Fix docker tmp/ and extensions/ handling for docker.

Add upscale latent, VAE, styles as new axis options to X/Y plot

add an option to samplers for skipping next to last sigma

Add a workaround patch for DPM2 a issue

Set httpcore version in requirements - fixes #4833

Training fixes for MPS

Improve InvokeAI cross attention reliability and speed when using MPS for large images

fix hints file typo

fix: xformers

Check if q.shape[0] * q.shape[1] is 2**18 or larger and use the lower memory usage MPS optimization if it is. This should prevent most crashes that were occurring at certain resolutions (e.g. 1024x1024, 2048x512, 512x2048).

Also included is a change to check slice_size and prevent it from being divisible by 4096 which also results in a crash. Otherwise a crash can occur at 1024x512 or 512x1024 resolution.

Adds upscale latent space for hires., VAE, and Styles as new axis options to the X/Y plot.

When saving training results with torch.save(), an exception is thrown:
"RuntimeError: Can't call numpy() on Tensor that requires grad. Use tensor.detach().numpy() instead."

So for MPS, check if Tensor.requires_grad and detach() if necessary.

DPM2 a and DPM2 a Karras samplers are both affected by an issue described by https://github.com/AUTOMATIC1111/stable-diffusion-webui/issues/3483 and can be resolved by a workaround suggested by the k-diffusion author at https://github.com/crowsonkb/k-diffusion/issues/43#issuecomment-1305195666

LDSR improvements - cache / optimization / opt_channelslast

Fix token counter color on dark theme

Fix WebUI not working inside of iframes

Support changing checkpoint and vae through override_settings

Add Clear Prompt button to roll_col 

Update SD Upscaler to include user selectable Scale Factor

Atomically rename saved image to avoid race condition with other processes

Update launch.py

allow randomized seeds in prompt_matrix

Add option to avoid sending size between interfaces.