- 07 Jun, 2023 1 commit
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Max-We authored
* Implement option for rescaling betas to zero terminal SNR * Implement rescale classifier free guidance in pipeline_stable_diffusion.py * focus on DDIM * make style * make style * make style * make style * Apply suggestions from Peter Lin * Apply suggestions from Peter Lin * make style * Apply suggestions from code review * Apply suggestions from code review * make style * make style --------- Co-authored-by:
MaxWe00 <gitlab.9v1lq@slmail.me> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com>
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- 05 Jun, 2023 1 commit
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YiYi Xu authored
VaeImageProcessor.preprocess refactor * refactored VaeImageProcessor - allow passing optional height and width argument to resize() - add convert_to_rgb * refactored prepare_latents method for img2img pipelines so that if we pass latents directly as image input, it will not encode it again * added a test in test_pipelines_common.py to test latents as image inputs * refactored img2img pipelines that accept latents as image: - controlnet img2img, stable diffusion img2img , instruct_pix2pix --------- Co-authored-by:
yiyixuxu <yixu310@gmail,com> Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com>
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- 22 May, 2023 1 commit
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Patrick von Platen authored
* up * fix more * Apply suggestions from code review * fix more * fix more * Check it * Remove 16:8 * fix more * fix more * fix more * up * up * Test only stable diffusion * Test only two files * up * Try out spinning up processes that can be killed * up * Apply suggestions from code review * up * up
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- 18 May, 2023 1 commit
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Will Berman authored
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- 16 May, 2023 1 commit
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clarencechen authored
* Add DPM-Solver Multistep Inverse Scheduler * Add draft tests for DiffEdit * Add inverse sde-dpmsolver steps to tune image diversity from inverted latents * Fix tests --------- Co-authored-by:
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- 11 May, 2023 1 commit
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Sayak Paul authored
* enable deterministic pytorch and cuda operations. * disable manual seeding. * make style && make quality for unet_2d tests. * enable determinism for the unet2dconditional model. * add CUBLAS_WORKSPACE_CONFIG for better reproducibility. * relax tolerance (very weird issue, though). * revert to torch manual_seed() where needed. * relax more tolerance. * better placement of the cuda variable and relax more tolerance. * enable determinism for 3d condition model. * relax tolerance. * add: determinism to alt_diffusion. * relax tolerance for alt diffusion. * dance diffusion. * dance diffusion is flaky. * test_dict_tuple_outputs_equivalent edit. * fix two more tests. * fix more ddim tests. * fix: argument. * change to diff in place of difference. * fix: test_save_load call. * test_save_load_float16 call. * fix: expected_max_diff * fix: paint by example. * relax tolerance. * add determinism to 1d unet model. * torch 2.0 regressions seem to be brutal * determinism to vae. * add reason to skipping. * up tolerance. * determinism to vq. * determinism to cuda. * determinism to the generic test pipeline file. * refactor general pipelines testing a bit. * determinism to alt diffusion i2i * up tolerance for alt diff i2i and audio diff * up tolerance. * determinism to audioldm * increase tolerance for audioldm lms. * increase tolerance for paint by paint. * increase tolerance for repaint. * determinism to cycle diffusion and sd 1. * relax tol for cycle diffusion
🚲 * relax tol for sd 1.0 * relax tol for controlnet. * determinism to img var. * relax tol for img variation. * tolerance to i2i sd * make style * determinism to inpaint. * relax tolerance for inpaiting. * determinism for inpainting legacy * relax tolerance. * determinism to instruct pix2pix * determinism to model editing. * model editing tolerance. * panorama determinism * determinism to pix2pix zero. * determinism to sag. * sd 2. determinism * sd. tolerance * disallow tf32 matmul. * relax tolerance is all you need. * make style and determinism to sd 2 depth * relax tolerance for depth. * tolerance to diffedit. * tolerance to sd 2 inpaint. * up tolerance. * determinism in upscaling. * tolerance in upscaler. * more tolerance relaxation. * determinism to v pred. * up tol for v_pred * unclip determinism * determinism to unclip img2img * determinism to text to video. * determinism to last set of tests * up tol. * vq cumsum doesn't have a deterministic kernel * relax tol * relax tol
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- 09 May, 2023 1 commit
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YiYi Xu authored
* add text2img * fix-copies * add * add all other pipelines * add * add * add * add * add * make style * style + fix copies --------- Co-authored-by:
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- 28 Apr, 2023 1 commit
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clarencechen authored
* Update Pix2PixZero Auto-correlation Loss * Add Stable Diffusion DiffEdit pipeline * Add draft documentation and import code * Bugfixes and refactoring * Add option to not decode latents in the inversion process * Harmonize preprocessing * Revert "Update Pix2PixZero Auto-correlation Loss" This reverts commit b218062fed08d6cc164206d6cb852b2b7b00847a. * Update annotations * rename `compute_mask` to `generate_mask` * Update documentation * Update docs * Update Docs * Fix copy * Change shape of output latents to batch first * Update docs * Add first draft for tests * Bugfix and update tests * Add `cross_attention_kwargs` support for all pipeline methods * Fix Copies * Add support for PIL image latents Add support for mask broadcasting Update docs and tests Align `mask` argument to `mask_image` Remove height and width arguments * Enable MPS Tests * Move example docstrings * Fix test * Fix test * fix pipeline inheritance * Harmonize `prepare_image_latents` with StableDiffusionPix2PixZeroPipeline * Register modules set to `None` in config for `test_save_load_optional_components` * Move fixed logic to specific test class * Clean changes to other pipelines * Update new tests to coordinate with #2953 * Update slow tests for better results * Safety to avoid potential problems with torch.inference_mode * Add reference in SD Pipeline Overview * Fix tests again * Enforce determinism in noise for generate_mask * Fix copies * Widen test tolerance for fp16 based on `test_stable_diffusion_upscale_pipeline_fp16` * Add LoraLoaderMixin and update `prepare_image_latents` * clean up repeat and reg * bugfix * Remove invalid args from docs Suppress spurious warning by repeating image before latent to mask gen
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- 18 Apr, 2023 1 commit
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YiYi Xu authored
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- 13 Apr, 2023 1 commit
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Patrick von Platen authored
* [Tests] parallelize * finish folder structuring * Parallelize tests more * Correct saving of pipelines * make sure logging level is correct * try again * Apply suggestions from code review Co-authored-by:
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- 11 Apr, 2023 1 commit
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Chanchana Sornsoontorn authored
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⚙ ️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:
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- 27 Mar, 2023 1 commit
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Pedro Cuenca authored
* Helper function to disable custom attention processors. * Restore code deleted by mistake. * Format * Fix modeling_text_unet copy.
