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Merge branch 'main' into feat/xformers-startup-message

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Kevin Turner 2023-01-31 18:48:09 -08:00 committed by GitHub
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13
.dockerignore
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@ -1,19 +1,18 @@
*
!assets/caution.png
!backend
!environments-and-requirements
!frontend
!frontend/dist
!ldm
!main.py
!pyproject.toml
!README.md
!scripts
!server
!static
!setup.py
# Guard against pulling in any models that might exist in the directory tree
**/*.pt*
**.pt*
# unignore configs, but only ignore the custom models.yaml, in case it exists
!configs
configs/models.yaml
configs/models.yaml.orig
**/__pycache__

34
.github/workflows/build-container.yml vendored
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@ -3,63 +3,59 @@ on:
push:
branches:
- 'main'
tags:
- 'v*.*.*'
jobs:
docker:
strategy:
fail-fast: false
matrix:
registry:
- ghcr.io
flavor:
- amd
- cuda
# - cloud
include:
- flavor: amd
pip-requirements: requirements-lin-amd.txt
pip-extra-index-url: 'https://download.pytorch.org/whl/rocm5.2'
dockerfile: docker-build/Dockerfile
platforms: linux/amd64,linux/arm64
- flavor: cuda
pip-requirements: requirements-lin-cuda.txt
pip-extra-index-url: ''
dockerfile: docker-build/Dockerfile
platforms: linux/amd64,linux/arm64
# - flavor: cloud
# pip-requirements: requirements-lin-cuda.txt
# dockerfile: docker-build/Dockerfile.cloud
# platforms: linux/amd64
runs-on: ubuntu-latest
name: ${{ matrix.flavor }}
steps:
- name: Checkout
uses: actions/checkout@v3
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Docker meta
id: meta
uses: docker/metadata-action@v4
with:
images: ${{ matrix.registry }}/${{ github.repository }}-${{ matrix.flavor }}
images: ghcr.io/${{ github.repository }}-${{ matrix.flavor }}
tags: |
type=ref,event=branch
type=ref,event=tag
type=semver,pattern={{version}}
type=semver,pattern={{major}}.{{minor}}
type=semver,pattern={{major}}
type=sha
flavor: |
latest=true
- name: Set up QEMU
uses: docker/setup-qemu-action@v2
- name: Set up Docker Buildx
uses: docker/setup-buildx-action@v2
- if: github.event_name != 'pull_request'
name: Docker login
- name: Login to GitHub Container Registry
if: github.event_name != 'pull_request'
uses: docker/login-action@v2
with:
registry: ${{ matrix.registry }}
username: ${{ github.actor }}
registry: ghcr.io
username: ${{ github.repository_owner }}
password: ${{ secrets.GITHUB_TOKEN }}
- name: Build container
@ -71,4 +67,6 @@ jobs:
push: ${{ github.event_name != 'pull_request' }}
tags: ${{ steps.meta.outputs.tags }}
labels: ${{ steps.meta.outputs.labels }}
build-args: pip_requirements=${{ matrix.pip-requirements }}
build-args: PIP_EXTRA_INDEX_URL=${{ matrix.pip-extra-index-url }}
# cache-from: type=gha
# cache-to: type=gha,mode=max

