- 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:
Pedro Cuenca <pedro@huggingface.co> --------- 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:Patrick von Platen <patrick.v.platen@gmail.com>
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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:
yiyixuxu <yixu310@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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- 13 Dec, 2022 1 commit
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Patrick von Platen authored
* [SD] Make sure batched input works correctly * uP * uP * up * up * uP * up * fix mask stuff * up * uP * more up * up * uP * up * finish * Apply suggestions from code review Co-authored-by:
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- 08 Dec, 2022 1 commit
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Suraj Patil authored
* begin depth pipeline * add depth estimation model * fix prepare_depth_mask * add a comment about autocast * copied from, quality, cleanup * begin tests * handle tensors * norm image tensor * fix batch size * fix tests * fix enable_sequential_cpu_offload * fix save load * fix test_save_load_float16 * fix test_save_load_optional_components * fix test_float16_inference * fix test_cpu_offload_forward_pass * fix test_dict_tuple_outputs_equivalent * up * fix fast tests * fix test_stable_diffusion_img2img_multiple_init_images * fix few more fast tests * don't use device map for DPT * fix test_stable_diffusion_pipeline_with_sequential_cpu_offloading * accept external depth maps * prepare_depth_mask -> prepare_depth_map * fix file name * fix file name * quality * check transformers version * fix test names * use skipif * fix import * add docs * skip tests on mps * correct version * uP * Update docs/source/api/pipelines/stable_diffusion_2.mdx * fix fix-copies * fix fix-copies Co-authored-by:
anton- <anton@huggingface.co>
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- 07 Dec, 2022 1 commit
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Suraj Patil authored
* fix upcast in slice attention * fix dtype * add test * fix test
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- 06 Dec, 2022 1 commit
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Anton Lozhkov authored
* [WIP] Standardize fast pipeline tests with PipelineTestMixin * refactor the sd tests a bit * add more common tests * add xformers * add progressbar test * cleanup * upd fp16 * CycleDiffusionPipelineFastTests * DanceDiffusionPipelineFastTests * AltDiffusionPipelineFastTests * StableDiffusion2PipelineFastTests * StableDiffusion2InpaintPipelineFastTests * StableDiffusionImageVariationPipelineFastTests * StableDiffusionImg2ImgPipelineFastTests * StableDiffusionInpaintPipelineFastTests * remove unused mixins * quality * add missing inits * try to fix mps tests * fix mps tests * add mps warmups * skip for some pipelines * style * Update tests/test_pipelines_common.py Co-authored-by:
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- 05 Dec, 2022 1 commit
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Patrick von Platen authored
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- 02 Dec, 2022 1 commit
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Patrick von Platen authored
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- 29 Nov, 2022 2 commits
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Pedro Cuenca authored
* Flax: start adapting to Stable Diffusion 2 * More changes. * attention_head_dim can be a tuple. * Fix typos * Add simple SD 2 integration test. Slice values taken from my Ampere GPU. * Add simple UNet integration tests for Flax. Note that the expected values are taken from the PyTorch results. This ensures the Flax and PyTorch versions are not too far off. * Apply suggestions from code review Co-authored-by:
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Patrick von Platen authored
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- 28 Nov, 2022 1 commit
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Patrick von Platen authored
* Add heun * Finish first version of heun * remove bogus * finish * finish * improve * up * up * fix more * change progress bar * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py * finish * up * up * up
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