- 01 Sep, 2023 1 commit
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Dhruv Nair authored
* proposal for flaky tests * more precision fixes * move more tests to use cosine distance * more test fixes * clean up * use default attn * clean up * update expected value * make style * make style * Apply suggestions from code review * Update src/diffusers/pipelines/stable_diffusion/pipeline_onnx_stable_diffusion_img2img.py * make style * fix failing tests --------- Co-authored-by:Patrick von Platen <patrick.v.platen@gmail.com>
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- 24 Aug, 2023 1 commit
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Dhruv Nair authored
use max diff to compare model outputs
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- 17 Aug, 2023 1 commit
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Patrick von Platen authored
* make safetensors default * set default save method as safetensors * update tests * update to support saving safetensors * update test to account for safetensors default * update example tests to use safetensors * update example to support safetensors * update unet tests for safetensors * fix failing loader tests * fix qc issues * fix pipeline tests * fix example test --------- Co-authored-by:Dhruv Nair <dhruv.nair@gmail.com>
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- 04 Aug, 2023 1 commit
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Patrick von Platen authored
* correct * correct blocks * finish * finish * finish * Apply suggestions from code review * fix * up * up * up * Update examples/dreambooth/README_sdxl.md Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com> * Apply suggestions from code review --------- Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com>
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- 06 Jul, 2023 1 commit
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Prathik Rao authored
* add default to unet output to prevent it from being a required arg * add unit test * make style * adjust unit test * mark as fast test * adjust assert statement in test --------- Co-authored-by: Prathik Rao <prathikrao@microsoft.com@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net> Co-authored-by:root <root@orttrainingdev8.d32nl1ml4oruzj4qz3bqlggovf.px.internal.cloudapp.net>
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- 15 Jun, 2023 1 commit
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Patrick von Platen authored
* relax tolerance slightly * Add more tests * upload readme * upload readme * Apply suggestions from code review * Improve API Autoencoder KL * finalize * finalize tests * finalize tests * Apply suggestions from code review Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com> * up --------- Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com>
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- 22 May, 2023 2 commits
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Birch-san authored
* Cross-attention masks prefer qualified symbol, fix accidental Optional prefer qualified symbol in AttentionProcessor prefer qualified symbol in embeddings.py qualified symbol in transformed_2d qualify FloatTensor in unet_2d_blocks move new transformer_2d params attention_mask, encoder_attention_mask to the end of the section which is assumed (e.g. by functions such as checkpoint()) to have a stable positional param interface. regard return_dict as a special-case which is assumed to be injected separately from positional params (e.g. by create_custom_forward()). move new encoder_attention_mask param to end of CrossAttn block interfaces and Unet2DCondition interface, to maintain positional param interface. regenerate modeling_text_unet.py remove unused import unet_2d_condition encoder_attention_mask docs Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> versatile_diffusion/modeling_text_unet.py encoder_attention_mask docs Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> transformer_2d encoder_attention_mask docs Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> unet_2d_blocks.py: add parameter name comments Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> revert description. bool-to-bias treatment happens in unet_2d_condition only. comment parameter names fix copies, style * encoder_attention_mask for SimpleCrossAttnDownBlock2D, SimpleCrossAttnUpBlock2D * encoder_attention_mask for UNetMidBlock2DSimpleCrossAttn * support attention_mask, encoder_attention_mask in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D, KAttentionBlock. fix binding of attention_mask, cross_attention_kwargs params in KCrossAttnDownBlock2D, KCrossAttnUpBlock2D checkpoint invocations. * fix mistake made during merge conflict resolution * regenerate versatile_diffusion * pass time embedding into checkpointed attention invocation * always assume encoder_attention_mask is a mask (i.e. not a bias). * style, fix-copies * add tests for cross-attention masks * add test for padding of attention mask * explain mask's query_tokens dim. fix explanation about broadcasting over channels; we actually broadcast over query tokens * support both masks and biases in Transformer2DModel#forward. document behaviour * fix-copies * delete attention_mask docs on the basis I never tested self-attention masking myself. not comfortable explaining it, since I don't actually