Lincoln Stein e93f4d632d [util] Add generic torch device class (#6174) ... * introduce new abstraction layer for GPU devices * add unit test for device abstraction * fix ruff * convert TorchDeviceSelect into a stateless class * move logic to select context-specific execution device into context API * add mock hardware environments to pytest * remove dangling mocker fixture * fix unit test for running on non-CUDA systems * remove unimplemented get_execution_device() call * remove autocast precision * Multiple changes: 1. Remove TorchDeviceSelect.get_execution_device(), as well as calls to context.models.get_execution_device(). 2. Rename TorchDeviceSelect to TorchDevice 3. Added back the legacy public API defined in `invocation_api`, including choose_precision(). 4. Added a config file migration script to accommodate removal of precision=autocast. * add deprecation warnings to choose_torch_device() and choose_precision() * fix test crash * remove app_config argument from choose_torch_device() and choose_torch_dtype() --------- Co-authored-by: Lincoln Stein <lstein@gmail.com>		2024-04-15 13:12:49 +00:00
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app	[util] Add generic torch device class (#6174)	2024-04-15 13:12:49 +00:00
assets	feat(api): chore: pydantic & fastapi upgrade	2023-10-17 14:59:25 +11:00
backend	[util] Add generic torch device class (#6174)	2024-04-15 13:12:49 +00:00
configs	fix(mm): add missing v2-midas-inference.yaml	2024-03-27 07:48:54 -04:00
frontend	perf(ui): memoize infill components	2024-04-15 22:50:54 +10:00
invocation_api	Remove support for Prompt-to-Prompt cross-attention control (aka .swap()). This feature is not widely used. It does not work with SDXL and is incompatible with IP-Adapter and regional prompting. The implementation is also intertwined with both text embedding and the UNet attention layers, resulting in a high maintenance burden. For all of these reasons, we have decided to drop support.	2024-04-09 10:57:02 -04:00
version	chore: v4.0.4	2024-04-06 15:15:16 +11:00
__init__.py