"gallery/v2_transforms/plot_transforms_v2.py" did not exist on "312c3d3287aa9936e79a374819ff466e0517c5d1"
- 07 Feb, 2023 3 commits
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Patrick von Platen authored
* before running make style * remove left overs from flake8 * finish * make fix-copies * final fix * more fixes
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Patrick von Platen authored
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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:
Patrick von Platen <patrick.v.platen@gmail.com> * Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx Co-authored-by:
yiyixuxu <yixu@yis-macbook-pro.lan> Co-authored-by:
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- 01 Feb, 2023 1 commit
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Patrick von Platen authored
* up * finish
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- 31 Jan, 2023 4 commits
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Patrick von Platen authored
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1lint authored
* fix legacy inpaint noise and resize mask tensor * updated legacy inpaint pipe test expected_slice
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Dudu Moshe authored
scheduling_ddpm: fix evaluate with lower timesteps count than train. Co-authored-by: -
Patrick von Platen authored
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- 27 Jan, 2023 3 commits
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Patrick von Platen authored
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Patrick von Platen authored
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Patrick von Platen authored
* [LoRA] All to use in inference with pipeline * [LoRA] allow cross attention kwargs passed to pipeline * finish
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- 26 Jan, 2023 1 commit
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Patrick von Platen authored
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- 25 Jan, 2023 3 commits
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Patrick von Platen authored
* [Bump version] 0.13 * Bump model up * up
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Patrick von Platen authored
* 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:
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Patrick von Platen authored
* add text embeds to sd * add text embeds to sd * finish tests * finish * finish * make style * fix tests * make style * make style * up * better docs * fix * fix * new try * up * up * finish
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- 22 Jan, 2023 2 commits
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Patrick von Platen authored
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Patrick von Platen authored
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- 21 Jan, 2023 1 commit
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Patrick von Platen authored
* [From pretrained] Don't download .safetensors files if safetensors is not available * tests * tests * up
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- 20 Jan, 2023 3 commits
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Suraj Patil authored
* use cpu generator in slow tests * ifx get_inputs
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Lucain authored
* Switch to huggingface_hub.ModelCard * Remove modelcards dependency in favor of Jinja2
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Suraj Patil authored
* being pix2pix * ifx * cfg image_latents * fix some docstr * fix * fix * hack * fix * Apply suggestions from code review Co-authored-by:
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- 19 Jan, 2023 2 commits
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Anton Lozhkov authored
* improve EMA * style * one EMA model * quality * fix tests * fix test * Apply suggestions from code review Co-authored-by:
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Patrick von Platen authored
* [Dit] Fix dit tests * up
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- 18 Jan, 2023 1 commit
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Patrick von Platen authored
* [Lora] first upload * add first lora version * upload * more * first training * up * correct * improve * finish loaders and inference * up * up * fix more * up * finish more * finish more * up * up * change year * revert year change * Change lines * Add cloneofsimo as co-author. Co-authored-by:
Simo Ryu <cloneofsimo@gmail.com> * finish * fix docs * Apply suggestions from code review Co-authored-by:
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- 17 Jan, 2023 2 commits
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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:
William Berman <WLBberman@gmail.com> Co-authored-by:
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Jerry Jiarui XU authored
* [Flax] Add Flax inpainting impl * fixed copies, add README.md * fixed README.md * add test * format * update README.md
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- 16 Jan, 2023 3 commits
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Will Berman authored
re: https://github.com/huggingface/diffusers/issues/1857 We relax some of the checks to deal with unclip reproducibility issues. Mainly by checking the average pixel difference (measured w/in 0-255) instead of the max pixel difference (measured w/in 0-1). - [x] add mixin to UnCLIPPipelineFastTests - [x] add mixin to UnCLIPImageVariationPipelineFastTests - [x] Move UnCLIPPipeline flags in mixin to base class - [x] Small MPS fixes for F.pad and F.interpolate - [x] Made test unCLIP model's dimensions smaller to run tests faster
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Patrick von Platen authored
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Erin authored
* test unet blocks 2d * change to randn_tensor * mps flaky
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- 13 Jan, 2023 1 commit
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Vladimir Sotnikov authored
* [Stable Diffusion Img2Img] resize source images to integer multiple of 8 instead of 32 * [Alt Diffusion Img2Img] resize source images to multiple of 8 instead of 32 * [Img2Img] fix AltDiffusion Img2Img resolution test * [Img2Img] add Stable Diffusion Img2Img resolution test * [Cycle Diffusion] round resolution to multiplies of 8 instead of 32 * [ONNX SD Img2Img] round resolution to multiplies of 64 instead of 32 * [SD Depth2Img] round resolution to multiplies of 8 instead of 32 * [Repaint] round resolution to multiplies of 8 instead of 32 * fix make style Co-authored-by:
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- 12 Jan, 2023 2 commits
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camenduru authored
* from_flax * oops * oops * make style with pip install -e ".[dev]" * oops * now code quality happy
😋 * allow_patterns += FLAX_WEIGHTS_NAME * Update src/diffusers/pipelines/pipeline_utils.py Co-authored-by: -
Patrick von Platen authored
* [Slow tests] Fix tests * Update tests/pipelines/karras_ve/test_karras_ve.py
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- 04 Jan, 2023 3 commits
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qsh-zh authored
* feat : add log-rho deis multistep deis * docs :fix typo * docs : add docs for impl algo * docs : remove duplicate ref * finish deis * add docs * fix Co-authored-by: -
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
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Erin authored
* test resnet block * fix code format required by isort * add torch device * nit
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- 03 Jan, 2023 2 commits
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Patrick von Platen authored
* [Deterministic torch randn] Allow tensors to be generated on CPU * fix more * up * fix more * up * Update src/diffusers/utils/torch_utils.py Co-authored-by:
Anton Lozhkov <anton@huggingface.co> * Apply suggestions from code review * up * up * Apply suggestions from code review Co-authored-by:
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Robert Dargavel Smith authored
* Add condtional generation * add fast test for conditional audio generation
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- 01 Jan, 2023 1 commit
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Patrick von Platen authored
* [Attention] Finish refactor attention file * correct more * fix * more fixes * correct * up
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- 30 Dec, 2022 2 commits
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Patrick von Platen authored
[Unclip] Make sure text_embeddings & image_embeddings can directly be passed to enable interpolation tasks. (#1858) * [Unclip] Make sure latents can be reused * allow one to directly pass embeddings * up * make unclip for text work * finish allowing to pass embeddings * correct more * make style
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Patrick von Platen authored
* move files a bit * more refactors * fix more * more fixes * fix more onnx * make style * upload * fix * up * fix more * up again * up * small fix * Update src/diffusers/__init__.py Co-authored-by:
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