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…ention processors if no mid_block is detected
## What type of PR is this? (check all applicable)
- [ ] Refactor
- [ ] Feature
- [x] Bug Fix
- [ ] Optimization
- [ ] Documentation Update
- [ ] Community Node Submission
## Have you discussed this change with the InvokeAI team?
- [x] Yes
- [ ] No, because:
## Have you updated all relevant documentation?
- [ ] Yes
- [x] No
## Description
L2i throws an assertion error when run with `madebyollin/taesdxl` due to
it requiring a different class in diffusers to load it. This is a small
PR to update seamless and l2i to accept AutoencoderTiny models and not
throw exceptions while processing them.
## QA Instructions, Screenshots, Recordings
<img width="445" alt="Screenshot 2024-03-12 at 12 04 29 PM"
src="https://github.com/invoke-ai/InvokeAI/assets/58442074/34a17e44-d911-4fef-8fc1-71f7b688688c">
Run an sdxl pipeline using a vae that requires AutoencoderTiny and
validate that the image successfully encodes and decodes.
## Merge Plan
This PR can be merged when approved
We were stripping the file extension from file models when moving them in `_sync_model_path`. For example, `some_model.safetensors` would be moved to `some_model`, which of course breaks things.
Instead of using the model's name as the new path, use the model's path's last segment. This is the same behaviour for directories, but for files, it retains the file extension.
- No need for it to by a pydantic model. Just a class now.
- Remove ABC, it made it hard to understand what was going on as attributes were spread across the ABC and implementation. Also, there is no other implementation.
- Add tests