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- 22 Mar, 2023 1 commit
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Pedro Cuenca authored
* Remove warmup passes in mps tests. * Update mps docs: no warmup pass in PyTorch 2 * Update imports.
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- 21 Mar, 2023 1 commit
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Will Berman authored
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- 18 Mar, 2023 2 commits
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Patrick von Platen authored
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Patrick von Platen authored
* [Tests] Correct PT2 * correct more * move versatile to nightly * up * up * again * Apply suggestions from code review
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- 03 Mar, 2023 1 commit
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Will Berman authored
* attend and excite batch test causing timeouts * move test num_images_per_prompt to pipeline mixin * style * prompt_key -> self.batch_params
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- 01 Mar, 2023 3 commits
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Will Berman authored
* attend and excite batch test causing timeouts * PipelineTesterMixin argument configuration refactor * error message text re: @yiyixuxu * remove eta re: @patrickvonplaten
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Patrick von Platen authored
* [Tests] Fix slow tests * [Tests] Fix slow tsets
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Patrick von Platen authored
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- 28 Feb, 2023 1 commit
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Pedro Cuenca authored
* Sequential cpu offload: require accelerate 0.14.0. * Import is_accelerate_version * Missing copy.
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- 27 Feb, 2023 2 commits
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Will Berman authored
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Will Berman authored
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- 16 Feb, 2023 3 commits
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YiYi Xu authored
* attend and excite pipeline * update update docstring example remove visualization remove the base class attention control remove dependency on stable diffusion pipeline always apply gaussian filter with default setting remove run_standard_sd argument hardcode attention_res and scale_range (related to step size) Update docs/source/en/api/pipelines/stable_diffusion/attend_and_excite.mdx Co-authored-by:
Will Berman <wlbberman@gmail.com> Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_attend_and_excite.py Co-authored-by:
Suraj Patil <surajp815@gmail.com> Co-authored-by:
evin <evinpinarornek@gmail.com> Co-authored-by:
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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
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Will Berman authored
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- 15 Feb, 2023 1 commit
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Patrick von Platen authored
* finish * Apply suggestions from code review * fix indent and import error in test_stable_diffusion_depth --------- Co-authored-by:
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- 14 Feb, 2023 1 commit
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Will Berman authored
* unet check length input * prep test file for changes * correct all tests * clean up --------- Co-authored-by:
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- 13 Feb, 2023 1 commit
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Patrick von Platen authored
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- 10 Feb, 2023 1 commit
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Patrick von Platen authored
* correct some * Apply suggestions from code review * correct * Update tests/pipelines/altdiffusion/test_alt_diffusion_img2img.py * Final
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- 08 Feb, 2023 1 commit
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Patrick von Platen authored
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- 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:
yiyixuxu <yixu@yis-macbook-pro.lan> Co-authored-by:
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- 25 Jan, 2023 1 commit
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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:
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- 17 Jan, 2023 1 commit
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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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- 29 Dec, 2022 1 commit
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Patrick von Platen authored
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- 25 Dec, 2022 1 commit
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Pedro Cuenca authored
* Make safety_checker optional in more pipelines. * Remove inappropriate comment in inpaint pipeline. * InPaint Test: set feature_extractor to None. * Remove import * img2img test: set feature_extractor to None. * inpaint sd2 test: set feature_extractor to None. Co-authored-by:
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- 19 Dec, 2022 1 commit
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Patrick von Platen authored
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- 16 Dec, 2022 1 commit
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Anton Lozhkov authored
* [WIP] Nightly integration tests * initial SD tests * update SD slow tests * style * repaint * ImageVariations * style * finish imgvar * img2img tests * debug * inpaint 1.5 * inpaint legacy * torch isn't happy about deterministic ops * allclose -> max diff for shorter logs * add SD2 * debug * Update tests/pipelines/stable_diffusion_2/test_stable_diffusion.py Co-authored-by:
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