Skip to content

GitLab

Switch branch/tag
  1. 11 Sep, 2023 1 commit
    • Dhruv Nair's avatar
      Lazy Import for Diffusers (#4829) · b6e0b016
      Dhruv Nair authored 
      

* initial commit

* move modules to import struct

* add dummy objects and _LazyModule

* add lazy import to schedulers

* clean up unused imports

* lazy import on models module

* lazy import for schedulers module

* add lazy import to pipelines module

* lazy import altdiffusion

* lazy import audio diffusion

* lazy import audioldm

* lazy import consistency model

* lazy import controlnet

* lazy import dance diffusion ddim ddpm

* lazy import deepfloyd

* lazy import kandinksy

* lazy imports

* lazy import semantic diffusion

* lazy imports

* lazy import stable diffusion

* move sd output to its own module

* clean up

* lazy import t2iadapter

* lazy import unclip

* lazy import versatile and vq diffsuion

* lazy import vq diffusion

* helper to fetch objects from modules

* lazy import sdxl

* lazy import txt2vid

* lazy import stochastic karras

* fix model imports

* fix bug

* lazy import

* clean up

* clean up

* fixes for tests

* fixes for tests

* clean up

* remove import of torch_utils from utils module

* clean up

* clean up

* fix mistake import statement

* dedicated modules for exporting and loading

* remove testing utils from utils module

* fixes from  merge conflicts

* Update src/diffusers/pipelines/kandinsky2_2/__init__.py

* fix docs

* fix alt diffusion copied from

* fix check dummies

* fix more docs

* remove accelerate import from utils module

* add type checking

* make style

* fix check dummies

* remove torch import from xformers check

* clean up error message

* fixes after upstream merges

* dummy objects fix

* fix tests

* remove unused module import

---------
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      b6e0b016
  3. 26 Jul, 2023 1 commit
  5. 23 May, 2023 1 commit
  7. 09 May, 2023 1 commit
  9. 06 May, 2023 1 commit
  11. 01 May, 2023 1 commit
    • Patrick von Platen's avatar
      Torch compile graph fix (#3286) · 0e82fb19
      Patrick von Platen authored 
      * fix more

* Fix more

* fix more

* Apply suggestions from code review

* fix

* make style

* make fix-copies

* fix

* make sure torch compile

* Clean

* fix test
      0e82fb19
  13. 19 Apr, 2023 1 commit
  15. 12 Apr, 2023 1 commit
    • Sayak Paul's avatar
      [LoRA] Enabling limited LoRA support for text encoder (#2918) · a89a14fa
      Sayak Paul authored 
      * add: first draft for a better LoRA enabler.

* make fix-copies.

* feat: backward compatibility.

* add: entry to the docs.

* add: tests.

* fix: docs.

* fix: norm group test for UNet3D.

* feat: add support for flat dicts.

* add depcrcation message instead of warning.
      a89a14fa
  17. 11 Apr, 2023 1 commit
    • Patrick von Platen's avatar
      Fix config prints and save, load of pipelines (#2849) · 8b451eb6
      Patrick von Platen authored 
      * [Config] Fix config prints and save, load

* Only use potential nn.Modules for dtype and device

* Correct vae image processor

* make sure in_channels is not accessed directly

* make sure in channels is only accessed via config

* Make sure schedulers only access config attributes

* Make sure to access config in SAG

* Fix vae processor and make style

* add tests

* uP

* make style

* Fix more naming issues

* Final fix with vae config

* change more
      8b451eb6
  19. 30 Mar, 2023 1 commit
  21. 28 Mar, 2023 1 commit
  23. 23 Mar, 2023 1 commit
  25. 22 Mar, 2023 1 commit
    • Patrick von Platen's avatar
      [MS Text To Video] Add first text to video (#2738) · ca1a2229
      Patrick von Platen authored 
      

* [MS Text To Video} Add first text to video

* upload

* make first model example

* match unet3d params

* make sure weights are correcctly converted

* improve

* forward pass works, but diff result

* make forward work

* fix more

* finish

* refactor video output class.

* feat: add support for a video export utility.

* fix: opencv availability check.

* run make fix-copies.

* add: docs for the model components.

* add: standalone pipeline doc.

* edit docstring of the pipeline.

* add: right path to TransformerTempModel

* add: first set of tests.

* complete fast tests for text to video.

* fix bug

* up

* three fast tests failing.

* add: note on slow tests

* make work with all schedulers

* apply styling.

