Merge branch 'main' into dev/diffusers

.github/workflows/build-cloud-img.yml

@@ -4,9 +4,12 @@ on:
   push:
     branches:
     - main
-    - development
     tags:
       - v*
+  # we will NOT push the image on pull requests, only test buildability.
+  pull_request:
+    branches:
+    - main
 
 permissions:
   contents: read
@@ -21,36 +24,56 @@ jobs:
     strategy:
       fail-fast: false
       matrix:
-        # only x86_64 for now. aarch64+cuda isn't really a thing yet
         arch:
         - x86_64
+        # requires resolving a patchmatch issue
+        # - aarch64
     runs-on: ubuntu-latest
     name: ${{ matrix.arch }}
     steps:
     - name: Checkout
       uses: actions/checkout@v3
 
+    - name: Set up QEMU
+      uses: docker/setup-qemu-action@v2
+      if: matrix.arch == 'aarch64'
+
     - name: Docker meta
       id: meta
       uses: docker/metadata-action@v4
       with:
         images: ${{ env.REGISTRY }}/${{ env.IMAGE_NAME }}
+        # see https://github.com/docker/metadata-action
+        # will push the following tags:
+        # :edge
+        # :main (+ any other branches enabled in the workflow)
+        # :<tag>
+        # :1.2.3 (for semver tags)
+        # :1.2 (for semver tags)
+        # :<sha>
         tags: |
+          type=edge,branch=main
           type=ref,event=branch
           type=ref,event=tag
-          type=ref,event=pr
+          type=semver,pattern={{version}}
+          type=semver,pattern={{major}}.{{minor}}
           type=sha
+        # suffix image tags with architecture
+        flavor: |
+          latest=auto
+          suffix=-${{ matrix.arch }},latest=true
 
     - name: Set up Docker Buildx
       uses: docker/setup-buildx-action@v2
 
-    # - if: github.event_name != 'pull_request'
-    #   name: Docker login
-    #   uses: docker/login-action@v2
-    #   with:
-    #     registry: ghcr.io
-    #     username: ${{ github.actor }}
-    #     password: ${{ secrets.GITHUB_TOKEN }}
+    # do not login to container registry on PRs
+    - if: github.event_name != 'pull_request'
+      name: Docker login
+      uses: docker/login-action@v2
+      with:
+        registry: ghcr.io
+        username: ${{ github.actor }}
+        password: ${{ secrets.GITHUB_TOKEN }}
 
     - name: Build and push cloud image
       uses: docker/build-push-action@v3
@@ -58,7 +81,7 @@ jobs:
         context: .
         file: docker-build/Dockerfile.cloud
         platforms: Linux/${{ matrix.arch }}
-        # push: ${{ github.event_name != 'pull_request' }}
-        push: false
+        # do not push the image on PRs
+        push: ${{ github.event_name != 'pull_request' }}
         tags: ${{ steps.meta.outputs.tags }}
         labels: ${{ steps.meta.outputs.labels }}

docs/installation/INSTALL_JUPYTER.md

@@ -2,12 +2,10 @@
 title: Running InvokeAI on Google Colab using a Jupyter Notebook
 ---
 
-# THIS DOCUMENTATION IS UNFINISHED - VOLUNTEERS GRATEFULLY ACCEPTED
-
 ## Introduction
 
 We have a [Jupyter
-notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable-Diffusion-local-Windows.ipynb)
+notebook](https://github.com/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
 with cell-by-cell installation steps. It will download the code in
 this repo as one of the steps, so instead of cloning this repo, simply
 download the notebook from the link above and load it up in VSCode
@@ -16,10 +14,19 @@ start running the cells one-by-one.
 
 !!! Note "you will need NVIDIA drivers, Python 3.10, and Git installed beforehand"
 
-## Walkthrough
+## Running Online On Google Colabotary
+[![Open in Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/invoke-ai/InvokeAI/blob/main/notebooks/Stable_Diffusion_AI_Notebook.ipynb)
 
-## Updating to newer versions
+## Running Locally (Cloning)
 
-### Updating the stable version
+1. Install the Jupyter Notebook python library (one-time):
+pip install jupyter
 
-## Troubleshooting
+2. Clone the InvokeAI repository:
+git clone https://github.com/invoke-ai/InvokeAI.git
+cd invoke-ai
+3. Create a virtual environment using conda:
+conda create -n invoke jupyter
+4. Activate the environment and start the Jupyter notebook:
+conda activate invoke
+jupyter notebook

ldm/invoke/model_cache.py

@@ -266,7 +266,9 @@ class ModelCache(object):
         model_hash = self._cached_sha256(weights, weight_bytes)
         sd = torch.load(io.BytesIO(weight_bytes), map_location='cpu')
         del weight_bytes
-        sd = sd['state_dict']
+        # merged models from auto11 merge board are flat for some reason
+        if 'state_dict' in sd:
+            sd = sd['state_dict']
         model = instantiate_from_config(omega_config.model)
         model.load_state_dict(sd, strict=False)