83
docker-build/Dockerfile
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@ -1,59 +1,71 @@
FROM python:3.10-slim AS builder
# syntax=docker/dockerfile:1
FROM python:3.9-slim AS python-base
# use bash
SHELL [ "/bin/bash", "-c" ]
# Install necesarry packages
RUN apt-get update \
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
libgl1-mesa-glx=20.3.* \
libglib2.0-0=2.66.* \
libopencv-dev=4.5.* \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
ARG APPDIR=/usr/src/app
ENV APPDIR ${APPDIR}
WORKDIR ${APPDIR}
FROM python-base AS builder
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
gcc=4:10.2.* \
libgl1-mesa-glx=20.3.* \
libglib2.0-0=2.66.* \
python3-dev=3.9.* \
&& apt-get clean \
&& rm -rf /var/lib/apt/lists/*
# set WORKDIR, PATH and copy sources
ARG APPDIR=/usr/src/app
WORKDIR ${APPDIR}
ENV PATH ${APPDIR}/.venv/bin:$PATH
ARG PIP_REQUIREMENTS=requirements-lin-cuda.txt
COPY . ./environments-and-requirements/${PIP_REQUIREMENTS} ./
# copy sources
COPY --link . .
ARG PIP_EXTRA_INDEX_URL
ENV PIP_EXTRA_INDEX_URL ${PIP_EXTRA_INDEX_URL}
# install requirements
RUN python3 -m venv .venv \
&& pip install \
--upgrade \
RUN python3 -m venv invokeai \
&& ${APPDIR}/invokeai/bin/pip \
install \
--no-cache-dir \
'wheel>=0.38.4' \
&& pip install \
--no-cache-dir \
-r ${PIP_REQUIREMENTS}
--use-pep517 \
.
FROM python:3.10-slim AS runtime
FROM python-base AS runtime
# setup environment
ARG APPDIR=/usr/src/app
WORKDIR ${APPDIR}
COPY --from=builder ${APPDIR} .
ENV \
PATH=${APPDIR}/.venv/bin:$PATH \
INVOKEAI_ROOT=/data \
INVOKE_MODEL_RECONFIGURE=--yes
COPY --link . .
COPY --from=builder ${APPDIR}/invokeai ${APPDIR}/invokeai
ENV PATH=${APPDIR}/invokeai/bin:$PATH
ENV INVOKEAI_ROOT=/data
ENV INVOKE_MODEL_RECONFIGURE="--yes --default_only"
# Install necesarry packages
RUN apt-get update \
# build patchmatch
RUN \
--mount=type=cache,target=/var/cache/apt,sharing=locked \
--mount=type=cache,target=/var/lib/apt,sharing=locked \
apt-get update \
&& apt-get install -y \
--no-install-recommends \
build-essential=12.9 \
libgl1-mesa-glx=20.3.* \
libglib2.0-0=2.66.* \
libopencv-dev=4.5.* \
&& ln -sf \
/usr/lib/"$(arch)"-linux-gnu/pkgconfig/opencv4.pc \
/usr/lib/"$(arch)"-linux-gnu/pkgconfig/opencv.pc \
&& python3 -c "from patchmatch import patch_match" \
&& PYTHONDONTWRITEBYTECODE=1 \
python3 -c "from patchmatch import patch_match" \
&& apt-get remove -y \
--autoremove \
build-essential \
@ -61,5 +73,6 @@ RUN apt-get update \
&& rm -rf /var/lib/apt/lists/*
# set Entrypoint and default CMD
ENTRYPOINT [ "python3", "scripts/invoke.py" ]
ENTRYPOINT [ "invoke" ]
CMD [ "--web", "--host=0.0.0.0" ]
VOLUME [ "/data" ]

