* renamed single letter variables
* renamed x to meaningful variable in resnet.py
Hello @patil-suraj can you verify it
Thanks
* Reformatted using black
* renamed x to meaningful variable in resnet.py
Hello @patil-suraj can you verify it
Thanks
* reformatted the files
* modified unboundlocalerror in line 374
* removed referenced before error
* renamed single variable x -> hidden_state, p-> pad_value
Co-authored-by: Nikhil A V <nikhilav@Nikhils-MacBook-Pro.local>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Add an argument "negative_prompt"
* Fix argument order
* Fix to use TypeError instead of ValueError
* Removed needless batch_size multiplying
* Fix to multiply by batch_size
* Add truncation=True for long negative prompt
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_onnx.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_onnx.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Fix styles
* Renamed ucond_tokens to uncond_tokens
* Added description about "negative_prompt"
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* add accelerate to load models with smaller memory footprint
* remove low_cpu_mem_usage as it is reduntant
* move accelerate init weights context to modelling utils
* add test to ensure results are the same when loading with accelerate
* add tests to ensure ram usage gets lower when using accelerate
* move accelerate logic to single snippet under modelling utils and remove it from configuration utils
* format code using to pass quality check
* fix imports with isor
* add accelerate to test extra deps
* only import accelerate if device_map is set to auto
* move accelerate availability check to diffusers import utils
* format code
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Conversion script
* ran black
* ran isort
* remove unused import
* map location so everything gets loaded onto CPU before conversion
* ran black again
* Update setup.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* Don't use `load_state_dict` if torch is not installed.
* Define `SchedulerOutput` to use torch or flax arrays.
* Don't import LMSDiscreteScheduler without torch.
* Create distinct FlaxSchedulerOutput.
* Additional changes required for FlaxSchedulerMixin
* Do not import torch pipelines in Flax.
* Revert "Define `SchedulerOutput` to use torch or flax arrays."
This reverts commit f653140134b74d9ffec46d970eb46925fe3a409d.
* Prefix Flax scheduler outputs for consistency.
* make style
* FlaxSchedulerOutput is now a dataclass.
* Don't use f-string without placeholders.
* Add blank line.
* Style (docstrings)
* Add callback parameters for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>
* Lint code with `black --preview`
Signed-off-by: James R T <jamestiotio@gmail.com>
* Refactor callback implementation for Stable Diffusion pipelines
* Fix missing imports
Signed-off-by: James R T <jamestiotio@gmail.com>
* Fix documentation format
Signed-off-by: James R T <jamestiotio@gmail.com>
* Add kwargs parameter to standardize with other pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>
* Modify Stable Diffusion pipeline callback parameters
Signed-off-by: James R T <jamestiotio@gmail.com>
* Remove useless imports
Signed-off-by: James R T <jamestiotio@gmail.com>
* Change types for timestep and onnx latents
* Fix docstring style
* Return decode_latents and run_safety_checker back into __call__
* Remove unused imports
* Add intermediate state tests for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>
* Fix intermediate state tests for Stable Diffusion pipelines
Signed-off-by: James R T <jamestiotio@gmail.com>
Signed-off-by: James R T <jamestiotio@gmail.com>
* Allow resolutions that are not multiples of 64
* ran black
* fix bug
* add test
* more explanation
* more comments
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* initial commit
* make UNet stream capturable
* try to fix noise_pred value
* remove cuda graph and keep NB
* non blocking unet with PNDMScheduler
* make timesteps np arrays for pndm scheduler
because lists don't get formatted to tensors in `self.set_format`
* make max async in pndm
* use channel last format in unet
* avoid moving timesteps device in each unet call
* avoid memcpy op in `get_timestep_embedding`
* add `channels_last` kwarg to `DiffusionPipeline.from_pretrained`
* update TODO
* replace `channels_last` kwarg with `memory_format` for more generality
* revert the channels_last changes to leave it for another PR
* remove non_blocking when moving input ids to device
* remove blocking from all .to() operations at beginning of pipeline
* fix merging
* fix merging
* model can run in other precisions without autocast
* attn refactoring
* Revert "attn refactoring"
This reverts commit 0c70c0e189cd2c4d8768274c9fcf5b940ee310fb.
* remove restriction to run conv_norm in fp32
* use `baddbmm` instead of `matmul`for better in attention for better perf
* removing all reshapes to test perf
* Revert "removing all reshapes to test perf"
This reverts commit 006ccb8a8c6bc7eb7e512392e692a29d9b1553cd.