* add slow tests

* change file name

* update

* more correction

* more fixes

* finish

* up

* Apply suggestions from code review

* up

* finish

* make copies

* fix pipeline tests

* fix more tests

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

* apply suggestions

* up

* revert

---------
Co-authored-by: default avatarSayak Paul <spsayakpaul@gmail.com>
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      ca1a2229
  27. 15 Mar, 2023 1 commit
  29. 03 Mar, 2023 1 commit
  31. 02 Mar, 2023 1 commit
  33. 01 Mar, 2023 1 commit
  35. 28 Feb, 2023 1 commit
  37. 16 Feb, 2023 1 commit
    • Pedro Cuenca's avatar
      `enable_model_cpu_offload` (#2285) · 2777264e
      Pedro Cuenca authored 
      * 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
      2777264e
  39. 14 Feb, 2023 1 commit
  41. 07 Feb, 2023 2 commits
    • Patrick von Platen's avatar
      Replace flake8 with ruff and update black (#2279) · a7ca03aa
      Patrick von Platen authored 
      * before running make style

* remove left overs from flake8

* finish

* make fix-copies

* final fix

* more fixes
      a7ca03aa
    • YiYi Xu's avatar
      Stable Diffusion Latent Upscaler (#2059) · 1051ca81
      YiYi Xu authored 
      

* Modify UNet2DConditionModel

- allow skipping mid_block

- adding a norm_group_size argument so that we can set the `num_groups` for group norm using `num_channels//norm_group_size`

- allow user to set dimension for the timestep embedding (`time_embed_dim`)

- the kernel_size for `conv_in` and `conv_out` is now configurable

- add random fourier feature layer (`GaussianFourierProjection`) for `time_proj`

- allow user to add the time and class embeddings before passing through the projection layer together - `time_embedding(t_emb + class_label))`

- added 2 arguments `attn1_types` and `attn2_types`

  * currently we have argument `only_cross_attention`: when it's set to `True`, we will have a to the
`BasicTransformerBlock` block with 2 cross-attention , otherwise we
get a self-attention followed by a cross-attention; in k-upscaler, we need to have blocks that include just one cross-attention, or self-attention -> cross-attention;
so I added `attn1_types` and `attn2_types` to the unet's argument list to allow user specify the attention types for the 2 positions in each block;  note that I stil kept
the `only_cross_attention` argument for unet for easy configuration, but it will be converted to `attn1_type` and `attn2_type` when passing down to the down blocks

- the position of downsample layer and upsample layer is now configurable

- in k-upscaler unet, there is only one skip connection per each up/down block (instead of each layer in stable diffusion unet), added `skip_freq = "block"` to support
this use case

- if user passes attention_mask to unet, it will prepare the mask and pass a flag to cross attention processer to skip the `prepare_attention_mask` step
inside cross attention block

add up/down blocks for k-upscaler

modify CrossAttention class

- make the `dropout` layer in `to_out` optional

- `use_conv_proj` - use conv instead of linear for all projection layers (i.e. `to_q`, `to_k`, `to_v`, `to_out`) whenever possible. note that when it's used to do cross
attention, to_k, to_v has to be linear because the `encoder_hidden_states` is not 2d

- `cross_attention_norm` - add an optional layernorm on encoder_hidden_states

- `attention_dropout`: add an optional dropout on attention score

adapt BasicTransformerBlock

- add an ada groupnorm layer  to conditioning attention input with timestep embedding

- allow skipping the FeedForward layer in between the attentions

- replaced the only_cross_attention argument with attn1_type and attn2_type for more flexible configuration

update timestep embedding: add new act_fn  gelu and an optional act_2

modified ResnetBlock2D

- refactored with AdaGroupNorm class (the timestep scale shift normalization)

- add `mid_channel` argument - allow the first conv to have a different output dimension from the second conv

- add option to use input AdaGroupNorm on the input instead of groupnorm

- add options to add a dropout layer after each conv

- allow user to set the bias in conv_shortcut (needed for k-upscaler)

- add gelu

adding conversion script for k-upscaler unet

add pipeline

* fix attention mask

* fix a typo

* fix a bug

* make sure model can be used with GPU

* make pipeline work with fp16

* fix an error in BasicTransfomerBlock

* make style

* fix typo

* some more fixes

* uP

* up

* correct more

* some clean-up

* clean time proj

* up

* uP

* more changes

* remove the upcast_attention=True from unet config

* remove attn1_types, attn2_types etc

* fix

* revert incorrect changes up/down samplers

* make style

* remove outdated files

* Apply suggestions from code review

* attention refactor

* refactor cross attention

* Apply suggestions from code review

* update

* up

* update

* Apply suggestions from code review

* finish

* Update src/diffusers/models/cross_attention.py

* more fixes

* up

* up

* up

* finish

* more corrections of conversion state

* act_2 -> act_2_fn

* remove dropout_after_conv from ResnetBlock2D

* make style

* simplify KAttentionBlock

* add fast test for latent upscaler pipeline

* add slow test

* slow test fp16

* make style

* add doc string for pipeline_stable_diffusion_latent_upscale

* add api doc page for latent upscaler pipeline

* deprecate attention mask

* clean up embeddings

* simplify resnet

* up

* clean up resnet

* up

* correct more

* up

* up

* improve a bit more

* correct more

* more clean-ups

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>

* Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>

* add docstrings for new unet config

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

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

* # Copied from

* encode the image if not latent

* remove force casting vae to fp32

* fix

* add comments about preconditioning parameters from k-diffusion paper

* attn1_type, attn2_type -> add_self_attention

* clean up get_down_block and get_up_block

* fix

* fixed a typo(?) in ada group norm

* update slice attention processer for cross attention

* update slice

* fix fast test

* update the checkpoint

* finish tests

* fix-copies

* fix-copy for modeling_text_unet.py

* make style

* make style

* fix f-string

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

* fix import

* correct changes

* fix resnet

* make fix-copies

* correct euler scheduler

* add missing #copied from for preprocess

* revert

* fix

* fix copies

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

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

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

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

* Update src/diffusers/models/cross_attention.py
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