35
docker-build/build.sh
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@ -2,34 +2,41 @@
set -e
# How to use: https://invoke-ai.github.io/InvokeAI/installation/INSTALL_DOCKER/#setup
#
# Some possible pip extra-index urls (cuda 11.7 is available without extra url):
#
# CUDA 11.6: https://download.pytorch.org/whl/cu116
# ROCm 5.2: https://download.pytorch.org/whl/rocm5.2
# CPU: https://download.pytorch.org/whl/cpu
#
# as found on https://pytorch.org/get-started/locally/
source ./docker-build/env.sh \
|| echo "please execute docker-build/build.sh from repository root" \
|| exit 1
cd "$(dirname "$0")" || exit 1
PIP_REQUIREMENTS=${PIP_REQUIREMENTS:-requirements-lin-cuda.txt}
DOCKERFILE=${INVOKE_DOCKERFILE:-docker-build/Dockerfile}
source ./env.sh
DOCKERFILE=${INVOKE_DOCKERFILE:-"./Dockerfile"}
# print the settings
echo -e "You are using these values:\n"
echo -e "Dockerfile:\t ${DOCKERFILE}"
echo -e "Requirements:\t ${PIP_REQUIREMENTS}"
echo -e "extra-index-url: ${PIP_EXTRA_INDEX_URL:-none}"
echo -e "Volumename:\t ${VOLUMENAME}"
echo -e "arch:\t\t ${ARCH}"
echo -e "Platform:\t ${PLATFORM}"
echo -e "Invokeai_tag:\t ${INVOKEAI_TAG}\n"
if [[ -n "$(docker volume ls -f name="${VOLUMENAME}" -q)" ]]; then
echo -e "Volume already exists\n"
echo -e "Volume already exists\n"
else
echo -n "createing docker volume "
docker volume create "${VOLUMENAME}"
echo -n "createing docker volume "
docker volume create "${VOLUMENAME}"
fi
# Build Container
docker build \
--platform="${PLATFORM}" \
--tag="${INVOKEAI_TAG}" \
--build-arg="PIP_REQUIREMENTS=${PIP_REQUIREMENTS}" \
--file="${DOCKERFILE}" \
.
--platform="${PLATFORM}" \
--tag="${INVOKEAI_TAG}" \
${PIP_EXTRA_INDEX_URL:+--build-arg=PIP_EXTRA_INDEX_URL="${PIP_EXTRA_INDEX_URL}"} \
--file="${DOCKERFILE}" \
..

2
docker-build/env.sh
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@ -7,4 +7,4 @@ ARCH=${ARCH:-$(uname -m)}
PLATFORM=${PLATFORM:-Linux/${ARCH}}
CONTAINER_FLAVOR=${CONTAINER_FLAVOR:-cuda}
INVOKEAI_BRANCH=$(git branch --show)
INVOKEAI_TAG=${REPOSITORY_NAME,,}-${CONTAINER_FLAVOR}:${INVOKEAI_TAG:-${INVOKEAI_BRANCH/\//-}}
INVOKEAI_TAG=${REPOSITORY_NAME,,}-${CONTAINER_FLAVOR}:${INVOKEAI_TAG:-${INVOKEAI_BRANCH##*/}}

19
docker-build/run.sh
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@ -4,17 +4,14 @@ set -e
# How to use: https://invoke-ai.github.io/InvokeAI/installation/INSTALL_DOCKER/#run-the-container
# IMPORTANT: You need to have a token on huggingface.co to be able to download the checkpoints!!!
source ./docker-build/env.sh \
|| echo "please run from repository root" \
|| exit 1
cd "$(dirname "$0")" || exit 1
# check if HUGGINGFACE_TOKEN is available
# You must have accepted the terms of use for required models
HUGGINGFACE_TOKEN=${HUGGINGFACE_TOKEN:?Please set your token for Huggingface as HUGGINGFACE_TOKEN}
source ./env.sh
echo -e "You are using these values:\n"
echo -e "Volumename:\t ${VOLUMENAME}"
echo -e "Invokeai_tag:\t ${INVOKEAI_TAG}\n"
echo -e "Volumename:\t${VOLUMENAME}"
echo -e "Invokeai_tag:\t${INVOKEAI_TAG}"
echo -e "local Models:\t${MODELSPATH:-unset}\n"
docker run \
--interactive \
@ -23,8 +20,10 @@ docker run \
--platform="$PLATFORM" \
--name="${REPOSITORY_NAME,,}" \
--hostname="${REPOSITORY_NAME,,}" \
--mount="source=$VOLUMENAME,target=/data" \
--env="HUGGINGFACE_TOKEN=${HUGGINGFACE_TOKEN}" \
--mount=source="$VOLUMENAME",target=/data \
${MODELSPATH:+-u "$(id -u):$(id -g)"} \
${MODELSPATH:+--mount=type=bind,source=${MODELSPATH},target=/data/models} \
${HUGGING_FACE_HUB_TOKEN:+--env=HUGGING_FACE_HUB_TOKEN=${HUGGING_FACE_HUB_TOKEN}} \
--publish=9090:9090 \
--cap-add=sys_nice \
${GPU_FLAGS:+--gpus=${GPU_FLAGS}} \