understand how a self-attn mask can work in its current form: the key length will be different in every ResBlock (we don't downsample the mask when we downsample the image). * review feedback: the standard Unet blocks shouldn't pass temb to attn (only to resnet). remove from KCrossAttnDownBlock2D,KCrossAttnUpBlock2D#forward. * remove encoder_attention_mask param from SimpleCrossAttn{Up,Down}Block2D,UNetMidBlock2DSimpleCrossAttn, and mask-choice in those blocks' #forward, on the basis that they only do one type of attention, so the consumer can pass whichever type of attention_mask is appropriate. * put attention mask padding back to how it was (since the SD use-case it enabled wasn't important, and it breaks the original unclip use-case). disable the test which was added. * fix-copies * style * fix-copies * put encoder_attention_mask param back into Simple block forward interfaces, to ensure consistency of forward interface. * restore passing of emb to KAttentionBlock#forward, on the basis that removal caused test failures. restore also the passing of emb to checkpointed calls to KAttentionBlock#forward. * make simple unet2d blocks use encoder_attention_mask, but only when attention_mask is None. this should fix UnCLIP compatibility. * fix copies
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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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- 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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- 20 Apr, 2023 1 commit
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nupurkmr9 authored
* diffusers==0.14.0 update * custom diffusion update * custom diffusion update * custom diffusion update * custom diffusion update * custom diffusion update * custom diffusion update * custom diffusion * custom diffusion * custom diffusion * custom diffusion * custom diffusion * apply formatting and get rid of bare except. * refactor readme and other minor changes. * misc refactor. * fix: repo_id issue and loaders logging bug. * fix: save_model_card. * fix: save_model_card. * fix: save_model_card. * add: doc entry. * refactor doc,. * custom diffusion * custom diffusion * custom diffusion * apply style. * remove tralining whitespace. * fix: toctree entry. * remove unnecessary print. * custom diffusion * custom diffusion * custom diffusion test * custom diffusion xformer update * custom diffusion xformer update * custom diffusion xformer update --------- Co-authored-by:
Nupur Kumari <nupurkumari@Nupurs-MacBook-Pro.local> Co-authored-by:
Sayak Paul <spsayakpaul@gmail.com> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Nupur Kumari <nupurkumari@nupurs-mbp.wifi.local.cmu.edu>
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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:
Pedro Cuenca <pedro@huggingface.co> --------- Co-authored-by:
Pedro Cuenca <pedro@huggingface.co>
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- 12 Apr, 2023 1 commit
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Andy authored
* inital commit for lora test cases * help a bit with lora for 3d * fixed lora tests * replaced redundant code --------- Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Sayak Paul <spsayakpaul@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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- 23 Mar, 2023 1 commit
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Sanchit Gandhi authored
* Add AudioLDM * up * add vocoder * start unet * unconditional unet * clap, vocoder and vae * clean-up: conversion scripts * fix: conversion script token_type_ids * clean-up: pipeline docstring * tests: from SD * clean-up: cpu offload vocoder instead of safety checker * feat: adapt tests to audioldm * feat: add docs * clean-up: amend pipeline docstrings * clean-up: make style * clean-up: make fix-copies * fix: add doc path to toctree * clean-up: args for conversion script * clean-up: paths to checkpoints * fix: use conditional unet * clean-up: make style * fix: type hints for UNet * clean-up: docstring for UNet * clean-up: make style * clean-up: remove duplicate in docstring * clean-up: make style * clean-up: make fix-copies * clean-up: move imports to start in code snippet * fix: pass cross_attention_dim as a list/tuple to unet * clean-up: make fix-copies * fix: update checkpoint path * fix: unet cross_attention_dim in tests * film embeddings -> class embeddings * Apply suggestions from code review Co-authored-by:
Will Berman <wlbberman@gmail.com> * fix: unet film embed to use existing args * fix: unet tests to use existing args * fix: make style * fix: transformers import and version in init * clean-up: make style * Revert "clean-up: make style" This reverts commit 5d6d1f8b324f5583e7805dc01e2c86e493660d66. * clean-up: make style * clean-up: use pipeline tester mixin tests where poss * clean-up: skip attn slicing test * fix: add torch dtype to docs * fix: remove conversion script out of src * fix: remove .detach from 1d waveform * fix: reduce default num inf steps * fix: swap height/width -> audio_length_in_s * clean-up: make style * fix: remove nightly tests * fix: imports in conversion script * clean-up: slim-down to two slow tests * clean-up: slim-down fast tests * fix: batch consistent tests * clean-up: make style * clean-up: remove vae slicing fast test * clean-up: propagate changes to doc * fix: increase test tol to 1e-2 * clean-up: finish docs * clean-up: make style * feat: vocoder / VAE compatibility check * feat: possibly expand / cut audio waveform * fix: pipeline call signature test * fix: slow tests output len * clean-up: make style * make style --------- Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
