other models are stored in
+   the directory `ROOTDIR/models/hub`. This organization is the
+   same as that used by HuggingFace for its cache management.
+
+   This allows you to share diffusers and ckpt model files easily with
+   other machine learning applications that use the HuggingFace
+   libraries. To do this, set the environment variable HF_HOME
+   before starting up InvokeAI to tell it what directory to
+   cache models in. To tell InvokeAI to use the standard HuggingFace
+   cache directory, you would set HF_HOME like this (Linux/Mac):
+
+   `export HF_HOME=~/.cache/hugging_face`
+
+3. If you upgrade to InvokeAI 2.3.* from an earlier version, there
+   will be a one-time migration from the old models directory format
+   to the new one. You will see a message about this the first time
+   you start `invoke.py`.
+
+4. Both the front end back ends of the model manager have been
+   rewritten to accommodate diffusers. You can import models using
+   their local file path, using their URLs, or their HuggingFace
+   repo_ids. On the command line, all these syntaxes work:
+
+   ```
+   !import_model stabilityai/stable-diffusion-2-1-base
+   !import_model /opt/sd-models/sd-1.4.ckpt
+   !import_model https://huggingface.co/Fictiverse/Stable_Diffusion_PaperCut_Model/blob/main/PaperCut_v1.ckpt
+   ```
+   
+**KNOWN BUGS (15 January 2023)
+
+1. On CUDA systems, the 768 pixel stable-diffusion-2.0 and
+   stable-diffusion-2.1 models can only be run as `diffusers` models
+   when the `xformer` library is installed and configured. Without
+   `xformers`, InvokeAI returns black images.
+
+2. Inpainting and outpainting have regressed in quality.
+
+Both these issues are being actively worked on.
+
 ## v2.2.4 <small>(11 December 2022)</small>
 
 **the `invokeai` directory**

docs/installation/020_INSTALL_MANUAL.md

@@ -12,17 +12,18 @@ title: Installing Manually
 
 ## Introduction
 
-You have two choices for manual installation, the [first
-one](#PIP_method) uses basic Python virtual environment (`venv`)
-commands and the PIP package manager. The [second one](#Conda_method)
-based on the Anaconda3 package manager (`conda`). Both methods require
-you to enter commands on the terminal, also known as the "console".
+You have two choices for manual installation.
+The [first one](#pip-Install) uses basic Python virtual environment (`venv`)
+command and `pip` package manager.
+The [second one](#Conda-method) uses Anaconda3 package manager (`conda`).
+Both methods require you to enter commands on the terminal, also known as the
+"console".
 
-Note that the conda install method is currently deprecated and will not
-be supported at some point in the future.
+Note that the `conda` installation method is currently deprecated and will
+not be supported at some point in the future.
 
-On Windows systems you are encouraged to install and use the
-[Powershell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell-on-windows?view=powershell-7.3),
+On Windows systems, you are encouraged to install and use the
+[PowerShell](https://learn.microsoft.com/en-us/powershell/scripting/install/installing-powershell-on-windows?view=powershell-7.3),
 which provides compatibility with Linux and Mac shells and nice
 features such as command-line completion.
 
@@ -37,7 +38,7 @@ manager, please follow these steps:
     ```bash
     python -V
     ```
-    
+
 2.  Clone the [InvokeAI](https://github.com/invoke-ai/InvokeAI) source code from
     GitHub:
 
@@ -52,15 +53,15 @@ manager, please follow these steps:
     environment named `invokeai`:
 
     ```bash
-    python -mvenv invokeai
+    python -m venv invokeai
     source invokeai/bin/activate
     ```
 
-4. Make sure that pip is installed in your virtual environment an up to date:
+4.  Make sure that pip is installed in your virtual environment an up to date:
 
     ```bash
-    python -mensurepip --upgrade
-    python -mpip install --upgrade pip
+    python -m ensurepip --upgrade
+    python -m pip install --upgrade pip
     ```
 
 5.  Pick the correct `requirements*.txt` file for your hardware and operating
@@ -199,20 +200,20 @@ manager, please follow these steps:
 
         You can permanently set the location of the runtime directory by setting the environment variable INVOKEAI_ROOT to the path of the directory.
 
-9. Render away!
+9.  Render away!
 
     Browse the [features](../features/CLI.md) section to learn about all the things you
     can do with InvokeAI.
 
     Note that some GPUs are slow to warm up. In particular, when using an AMD
     card with the ROCm driver, you may have to wait for over a minute the first
-    time you try to generate an image. Fortunately, after the warm up period
+    time you try to generate an image. Fortunately, after the warm-up period
     rendering will be fast.
 
-10. Subsequently, to relaunch the script, be sure to run "conda activate
-    invokeai", enter the `InvokeAI` directory, and then launch the invoke
-    script. If you forget to activate the 'invokeai' environment, the script
-    will fail with multiple `ModuleNotFound` errors.
+10. Subsequently, to relaunch the script, be sure to enter `InvokeAI` directory,
+    activate the virtual environment, and then launch `invoke.py` script.
+    If you forget to activate the virtual environment,
+    the script will fail with multiple `ModuleNotFound` errors.
 
     !!! tip