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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diffusion	Fix the padding behavior when max-pooling regional IP-Adapter masks to mirror the downscaling behavior of SD and SDXL. Prior to this change, denoising with input latent dimensions that were not evenly divisible by 8 would raise an exception.	2024-04-09 16:50:43 -04:00
schedulers	make model manager v2 ready for PR review	2024-03-01 10:42:33 +11:00
__init__.py	Remove unused code for attention map saving.	2024-03-02 08:25:41 -05:00
diffusers_pipeline.py	[util] Add generic torch device class (#6174)	2024-04-15 13:12:49 +00:00
seamless.py	fix(nodes): workaround seamless multi gpu error #6010	2024-03-29 08:56:38 +11:00