William Berman <WLBberman@gmail.com>
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- 21 Mar, 2023 1 commit
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Alexander Pivovarov authored
Co-authored-by:Patrick von Platen <patrick.v.platen@gmail.com>
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- 16 Mar, 2023 1 commit
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Nicolas Patry authored
* Adding `use_safetensors` argument to give more control to users about which weights they use. * Doc style. * Rebased (not functional). * Rebased and functional with tests. * Style. * Apply suggestions from code review * Style. * Addressing comments. * Update tests/test_pipelines.py Co-authored-by:
Will Berman <wlbberman@gmail.com> * Black ??? --------- Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Will Berman <wlbberman@gmail.com>
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- 15 Mar, 2023 2 commits
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Patrick von Platen authored
* rename file * rename attention * fix more * rename more * up * more deprecation imports * fixes
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Kashif Rasul authored
* fix AttnProcessor2_0 Fix use of AttnProcessor2_0 for cross attention with mask * added scale_qk and out_bias flags * fixed for xformers * check if it has scale argument * Update cross_attention.py * check torch version * fix sliced attn * style * set scale * fix test * fixed addedKV processor * revert back AttnProcessor2_0 * if missing if * fix inner_dim --------- Co-authored-by:Patrick von Platen <patrick.v.platen@gmail.com>
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- 04 Mar, 2023 1 commit
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Nicolas Patry authored
* Fix regression introduced in #2448 * Style.
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- 03 Mar, 2023 1 commit
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Nicolas Patry authored
* Adding support for `safetensors` and LoRa. * Adding metadata.
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- 01 Mar, 2023 1 commit
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Patrick von Platen authored
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- 13 Feb, 2023 1 commit
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bddppq authored
* Fix running LoRA with xformers * support disabling xformers * reformat * Add test
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- 07 Feb, 2023 2 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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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:
Patrick 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:
Patrick von Platen <patrick.v.platen@gmail.com> * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py Co-authored-by:
Patrick 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:
Patrick 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:
Pedro Cuenca <pedro@huggingface.co> * 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:
Pedro Cuenca <pedro@huggingface.co> * Update docs/source/en/api/pipelines/stable_diffusion/latent_upscale.mdx Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update src/diffusers/models/cross_attention.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * clean up conversion script * KDownsample2d,KUpsample2d -> KDownsample2D,KUpsample2D * more * Update src/diffusers/models/unet_2d_condition.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * remove prepare_extra_step_kwargs * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * Update src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_latent_upscale.py Co-authored-by:
Patrick 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:
yiyixuxu <yixu@yis-macbook-pro.lan> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Pedro Cuenca <pedro@huggingface.co>
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- 26 Jan, 2023 1 commit
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Patrick von Platen authored
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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:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Suraj Patil <surajp815@gmail.com> * upload * finish Co-authored-by:
Simo Ryu <cloneofsimo@gmail.com> Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Suraj Patil <surajp815@gmail.com>
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- 20 Dec, 2022 1 commit
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Patrick von Platen authored
* first proposal * rename * up * Apply suggestions from code review * better * up * finish * up * rename * correct versatile * up * up * up * up * fix * Apply suggestions from code review * make style * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> * add error message Co-authored-by:
Pedro Cuenca <pedro@huggingface.co>
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- 09 Dec, 2022 1 commit
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Patrick von Platen authored
* finish * fix * Update tests/models/test_models_unet_2d.py * style Co-authored-by:Anton Lozhkov <anton@huggingface.co>
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- 05 Dec, 2022 1 commit
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Suraj Patil authored
* make attn slice recursive * remove set_attention_slice from blocks * fix copies * make enable_attention_slicing base class method of DiffusionPipeline * fix set_attention_slice * fix set_attention_slice * fix copies * add tests * up * up * up * update * up * uP Co-authored-by:Patrick von Platen <patrick.v.platen@gmail.com>
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- 29 Nov, 2022 1 commit
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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:
Patrick von Platen <patrick.v.platen@gmail.com> * Typos and style * Tests: verify jax is available. * Style * Make flake happy * Remove typo. * Simple Flax SD 2 pipeline tests. * Import order * Remove unused import. Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by: @camenduru
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- 23 Nov, 2022 1 commit
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Suraj Patil authored
* boom boom * remove duplicate arg * add use_linear_proj arg * fix copies * style * add fast tests * use_linear_proj -> use_linear_projection
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- 08 Nov, 2022 1 commit
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Pedro Cuenca authored
* Schedulers: don't use float64 on mps * Test set_timesteps() on device (float schedulers). * SD pipeline: use device in set_timesteps. * SD in-painting pipeline: use device in set_timesteps. * Tests: fix mps crashes. * Skip test_load_pipeline_from_git on mps. Not compatible with float16. * Use device.type instead of str in Euler schedulers.
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- 03 Nov, 2022 2 commits
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Patrick von Platen authored
* correct naming * finish * Apply suggestions from code review * Apply suggestions from code review Co-authored-by:
Suraj Patil <surajp815@gmail.com> Co-authored-by:
Suraj Patil <surajp815@gmail.com>
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Suraj Patil authored
* make accelerate hard dep * default fast init * move params to cpu when device map is None * handle device_map=None * handle torch < 1.9 * remove device_map="auto" * style * add accelerate in torch extra * remove accelerate from extras["test"] * raise an error if torch is available but not accelerate * update installation docs * Apply suggestions from code review Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> * improve defautl loading speed even further, allow disabling fats loading * address review comments * adapt the tests * fix test_stable_diffusion_fast_load * fix test_read_init * temp fix for dummy checks * Trigger Build * Apply suggestions from code review Co-authored-by:
Anton Lozhkov <anton@huggingface.co> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Anton Lozhkov <anton@huggingface.co>
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- 02 Nov, 2022 1 commit
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Lewington-pitsos authored
* improve test precision get tests passing with greater precision using lewington images * make old numpy load function a wrapper around a more flexible numpy loading function * adhere to black formatting * add more black formatting * adhere to isort * loosen precision and replace path Co-authored-by:Patrick von Platen <patrick.v.platen@gmail.com>
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- 28 Oct, 2022 4 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
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Patrick von Platen authored
* improve tests * up * finish * upload * add init * up * finish vae * finish * reduce loading time with device_map * remove device_map from CPU * uP
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- 25 Oct, 2022 1 commit
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Patrick von Platen authored
* start * add more logic * Update src/diffusers/models/unet_2d_condition_flax.py * match weights * up * make model work * making class more general, fixing missed file rename * small fix * make new conversion work * up * finalize conversion * up * first batch of variable renamings * remove c and c_prev var names * add mid and out block structure * add pipeline * up * finish conversion * finish * upload * more fixes * Apply suggestions from code review * add attr * up * uP * up * finish tests * finish * uP * finish * fix test * up * naming consistency in tests * Apply suggestions from code review Co-authored-by:
Suraj Patil <surajp815@gmail.com> Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Nathan Lambert <nathan@huggingface.co> Co-authored-by:
Anton Lozhkov <anton@huggingface.co> * remove hardcoded 16 * Remove bogus * fix some stuff * finish * improve logging * docs * upload Co-authored-by:
Nathan Lambert <nol@berkeley.edu> Co-authored-by:
Suraj Patil <surajp815@gmail.com> Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Nathan Lambert <nathan@huggingface.co> Co-authored-by:
Anton Lozhkov <anton@huggingface.co>
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