77
ldm/invoke/CLI.py
View File

@ -21,6 +21,38 @@ import ldm.invoke
# global used in multiple functions (fix)
infile = None
def report_model_error(opt:Namespace, e:Exception):
print(f'** An error occurred while attempting to initialize the model: "{str(e)}"')
print('** This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models.')
if not str("--yes") in os.environ['INVOKE_MODEL_RECONFIGURE'].split():
response = input('Do you want to run configure_invokeai.py to select and/or reinstall models? [y] ')
if response.startswith(('n','N')):
return
print('configure_invokeai is launching....\n')
# Match arguments that were set on the CLI
# only the arguments accepted by the configuration script are parsed
root_dir = ["--root", opt.root_dir] if opt.root_dir is not None else []
config = ["--config", opt.conf] if opt.conf is not None else []
if os.getenv('INVOKE_MODEL_RECONFIGURE'):
yes_to_all = os.environ['INVOKE_MODEL_RECONFIGURE'].split()
else:
yes_to_all = None
previous_args = sys.argv
sys.argv = [ 'configure_invokeai' ]
sys.argv.extend(root_dir)
sys.argv.extend(config)
if yes_to_all is not None:
for argv in yes_to_all:
sys.argv.append(argv)
import ldm.invoke.configure_invokeai as configure_invokeai
sys.exit(configure_invokeai.main())
print('** InvokeAI will now restart')
sys.argv = previous_args
sys.exit(main()) # would rather do a os.exec(), but doesn't exist?
def main():
"""Initialize command-line parsers and the diffusion model"""
global infile
@ -50,10 +82,11 @@ def main():
if not args.conf:
if not os.path.exists(os.path.join(Globals.root,'configs','models.yaml')):
print(f"\n** Error. The file {os.path.join(Globals.root,'configs','models.yaml')} could not be found.")
print('** Please check the location of your invokeai directory and use the --root_dir option to point to the correct path.')
print('** This script will now exit.')
sys.exit(-1)
report_model_error(opt, e)
# print(f"\n** Error. The file {os.path.join(Globals.root,'configs','models.yaml')} could not be found.")
# print('** Please check the location of your invokeai directory and use the --root_dir option to point to the correct path.')
# print('** This script will now exit.')
# sys.exit(-1)
print(f'>> {ldm.invoke.__app_name__}, version {ldm.invoke.__version__}')
print(f'>> InvokeAI runtime directory is "{Globals.root}"')
@ -574,7 +607,7 @@ def import_model(model_path:str, gen, opt, completer):
if model_path.startswith(('http:','https:','ftp:')):
model_name = import_ckpt_model(model_path, gen, opt, completer)
elif os.path.exists(model_path) and model_path.endswith(('.ckpt','.safetensors')) and os.path.isfile(model_path):
model_name = import_ckpt_model(model_path, gen, opt, completer)
model_name = import_ckpt_model(model_path, gen, opt, completer)
elif re.match('^[\w.+-]+/[\w.+-]+$',model_path):
model_name = import_diffuser_model(model_path, gen, opt, completer)
elif os.path.isdir(model_path):
@ -743,7 +776,7 @@ def del_config(model_name:str, gen, opt, completer):
if input(f'Remove {model_name} from the list of models known to InvokeAI? [y] ').strip().startswith(('n','N')):
return
delete_completely = input('Completely remove the model file or directory from disk? [n] ').startswith(('y','Y'))
gen.model_manager.del_model(model_name,delete_files=delete_completely)
gen.model_manager.commit(opt.conf)
@ -786,8 +819,8 @@ def _get_model_name(existing_names,completer,default_name:str='')->str:
model_name = input(f'Short name for this model [{default_name}]: ').strip()
if len(model_name)==0:
model_name = default_name
if not re.match('^[\w._+-]+$',model_name):
print('** model name must contain only words, digits and the characters "._+-" **')
if not re.match('^[\w._+:/-]+$',model_name):
print('** model name must contain only words, digits and the characters "._+:/-" **')
elif model_name != default_name and model_name in existing_names:
print(f'** the name {model_name} is already in use. Pick another.')
else:
@ -1097,34 +1130,6 @@ def write_commands(opt, file_path:str, outfilepath:str):
f.write('\n'.join(commands))
print(f'>> File {outfilepath} with commands created')
def report_model_error(opt:Namespace, e:Exception):
print(f'** An error occurred while attempting to initialize the model: "{str(e)}"')
print('** This can be caused by a missing or corrupted models file, and can sometimes be fixed by (re)installing the models.')
response = input('Do you want to run configure_invokeai.py to select and/or reinstall models? [y] ')
if response.startswith(('n','N')):
return
print('configure_invokeai is launching....\n')
# Match arguments that were set on the CLI
# only the arguments accepted by the configuration script are parsed
root_dir = ["--root", opt.root_dir] if opt.root_dir is not None else []
config = ["--config", opt.conf] if opt.conf is not None else []
yes_to_all = os.environ.get('INVOKE_MODEL_RECONFIGURE')
previous_args = sys.argv
sys.argv = [ 'configure_invokeai' ]
sys.argv.extend(root_dir)
sys.argv.extend(config)
if yes_to_all is not None:
sys.argv.append(yes_to_all)
import ldm.invoke.configure_invokeai as configure_invokeai
configure_invokeai.main()
print('** InvokeAI will now restart')
sys.argv = previous_args
main() # would rather do a os.exec(), but doesn't exist?
sys.exit(0)
def check_internet()->bool:
'''
Return true if the internet is reachable.

