Merge branch 'dev' of https://github.com/AUTOMATIC1111/stable-diffusion-webui into tomesd

    steps:

      - name: Checkout Code

        uses: actions/checkout@v3

      - name: Set up Python 3.10

        uses: actions/setup-python@v4

      - uses: actions/setup-python@v4

        with:

          python-version: 3.10.6

          cache: pip

          cache-dependency-path: |

            **/requirements*txt

      - name: Install PyLint

        run: | 

          python -m pip install --upgrade pip

          pip install pylint

      # This lets PyLint check to see if it can resolve imports

      - name: Install dependencies

        run: |

          export COMMANDLINE_ARGS="--skip-torch-cuda-test --exit"

          python launch.py

      - name: Analysing the code with pylint

        run: |

          pylint $(git ls-files '*.py')

          python-version: 3.11

          # NB: there's no cache: pip here since we're not installing anything

          #     from the requirements.txt file(s) in the repository; it's faster

          #     not to have GHA download an (at the time of writing) 4 GB cache

          #     of PyTorch and other dependencies.

      - name: Install Ruff

        run: pip install ruff==0.0.265

      - name: Run Ruff

        run: ruff .

# The rest are currently disabled pending fixing of e.g. installing the torch dependency.

#      - name: Install PyLint

#        run: |

#          python -m pip install --upgrade pip

#          pip install pylint

#      # This lets PyLint check to see if it can resolve imports

#      - name: Install dependencies

#        run: |

#          export COMMANDLINE_ARGS="--skip-torch-cuda-test --exit"

#          python launch.py

#      - name: Analysing the code with pylint

#        run: |

#          pylint $(git ls-files '*.py')

          cache: pip

          cache-dependency-path: |

            **/requirements*txt

            launch.py

      - name: Run tests

        run: python launch.py --tests test --no-half --disable-opt-split-attention --use-cpu all --skip-torch-cuda-test

        env:

          PIP_DISABLE_PIP_VERSION_CHECK: "1"

          PIP_PROGRESS_BAR: "off"

          TORCH_INDEX_URL: https://download.pytorch.org/whl/cpu

          WEBUI_LAUNCH_LIVE_OUTPUT: "1"

      - name: Upload main app stdout-stderr

        uses: actions/upload-artifact@v3

        if: always()

## Upcoming 1.2.0

### Features:

 * do not load wait for stable diffusion model to load at startup

 * add filename patterns: [denoising]

 * directory hiding for extra networks: dirs starting with . will hide their cards on extra network tabs unless specifically searched for

 * Lora: for the `<...>` text in prompt, use name of Lora that is in the metdata of the file, if present, instead of filename (both can be used to activate lora)

 * Lora: read infotext params from kohya-ss's extension parameters if they are present and if his extension is not active

 * Lora: Fix some Loras not working (ones that have 3x3 convolution layer)

 * Lora: add an option to use old method of applying loras (producing same results as with kohya-ss)

 * add version to infotext, footer and console output when starting

 * add links to wiki for filename pattern settings

 * add extended info for quicksettings setting and use multiselect input instead of a text field

### Minor:

 * gradio bumped to 3.29.0

 * torch bumped to 2.0.1

 * --subpath option for gradio for use with reverse proxy

 * linux/OSX: use existing virtualenv if already active (the VIRTUAL_ENV environment variable)

 * possible frontend optimization: do not apply localizations if there are none

 * Add extra `None` option for VAE in XYZ plot

 * print error to console when batch processing in img2img fails

 * create HTML for extra network pages only on demand

 * allow directories starting with . to still list their models for lora, checkpoints, etc

 * put infotext options into their own category in settings tab

 * do not show licenses page when user selects Show all pages in settings

### Extensions:

 * Tooltip localization support

 * Add api method to get LoRA models with prompt

### Bug Fixes:

 * re-add /docs endpoint

 * fix gamepad navigation

 * make the lightbox fullscreen image function properly

 * fix squished thumbnails in extras tab

 * keep "search" filter for extra networks when user refreshes the tab (previously it showed everthing after you refreshed)

 * fix webui showing the same image if you configure the generation to always save results into same file

 * fix bug with upscalers not working properly

 * Fix MPS on PyTorch 2.0.1, Intel Macs

 * make it so that custom context menu from contextMenu.js only disappears after user's click, ignoring non-user click events

 * prevent Reload UI button/link from reloading the page when it's not yet ready

## 1.1.1

### Bug Fixes:

 * fix an error that prevents running webui on torch<2.0 without --disable-safe-unpickle

        x_t = None

        logs = None

        for n in range(n_runs):

        for _ in range(n_runs):

            if custom_shape is not None:

                x_t = torch.randn(1, custom_shape[1], custom_shape[2], custom_shape[3]).to(model.device)

                x_t = repeat(x_t, '1 c h w -> b c h w', b=custom_shape[0])

        diffusion_steps = int(steps)

        eta = 1.0

        down_sample_method = 'Lanczos'

        gc.collect()

        if torch.cuda.is_available:

def get_cond(selected_path):

    example = dict()

    example = {}

    up_f = 4

    c = selected_path.convert('RGB')

    c = torch.unsqueeze(torchvision.transforms.ToTensor()(c), 0)

@torch.no_grad()

def make_convolutional_sample(batch, model, custom_steps=None, eta=1.0, quantize_x0=False, custom_shape=None, temperature=1., noise_dropout=0., corrector=None,

                              corrector_kwargs=None, x_T=None, ddim_use_x0_pred=False):

    log = dict()

    log = {}

    z, c, x, xrec, xc = model.get_input(batch, model.first_stage_key,

                                        return_first_stage_outputs=True,

        x_sample_noquant = model.decode_first_stage(sample, force_not_quantize=True)

        log["sample_noquant"] = x_sample_noquant

        log["sample_diff"] = torch.abs(x_sample_noquant - x_sample)

    except:

    except Exception:

        pass

    log["sample"] = x_sample

from modules.upscaler import Upscaler, UpscalerData

from ldsr_model_arch import LDSR

from modules import shared, script_callbacks

import sd_hijack_autoencoder, sd_hijack_ddpm_v1

import sd_hijack_autoencoder  # noqa: F401

import sd_hijack_ddpm_v1  # noqa: F401

class UpscalerLDSR(Upscaler):