* clean up conversion script

* KDownsample2d,KUpsample2d -> KDownsample2D,KUpsample2D

* more

* Update src/diffusers/models/unet_2d_condition.py
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

* remove prepare_extra_step_kwargs

* Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>

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

* fix a typo in timestep embedding

* remove num_image_per_prompt

* fix fasttest

* make style + fix-copies

* fix

* fix xformer test

* fix style

* doc string

* make style

* fix-copies

* docstring for time_embedding_norm

* make style

* final finishes

* make fix-copies

* fix tests

---------
Co-authored-by: default avataryiyixuxu <yixu@yis-macbook-pro.lan>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
Co-authored-by: default avatarPedro Cuenca <pedro@huggingface.co>
      1051ca81
  43. 06 Feb, 2023 1 commit
  45. 03 Feb, 2023 1 commit
  47. 27 Jan, 2023 1 commit
  49. 26 Jan, 2023 1 commit
  51. 25 Jan, 2023 1 commit
  53. 17 Jan, 2023 1 commit
    • Kashif Rasul's avatar
      DiT Pipeline (#1806) · 37d113cc
      Kashif Rasul authored 
      

* added dit model

* import

* initial pipeline

* initial convert script

* initial pipeline

* make style

* raise valueerror

* single function

* rename classes

* use DDIMScheduler

* timesteps embedder

* samples to cpu

* fix var names

* fix numpy type

* use timesteps class for proj

* fix typo

* fix arg name

* flip_sin_to_cos and better var names

* fix C shape cal

* make style

* remove unused imports

* cleanup

* add back patch_size

* initial dit doc

* typo

* Update docs/source/api/pipelines/dit.mdx
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>

* added copyright license headers

* added example usage and toc

* fix variable names asserts

* remove comment

* added docs

* fix typo

* upstream changes

* set proper device for drop_ids

* added initial dit pipeline test

* update docs

* fix imports

* make fix-copies

* isort

* fix imports

* get rid of more magic numbers

* fix code when guidance is off

* remove block_kwargs

* cleanup script

* removed to_2tuple

* use FeedForward class instead of another MLP

* style

* work on mergint DiTBlock with BasicTransformerBlock

* added missing final_dropout and args to BasicTransformerBlock

* use norm from block

* fix arg

* remove unused arg

* fix call to class_embedder

* use timesteps

* make style

* attn_output gets multiplied

* removed commented code

* use Transformer2D

* use self.is_input_patches

* fix flags

* fixed conversion to use Transformer2DModel

* fixes for pipeline

* remove dit.py

* fix timesteps device

* use randn_tensor and fix fp16 inf.

* timesteps_emb already the right dtype

* fix dit test class

* fix test and style

* fix norm2 usage in vq-diffusion

* added author names to pipeline and lmagenet labels link

* fix tests

* use norm_type as string

* rename dit to transformer

* fix name

* fix test

* set  norm_type = "layer" by default

* fix tests

* do not skip common tests

* Update src/diffusers/models/attention.py
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>

* revert AdaLayerNorm API

* fix norm_type name

* make sure all components are in eval mode

* revert norm2 API

* compact

* finish deprecation

* add slow tests

* remove @

* refactor some stuff

* upload

* Update src/diffusers/pipelines/dit/pipeline_dit.py

* finish more

* finish docs

* improve docs

* finish docs
Co-authored-by: default avatarSuraj Patil <surajp815@gmail.com>
Co-authored-by: default avatarWilliam Berman <WLBberman@gmail.com>
Co-authored-by: default avatarPatrick von Platen <patrick.v.platen@gmail.com>
      37d113cc
  55. 16 Jan, 2023 1 commit
  57. 12 Jan, 2023 1 commit
  59. 04 Jan, 2023 1 commit
    • Patrick von Platen's avatar
      Improve reproduceability 2/3 (#1906) · 9b638548
      Patrick von Platen authored 
      * [Repro] Correct reproducability

* up

* up

* uP

* up

* need better image

* allow conversion from no state dict checkpoints

* up

* up

* up

* up

* check tensors

* check tensors

* check tensors

* check tensors

* next try

* up

* up

* better name

* up

* up

* Apply suggestions from code review

* correct more

* up

* replace all torch randn

* fix

* correct

* correct

* finish

* fix more

* up
      9b638548
  61. 02 Jan, 2023 1 commit
  63. 30 Dec, 2022 1 commit
  65. 17 Dec, 2022 1 commit
  67. 13 Dec, 2022 1 commit
  69. 12 Dec, 2022 1 commit
  71. 05 Dec, 2022 2 commits
  73. 02 Dec, 2022 2 commits