23
ldm/invoke/generator/diffusers_pipeline.py
View File

@ -544,6 +544,7 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
init_image = image_resized_to_grid_as_tensor(init_image.convert('RGB'))
init_image = init_image.to(device=device, dtype=latents_dtype)
mask = mask.to(device=device, dtype=latents_dtype)
if init_image.dim() == 3:
init_image = init_image.unsqueeze(0)
@ -562,17 +563,22 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
if mask.dim() == 3:
mask = mask.unsqueeze(0)
mask = tv_resize(mask, init_image_latents.shape[-2:], T.InterpolationMode.BILINEAR) \
latent_mask = tv_resize(mask, init_image_latents.shape[-2:], T.InterpolationMode.BILINEAR) \
.to(device=device, dtype=latents_dtype)
guidance: List[Callable] = []
if is_inpainting_model(self.unet):
# You'd think the inpainting model wouldn't be paying attention to the area it is going to repaint
# (that's why there's a mask!) but it seems to really want that blanked out.
masked_init_image = init_image * torch.where(mask < 0.5, 1, 0)
masked_latents = self.non_noised_latents_from_image(masked_init_image, device=device, dtype=latents_dtype)
# TODO: we should probably pass this in so we don't have to try/finally around setting it.
self.invokeai_diffuser.model_forward_callback = \
AddsMaskLatents(self._unet_forward, mask, init_image_latents)
AddsMaskLatents(self._unet_forward, latent_mask, masked_latents)
else:
guidance.append(AddsMaskGuidance(mask, init_image_latents, self.scheduler, noise))
guidance.append(AddsMaskGuidance(latent_mask, init_image_latents, self.scheduler, noise))
try:
result_latents, result_attention_maps = self.latents_from_embeddings(
@ -591,11 +597,20 @@ class StableDiffusionGeneratorPipeline(StableDiffusionPipeline):
output = InvokeAIStableDiffusionPipelineOutput(images=image, nsfw_content_detected=[], attention_map_saver=result_attention_maps)
return self.check_for_safety(output, dtype=conditioning_data.dtype)
def non_noised_latents_from_image(self, init_image, *, device, dtype):
def non_noised_latents_from_image(self, init_image, *, device: torch.device, dtype):
init_image = init_image.to(device=device, dtype=dtype)
with torch.inference_mode():
if device.type == 'mps':
# workaround for torch MPS bug that has been fixed in https://github.com/kulinseth/pytorch/pull/222
# TODO remove this workaround once kulinseth#222 is merged to pytorch mainline
self.vae.to('cpu')
init_image = init_image.to('cpu')
init_latent_dist = self.vae.encode(init_image).latent_dist
init_latents = init_latent_dist.sample().to(dtype=dtype) # FIXME: uses torch.randn. make reproducible!
if device.type == 'mps':
self.vae.to(device)
init_latents = init_latents.to(device)
init_latents = 0.18215 * init_latents
return init_latents