* add shapes comments
* hardcore whats needed for jitting
* Revert "hardcore whats needed for jitting"
This reverts commit 2fa9c698eae2890ac5f8e367ca80532ecf94df9a.
* Revert "remove restriction to run conv_norm in fp32"
This reverts commit cec592890c32da3d1b78d38b49e4307aedf459b9.
* revert using baddmm in attention's forward
* cleanup comment
* remove restriction to run conv_norm in fp32. no quality loss was noticed
This reverts commit cc9bc1339c998ebe9e7d733f910c6d72d9792213.
* add more optimizations techniques to docs
* Revert "add shapes comments"
This reverts commit 31c58eadb8892f95478cdf05229adf678678c5f4.
* apply suggestions
* make quality
* apply suggestions
* styling
* `scheduler.timesteps` are now arrays so we dont need .to()
* remove useless .type()
* use mean instead of max in `test_stable_diffusion_inpaint_pipeline_k_lms`
* move scheduler timestamps to correct device if tensors
* add device to `set_timesteps` in LMSD scheduler
* `self.scheduler.set_timesteps` now uses device arg for schedulers that accept it
* quick fix
* styling
* remove kwargs from schedulers `set_timesteps`
* revert to using max in K-LMS inpaint pipeline test
* Revert "`self.scheduler.set_timesteps` now uses device arg for schedulers that accept it"
This reverts commit 00d5a51e5c20d8d445c8664407ef29608106d899.
* move timesteps to correct device before loop in SD pipeline
* apply previous fix to other SD pipelines
* UNet now accepts tensor timesteps even on wrong device, to avoid errors
- it shouldnt affect performance if timesteps are alrdy on correct device
- it does slow down performance if they're on the wrong device
* fix pipeline when timesteps are arrays with strides
* correcting the beta value assignment
* updating DDIM and LMSDiscreteFlax schedulers
* bringing back the changes that were lost as part of main branch merge
* Replace deprecation warning f-string with class name.
When `__repr__` is invoked in the instance serialization of
`config_dict` fails, because it contains `kwargs` of type `<class
inspect._empty>`.
* Revert "Replace deprecation warning f-string with class name."
This reverts commit 1c4eb8cb104374bd84e43865fc3865862473799c.
* Do not attempt to register `"kwargs"` as an attribute.
Otherwise serialization could fail.
This may happen for other attributes, so we should create a better
solution.
* pytorch only schedulers
* fix style
* remove match_shape
* pytorch only ddpm
* remove SchedulerMixin
* remove numpy from karras_ve
* fix types
* remove numpy from lms_discrete
* remove numpy from pndm
* fix typo
* remove mixin and numpy from sde_vp and ve
* remove remaining tensor_format
* fix style
* sigmas has to be torch tensor
* removed set_format in readme
* remove set format from docs
* remove set_format from pipelines
* update tests
* fix typo
* continue to use mixin
* fix imports
* removed unsed imports
* match shape instead of assuming image shapes
* remove import typo
* update call to add_noise
* use math instead of numpy
* fix t_index
* removed commented out numpy tests
* timesteps needs to be discrete
* cast timesteps to int in flax scheduler too
* fix device mismatch issue
* small fix
* Update src/diffusers/schedulers/scheduling_pndm.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
* WIP: flax FlaxDiffusionPipeline & FlaxStableDiffusionPipeline
* todo comment
* Fix imports
* Fix imports
* add dummies
* Fix empty init
* make pipeline work
* up
* Allow dtype to be overridden on model load.
This may be a temporary solution until #567 is addressed.
* Convert params to bfloat16 or fp16 after loading.
This deals with the weights, not the model.
* Use Flax schedulers (typing, docstring)
* PNDM: replace control flow with jax functions.
Otherwise jitting/parallelization don't work properly as they don't know
how to deal with traced objects.
I temporarily removed `step_prk`.
* Pass latents shape to scheduler set_timesteps()
PNDMScheduler uses it to reserve space, other schedulers will just
ignore it.
* Wrap model imports inside availability checks.
* Optionally return state in from_config.
Useful for Flax schedulers.
* Do not convert model weights to dtype.
* Re-enable PRK steps with functional implementation.
Values returned still not verified for correctness.
* Remove left over has_state var.
* make style
* Apply suggestion list -> tuple
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Apply suggestion list -> tuple
Co-authored-by: Suraj Patil <surajp815@gmail.com>
* Remove unused comments.
* Use zeros instead of empty.
Co-authored-by: Mishig Davaadorj <dmishig@gmail.com>
Co-authored-by: Mishig Davaadorj <mishig.davaadorj@coloradocollege.edu>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Patrick von Platen