* update
* fix
* non_blocking; handle parameters and buffers
* update
* Group offloading with cuda stream prefetching (#10516)
* cuda stream prefetch
* remove breakpoints
* update
* copy model hook implementation from pab
* update; ~very workaround based implementation but it seems to work as expected; needs cleanup and rewrite
* more workarounds to make it actually work
* cleanup
* rewrite
* update
* make sure to sync current stream before overwriting with pinned params
not doing so will lead to erroneous computations on the GPU and cause bad results
* better check
* update
* remove hook implementation to not deal with merge conflict
* re-add hook changes
* why use more memory when less memory do trick
* why still use slightly more memory when less memory do trick
* optimise
* add model tests
* add pipeline tests
* update docs
* add layernorm and groupnorm
* address review comments
* improve tests; add docs
* improve docs
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* apply suggestions from code review
* update tests
* apply suggestions from review
* enable_group_offloading -> enable_group_offload for naming consistency
* raise errors if multiple offloading strategies used; add relevant tests
* handle .to() when group offload applied
* refactor some repeated code
* remove unintentional change from merge conflict
* handle .cuda()
---------
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update
* update
* make style
* remove dynamo disable
* add coauthor
Co-Authored-By: Dhruv Nair <dhruv.nair@gmail.com>
* update
* update
* update
* update mixin
* add some basic tests
* update
* update
* non_blocking
* improvements
* update
* norm.* -> norm
* apply suggestions from review
* add example
* update hook implementation to the latest changes from pyramid attention broadcast
* deinitialize should raise an error
* update doc page
* Apply suggestions from code review
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* update docs
* update
* refactor
* fix _always_upcast_modules for asym ae and vq_model
* fix lumina embedding forward to not depend on weight dtype
* refactor tests
* add simple lora inference tests
* _always_upcast_modules -> _precision_sensitive_module_patterns
* remove todo comments about review; revert changes to self.dtype in unets because .dtype on ModelMixin should be able to handle fp8 weight case
* check layer dtypes in lora test
* fix UNet1DModelTests::test_layerwise_upcasting_inference
* _precision_sensitive_module_patterns -> _skip_layerwise_casting_patterns based on feedback
* skip test in NCSNppModelTests
* skip tests for AutoencoderTinyTests
* skip tests for AutoencoderOobleckTests
* skip tests for UNet1DModelTests - unsupported pytorch operations
* layerwise_upcasting -> layerwise_casting
* skip tests for UNetRLModelTests; needs next pytorch release for currently unimplemented operation support
* add layerwise fp8 pipeline test
* use xfail
* Apply suggestions from code review
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
* add assertion with fp32 comparison; add tolerance to fp8-fp32 vs fp32-fp32 comparison (required for a few models' test to pass)
* add note about memory consumption on tesla CI runner for failing test
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* fix the Positinoal Embedding bug in 2K model;
* Change the default model to the BF16 one for more stable training and output
* make style
* substract buffer size
* add compute_module_persistent_sizes
---------
Co-authored-by: yiyixuxu <yixu310@gmail.com>
* remove 2 shapes from SDFunctionTesterMixin::test_vae_tiling
* combine freeu enable/disable test to reduce many inference runs
* remove low signal unet test for signature
* remove low signal embeddings test
* remove low signal progress bar test from PipelineTesterMixin
* combine ip-adapter single and multi tests to save many inferences
* fix broken tests
* Update tests/pipelines/test_pipelines_common.py
* Update tests/pipelines/test_pipelines_common.py
* add progress bar tests
* Fix sharding when no device_map is passed
* style
* add tests
* align
* add docstring
* format
---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* feat: support saving a model in sharded checkpoints.
* feat: make loading of sharded checkpoints work.
* add tests
* cleanse the loading logic a bit more.
* more resilience while loading from the Hub.
* parallelize shard downloads by using snapshot_download()/
* default to a shard size.
* more fix
* Empty-Commit
* debug
* fix
* uality
* more debugging
* fix more
* initial comments from Benjamin
* move certain methods to loading_utils
* add test to check if the correct number of shards are present.
* add a test to check if loading of sharded checkpoints from the Hub is okay
* clarify the unit when passed as an int.
* use hf_hub for sharding.
* remove unnecessary code
* remove unnecessary function
* lucain's comments.
* fixes
* address high-level comments.
* fix test
* subfolder shenanigans./
* Update src/diffusers/utils/hub_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>
* remove _huggingface_hub_version as not needed.
* address more feedback.
* add a test for local_files_only=True/
* need hf hub to be at least 0.23.2
* style
* final comment.
* clean up subfolder.
* deal with suffixes in code.
* _add_variant default.
* use weights_name_pattern
* remove add_suffix_keyword
* clean up downloading of sharded ckpts.
* don't return something special when using index.json
* fix more
* don't use bare except
* remove comments and catch the errors better
* fix a couple of things when using is_file()
* empty
---------
Co-authored-by: Lucain <lucainp@gmail.com>
* Add Ascend NPU support for SDXL fine-tuning and fix the model saving bug when using DeepSpeed.
* fix check code quality
* Decouple the NPU flash attention and make it an independent module.
* add doc and unit tests for npu flash attention.
---------
Co-authored-by: mhh001 <mahonghao1@huawei.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* feat: explicitly tag to diffusers when using push_to_hub
* remove tags.
* reset repo.
* Apply suggestions from code review
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* fix: tests
* fix: push_to_hub behaviour for tagging from save_pretrained
* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>
* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>
* import fixes.
* add library name to existing model card.
* add: standalone test for generate_model_card
* fix tests for standalone method
* moved library_name to a better place.
* merge create_model_card and generate_model_card.
* fix test
* address lucain's comments
* fix return identation
* Apply suggestions from code review
Co-authored-by: Lucain <lucainp@gmail.com>
* address further comments.
* Update src/diffusers/pipelines/pipeline_utils.py
Co-authored-by: Lucain <lucainp@gmail.com>
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Lucain <lucainp@gmail.com>
* utils and test modifications to enable device agnostic testing
* device for manual seed in unet1d
* fix generator condition in vae test
* consistency changes to testing
* make style
* add device agnostic testing changes to source and one model test
* make dtype check fns private, log cuda fp16 case
* remove dtype checks from import utils, move to testing_utils
* adding tests for most model classes and one pipeline
* fix vae import
* consistency decoder
* rename
* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Update src/diffusers/pipelines/consistency_models/pipeline_consistency_models.py
* uP
* Apply suggestions from code review
* uP
* uP
* uP
---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* make safetensors default
* set default save method as safetensors
* update tests
* update to support saving safetensors
* update test to account for safetensors default
* update example tests to use safetensors
* update example to support safetensors
* update unet tests for safetensors
* fix failing loader tests
* fix qc issues
* fix pipeline tests
* fix example test
---------
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