16
ldm/invoke/generator/inpaint.py
View File

@ -19,10 +19,12 @@ from ldm.util import debug_image
def infill_methods()->list[str]:
methods = list()
methods = [
"tile",
"solid",
]
if PatchMatch.patchmatch_available():
methods.append('patchmatch')
methods.append('tile')
methods.insert(0, 'patchmatch')
return methods
class Inpaint(Img2Img):
@ -182,6 +184,7 @@ class Inpaint(Img2Img):
infill_method = None,
inpaint_width=None,
inpaint_height=None,
inpaint_fill:tuple(int)=(0x7F, 0x7F, 0x7F, 0xFF),
attention_maps_callback=None,
**kwargs):
"""
@ -202,12 +205,17 @@ class Inpaint(Img2Img):
# Do infill
if infill_method == 'patchmatch' and PatchMatch.patchmatch_available():
init_filled = self.infill_patchmatch(self.pil_image.copy())
else: # if infill_method == 'tile': # Only two methods right now, so always use 'tile' if not patchmatch
elif infill_method == 'tile':
init_filled = self.tile_fill_missing(
self.pil_image.copy(),
seed = self.seed,
tile_size = tile_size
)
elif infill_method == 'solid':
solid_bg = PIL.Image.new("RGBA", init_image.size, inpaint_fill)
init_filled = PIL.Image.alpha_composite(solid_bg, init_image)
else:
raise ValueError(f"Non-supported infill type {infill_method}", infill_method)
init_filled.paste(init_image, (0,0), init_image.split()[-1])
# Resize if requested for inpainting

23
ldm/invoke/generator/txt2img2img.py
View File

@ -3,10 +3,10 @@ ldm.invoke.generator.txt2img inherits from ldm.invoke.generator
'''
import math
from diffusers.utils.logging import get_verbosity, set_verbosity, set_verbosity_error
from typing import Callable, Optional
import torch
from diffusers.utils.logging import get_verbosity, set_verbosity, set_verbosity_error
from ldm.invoke.generator.base import Generator
from ldm.invoke.generator.diffusers_pipeline import trim_to_multiple_of, StableDiffusionGeneratorPipeline, \
@ -128,18 +128,13 @@ class Txt2Img2Img(Generator):
scaled_width = width
scaled_height = height
device = self.model.device
device = self.model.device
channels = self.latent_channels
if channels == 9:
channels = 4 # we don't really want noise for all the mask channels
shape = (1, channels,
scaled_height // self.downsampling_factor, scaled_width // self.downsampling_factor)
if self.use_mps_noise or device.type == 'mps':
return torch.randn([1,
self.latent_channels,
scaled_height // self.downsampling_factor,
scaled_width // self.downsampling_factor],
dtype=self.torch_dtype(),
device='cpu').to(device)
return torch.randn(shape, dtype=self.torch_dtype(), device='cpu').to(device)
else:
return torch.randn([1,
self.latent_channels,
scaled_height // self.downsampling_factor,
scaled_width // self.downsampling_factor],
dtype=self.torch_dtype(),
device=device)
return torch.randn(shape, dtype=self.torch_dtype(), device=device)

2
ldm/invoke/model_manager.py
View File

@ -125,7 +125,7 @@ class ModelManager(object):
Set the default model. The change will not take
effect until you call model_manager.commit()
'''
assert model_name in self.models,f"unknown model '{model_name}'"
assert model_name in self.model_names(), f"unknown model '{model_name}'"
config = self.config
for model in config: