GitLab

* ⚙️chore(train_controlnet) fix typo in logger message

* ⚙️chore(models) refactor modules order; make them the same as calling order

When printing the BasicTransformerBlock to stdout, I think it's crucial that the attributes order are shown in proper order. And also previously the "3. Feed Forward" comment was not making sense. It should have been close to self.ff but it's instead next to self.norm3

* correct many tests

* remove bogus file

* make style

* correct more tests

* finish tests

* fix one more

* make style

* make unclip deterministic

* ⚙

️chore(models/attention) reorganize comments in BasicTransformerBlock class

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* fix slow tests

* uP

* add use_karras_sigmas option

thanks @Stax124

* fix sigma_min/max from scheduler.sigmas

* add docstring

* revert to use k_diffusion_model.sigma, to(device)

* add integration test

* make style

* add load textual inversion embeddings draft

* fix quality

* fix typo

* make fix copies

* move to textual inversion mixin

* make it accept from sd-concept library

* accept list of paths to embeddings

* fix styling of stable diffusion pipeline

* add dummy TextualInversionMixin

* add docstring to textualinversionmixin

* add load textual inversion embeddings draft

* fix quality

* fix typo

* make fix copies

* move to textual inversion mixin

* make it accept from sd-concept library

* accept list of paths to embeddings

* fix styling of stable diffusion pipeline

* add dummy TextualInversionMixin

* add docstring to textualinversionmixin

* add case for parsing embedding from auto1111 UI format
Co-authored-by: Evan Jones <evan.a.jones3@gmail.com>
Co-authored-by: Ana Tamais <aninhamoraestamais@gmail.com>

* fix style after rebase

* move textual inversion mixin to loaders

* move mixin inheritance to DiffusionPipeline from StableDiffusionPipeline)

* update dummy class name

* addressed allo comments

* fix old dangling import

* fix style

* proposal

* remove bogus

* Apply suggestions from code review
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>

* finish

* make style

* up

* fix code quality

* fix code quality - again

* fix code quality - 3

* fix alt diffusion code quality

* fix model editing pipeline

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Finish

---------
Co-authored-by: Evan Jones <evan.a.jones3@gmail.com>
Co-authored-by: Ana Tamais <aninhamoraestamais@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Helper function to disable custom attention processors.

* Restore code deleted by mistake.

* Format

* Fix modeling_text_unet copy.

* TIME first commit

* styling.

* styling 2.

* fixes; tests

* apply styling and doc fix.

* remove sups.

* fixes

* remove temp file

* move augmentations to const

* added doc entry

* code quality

* customize augmentations

* quality

* quality

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add contronet flax

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>

* [Tests] Correct PT2

* correct more

* move versatile to nightly

* up

* up

* again

* Apply suggestions from code review

* add image_processor

---------
Co-authored-by: yiyixuxu <yixu310@gmail,com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Add support for different model prediction types in DDIMInverseScheduler
Resolve alpha_prod_t_prev index issue for final step of inversion

* Fix old bug introduced when prediction type is "sample"

* Add support for sample clipping for numerical stability and deprecate old kwarg

* Detach sample, alphas, betas

Derive predicted noise from model output before dist. regularization

Style cleanup

* Log loss for debugging

* Revert "Log loss for debugging"

This reverts commit 76ea9c856f99f4c8eca45a0b1801593bb982584b.

* Add comments

* Add inversion equivalence test

* Add expected data for Pix2PixZero pipeline tests with SD 2

* Update tests/pipelines/stable_diffusion/test_stable_diffusion_pix2pix_zero.py

* Remove cruft and add more explanatory comments

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* support for List[ControlNetModel] on init()

* Add to support for multiple ControlNetCondition

* rename conditioning_scale to scale

* scaling bugfix

* Manually merge `MultiControlNet` #2621
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* cleanups
- don't expose ControlNetCondition
- move scaling to ControlNetModel

* make style error correct

* remove ControlNetCondition to reduce code diff

* refactoring image/cond_scale

* add explain for `images`

* Add docstrings

* all fast-test passed

* Add a slow test

* nit

* Apply suggestions from code review

* small precision fix

* nits

MultiControlNet -> MultiControlNetModel - Matches existing naming a bit
closer

MultiControlNetModel inherit from model utils class - Don't have to
re-write fp16 test

Skip tests that save multi controlnet pipeline - Clearer than changing
test body

Don't auto-batch the number of input images to the number of controlnets.
We generally like to require the user to pass the expected number of
inputs. This simplifies the processing code a bit more

Use existing image pre-processing code a bit more. We can rely on the
existing image pre-processing code and keep the inference loop a bit
simpler.

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: William Berman <WLBberman@gmail.com>

* [attention] Fix attention

* fix

* correct

* Support non square image generation for StableDiffusionSAGPipeline

* Fix style

* [Onnx] add Stable Diffusion Upscale pipeline

* add a test for the OnnxStableDiffusionUpscalePipeline

* check for VAE config before adjusting scaling factor

* update test assertions, lint fixes

* run fix-copies target

* switch test checkpoint to one hosted on huggingface

* partially restore attention mask

* reshape embeddings after running text encoder

* add longer nightly test for ONNX upscale pipeline

* use package import to fix tests

* fix scheduler compatibility and class labels dtype

* use more precise type

* remove LMS from fast tests

* lookup latent and timestamp types

* add docs for ONNX upscaling, rename lookup table

* replace deprecated pipeline names in ONNX docs

* attend and excite batch test causing timeouts

* move test num_images_per_prompt to pipeline mixin

* style

* prompt_key -> self.batch_params

* Tiled VAE for high-res text2img and img2img

* vae tiling, fix formatting

* enable_vae_tiling API and tests

* tiled vae docs, disable tiling for images that would have only one tile

* tiled vae tests, use channels_last memory format

* tiled vae tests, use smaller test image

* tiled vae tests, remove tiling test from fast tests

* up

* up

* make style

* Apply suggestions from code review

* Apply suggestions from code review

* Apply suggestions from code review

* make style

* improve naming

* finish

* apply suggestions

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* up

---------
Co-authored-by: Ilmari Heikkinen <ilmari@fhtr.org>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* add scaffold
- copied convert_controlnet_to_diffusers.py from
convert_original_stable_diffusion_to_diffusers.py

* Add support to load ControlNet (WIP)
- this makes Missking Key error on ControlNetModel

* Update to convert ControlNet without error msg
- init impl for StableDiffusionControlNetPipeline
- init impl for ControlNetModel

* cleanup of commented out

* split create_controlnet_diffusers_config()
from create_unet_diffusers_config()

- add config: hint_channels

* Add input_hint_block, input_zero_conv and
middle_block_out
- this makes missing key error on loading model

* add unet_2d_blocks_controlnet.py
- copied from unet_2d_blocks.py as impl CrossAttnDownBlock2D,DownBlock2D
- this makes missing key error on loading model

* Add loading for input_hint_block, zero_convs
and middle_block_out

- this makes no error message on model loading

* Copy from UNet2DConditionalModel except __init__

* Add ultra primitive test for ControlNetModel
inference

* Support ControlNetModel inference
- without exceptions

* copy forward() from UNet2DConditionModel

* Impl ControlledUNet2DConditionModel inference
- test_controlled_unet_inference passed

* Frozen weight & biases for training

* Minimized version of ControlNet/ControlledUnet
- test_modules_controllnet.py passed

* make style

* Add support model loading for minimized ver

* Remove all previous version files

* from_pretrained and inference test passed

* copied from pipeline_stable_diffusion.py
except `__init__()`

* Impl pipeline, pixel match test (almost) passed.

* make style

* make fix-copies

* Fix to add import ControlNet blocks
for `make fix-copies`

* Remove einops dependency

* Support  np.ndarray, PIL.Image for controlnet_hint

* set default config file as lllyasviel's

* Add support grayscale (hw) numpy array

* Add and update docstrings

* add control_net.mdx

* add control_net.mdx to toctree

* Update copyright year

* Fix to add PIL.Image RGB->BGR conversion
- thanks @Mystfit

* make fix-copies

* add basic fast test for controlnet

* add slow test for controlnet/unet

* Ignore down/up_block len check on ControlNet

* add a copy from test_stable_diffusion.py

* Accept controlnet_hint is None

* merge pipeline_stable_diffusion.py diff

* Update class name to SDControlNetPipeline

* make style

* Baseline fast test almost passed (w long desc)

* still needs investigate.

Following didn't passed descriped in TODO comment:
- test_stable_diffusion_long_prompt
- test_stable_diffusion_no_safety_checker

Following didn't passed same as stable_diffusion_pipeline:
- test_attention_slicing_forward_pass
- test_inference_batch_single_identical
- test_xformers_attention_forwardGenerator_pass
these seems come from calc accuracy.

* Add note comment related vae_scale_factor

* add test_stable_diffusion_controlnet_ddim

* add assertion for vae_scale_factor != 8

* slow test of pipeline almost passed
Failed: test_stable_diffusion_pipeline_with_model_offloading
- ImportError: `enable_model_offload` requires `accelerate v0.17.0` or higher

but currently latest version == 0.16.0

* test_stable_diffusion_long_prompt passed

* test_stable_diffusion_no_safety_checker passed

- due to its model size, move to slow test

* remove PoC test files

* fix num_of_image, prompt length issue add add test

* add support List[PIL.Image] for controlnet_hint

* wip

* all slow test passed

* make style

* update for slow test

* RGB(PIL)->BGR(ctrlnet) conversion

* fixes

* remove manual num_images_per_prompt test

* add document

* add `image` argument docstring

* make style

* Add line to correct conversion

* add controlnet_conditioning_scale (aka control_scales
strength)

* rgb channel ordering by default

* image batching logic

* Add control image descriptions for each checkpoint

* Only save controlnet model in conversion script

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py

typo
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* Update docs/source/en/api/pipelines/stable_diffusion/control_net.mdx
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* add gerated image example

* a depth mask -> a depth map

* rename control_net.mdx to controlnet.mdx

* fix toc title

* add ControlNet abstruct and link

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_controlnet.py
Co-authored-by: dqueue <dbyqin@gmail.com>

* remove controlnet constructor arguments re: @patrickvonplaten

* [integration tests] test canny

* test_canny fixes

* [integration tests] test_depth

* [integration tests] test_hed

* [integration tests] test_mlsd

* add channel order config to controlnet

* [integration tests] test normal

* [integration tests] test_openpose test_scribble

* change height and width to default to conditioning image

* [integration tests] test seg

* style

* test_depth fix

* [integration tests] size fixes

* [integration tests] cpu offloading

* style

* generalize controlnet embedding

* fix conversion script

* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/controlnet.mdx
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Style adapted to the documentation of pix2pix

* merge main by hand

* style

* [docs] controlling generation doc nits

* correct some things

* add: controlnetmodel to autodoc.

* finish docs

* finish

* finish 2

* correct images

* finish controlnet

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* uP

* upload model

* up

* up

---------
Co-authored-by: William Berman <WLBberman@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>
Co-authored-by: dqueue <dbyqin@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* attend and excite batch test causing timeouts

* PipelineTesterMixin argument configuration refactor

* error message text re: @yiyixuxu

* remove eta re: @patrickvonplaten

* [Tests] Fix slow tests

* [Tests] Fix slow tsets

* attend and excite batch test causing timeouts

* pix2pix tests, no write to fs

* Skip variant tests (UNet1d, UNetRL) on mps.

mish op not yet supported.

* Exclude a couple of panorama tests on mps

They are too slow for fast CI.

* Exclude mps panorama from more tests.

* mps: exclude all fast panorama tests as they keep failing.

* add MultiDiffusionPanorama pipeline

* fix docs naming

* update pipeline name, remove redundant tests

* apply styling.

* debugging information.

* fix: assertion values.

* fix-copies.

* update docs

* update docs

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* add

* finish

* add tests

* add tests

* up

* up

* pull from main

* uP

* Apply suggestions from code review

* finish

* Update docs/source/en/_toctree.yml
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* finish

* clean docs

* next

* next

* Apply suggestions from code review
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* up

* up

---------
Co-authored-by: Suraj Patil <surajp815@gmail.com>
Co-authored-by: Pedro Cuenca <pedro@huggingface.co>

* fix: slow tests.

* retrieving the slices.

* fix: assertion.

* debugging.

* debugging.

* debugging

* debugging.

* debugging

* debugging.

* debugging.

* debugging

* debugging

* change debugging.

* change debugging.

* fix: tests for pix2pix zero.

* enable_model_offload PoC

It's surprisingly more involved than expected, see comments in the PR.

* Rename final_offload_hook

* Invoke the vae forward hook manually.

* Completely remove decoder.

* Style

* apply_forward_hook decorator

* Rename method.

* Style

* Copy enable_model_cpu_offload

* Fix copies.

* Remove comment.

* Fix copies

* Missing import

* Fix doc-builder style.

* Merge main and fix again.

* Add docs

* Fix docs.

* Add a couple of tests.

* style

* Add Stable Diffusion Sw/ elf-Attention Guidance

* Modify __init__.py

* Register attention storing processor

* Update pipeline_stable_diffusion_sag.py

* Editing default value

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update dummy_torch_and_transformers_objects.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update pipeline_stable_diffusion_sag.py

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_sag.py
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Create test_stable_diffusion_sag.py

* Create self_attention_guidance.py

* Update pipeline_stable_diffusion_sag.py

* Update test_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Rename self_attention_guidance.py to self_attention_guidance.mdx

* Update self_attention_guidance.mdx

* Update self_attention_guidance.mdx

* Update _toctree.yml

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Fixing order

* Update pipeline_stable_diffusion_sag.py

* fixing import order

* fix order

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* Naming change

* Noting pred_x0

* Adding some fast tests

* Update pipeline_stable_diffusion_sag.py

* Update test_stable_diffusion_sag.py

* Update test_stable_diffusion_sag.py

* Update test_stable_diffusion_sag.py

* Update docs/source/en/api/pipelines/stable_diffusion/self_attention_guidance.mdx

* implement gaussian_blur

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

* fix tests

* Update pipeline_stable_diffusion_sag.py

* Update pipeline_stable_diffusion_sag.py

---------
Co-authored-by: Patrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: Will Berman <wlbberman@gmail.com>

* add: support for BLIP generation.

* add: support for editing synthetic images.

* remove unnecessary comments.

* add inits and run make fix-copies.

* version change of diffusers.

* fix: condition for loading the captioner.

* default conditions_input_image to False.

* guidance_amount -> cross_attention_guidance_amount

* fix inputs to check_inputs()

* fix: attribute.

* fix: prepare_attention_mask() call.

* debugging.

* better placement of references.

* remove torch.no_grad() decorations.

* put torch.no_grad() context before the first denoising loop.

* detach() latents before decoding them.

* put deocding in a torch.no_grad() context.

* add reconstructed image for debugging.

* no_grad(0

* apply formatting.

* address one-off suggestions from the draft PR.

* back to torch.no_grad() and add more elaborate comments.

* refactor prepare_unet() per Patrick's suggestions.

* more elaborate description for .

* formatting.

* add docstrings to the methods specific to pix2pix zero.

* suspecting a redundant noise prediction.

* needed for gradient computation chain.

* less hacks.

* fix: attention mask handling within the processor.

* remove attention reference map computation.

* fix: cross attn args.

* fix: prcoessor.

* store attention maps.

* fix: attention processor.

* update docs and better treatment to xa args.

* update the final noise computation call.

* change xa args call.

* remove xa args option from the pipeline.

* add: docs.

* first test.

* fix: url call.

* fix: argument call.

* remove image conditioning for now.

* 🚨 add: fast tests.

* explicit placement of the xa attn weights.

* add: slow tests 🐢

* fix: tests.

* edited direction embedding should be on the same device as prompt_embeds.

* debugging message.

* debugging.

* add pix2pix zero pipeline for a non-deterministic test.

* debugging/

* remove debugging message.

* make caption generation _

* address comments (part I).

* address PR comments (part II)

* fix: DDPM test assertion.

* refactor doc.

* address PR comments (part III).

* fix: type annotation for the scheduler.

* apply styling.

* skip_mps and add note on embeddings in the docs.

* before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes

* fix legacy inpaint noise and resize mask tensor

* updated legacy inpaint pipe test expected_slice

* [LoRA] All to use in inference with pipeline

* [LoRA] allow cross attention kwargs passed to pipeline

* finish

* make tests deterministic

* run slow tests

* prepare for testing

* finish

* refactor

* add print statements

* finish more

* correct some test failures

* more fixes

* set up to correct tests

* more corrections

* up

* fix more

* more prints

* add

* up

* up

* up

* uP

* uP

* more fixes

* uP

* up

* up

* up

* up

* fix more

* up

* up

* clean tests

* up

* up

* up

* more fixes

* Apply suggestions from code review
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* make

* correct

* finish

* finish
Co-authored-by: Suraj Patil <surajp815@gmail.com>