- 04 Oct, 2022 3 commits
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NIKHIL A V authored
* renamed single letter variables * renamed x to meaningful variable in resnet.py Hello @patil-suraj can you verify it Thanks * Reformatted using black * renamed x to meaningful variable in resnet.py Hello @patil-suraj can you verify it Thanks * reformatted the files * modified unboundlocalerror in line 374 * removed referenced before error * renamed single variable x -> hidden_state, p-> pad_value Co-authored-by:
Nikhil A V <nikhilav@Nikhils-MacBook-Pro.local> Co-authored-by:
Patrick von Platen <patrick.v.platen@gmail.com> Co-authored-by:
Suraj Patil <surajp815@gmail.com>
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Pedro Cuenca authored
Remove comments no longer appropriate. There were casting operations before, they are now gone.
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Kashif Rasul authored
fix docstring fixes #709
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- 30 Sep, 2022 3 commits
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Nouamane Tazi authored
* revert using baddbmm in attention - to fix `test_stable_diffusion_memory_chunking` test * styling
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Josh Achiam authored
* Allow resolutions that are not multiples of 64 * ran black * fix bug * add test * more explanation * more comments Co-authored-by: -
Nouamane Tazi authored
* initial commit * make UNet stream capturable * try to fix noise_pred value * remove cuda graph and keep NB * non blocking unet with PNDMScheduler * make timesteps np arrays for pndm scheduler because lists don't get formatted to tensors in `self.set_format` * make max async in pndm * use channel last format in unet * avoid moving timesteps device in each unet call * avoid memcpy op in `get_timestep_embedding` * add `channels_last` kwarg to `DiffusionPipeline.from_pretrained` * update TODO * replace `channels_last` kwarg with `memory_format` for more generality * revert the channels_last changes to leave it for another PR * remove non_blocking when moving input ids to device * remove blocking from all .to() operations at beginning of pipeline * fix merging * fix merging * model can run in other precisions without autocast * attn refactoring * Revert "attn refactoring" This reverts commit 0c70c0e189cd2c4d8768274c9fcf5b940ee310fb. * remove restriction to run conv_norm in fp32 * use `baddbmm` instead of `matmul`for better in attention for better perf * removing all reshapes to test perf * Revert "removing all reshapes to test perf" This reverts commit 006ccb8a8c6bc7eb7e512392e692a29d9b1553cd. * add shapes comments * hardcore whats needed for jitting * Revert "hardcore whats needed for jitting" This reverts commit 2fa9c698eae2890ac5f8e367ca80532ecf94df9a. * Revert "remove restriction to run conv_norm in fp32" This reverts commit cec592890c32da3d1b78d38b49e4307aedf459b9. * revert using baddmm in attention's forward * cleanup comment * remove restriction to run conv_norm in fp32. no quality loss was noticed This reverts commit cc9bc1339c998ebe9e7d733f910c6d72d9792213. * add more optimizations techniques to docs * Revert "add shapes comments" This reverts commit 31c58eadb8892f95478cdf05229adf678678c5f4. * apply suggestions * make quality * apply suggestions * styling * `scheduler.timesteps` are now arrays so we dont need .to() * remove useless .type() * use mean instead of max in `test_stable_diffusion_inpaint_pipeline_k_lms` * move scheduler timestamps to correct device if tensors * add device to `set_timesteps` in LMSD scheduler * `self.scheduler.set_timesteps` now uses device arg for schedulers that accept it * quick fix * styling * remove kwargs from schedulers `set_timesteps` * revert to using max in K-LMS inpaint pipeline test * Revert "`self.scheduler.set_timesteps` now uses device arg for schedulers that accept it" This reverts commit 00d5a51e5c20d8d445c8664407ef29608106d899. * move timesteps to correct device before loop in SD pipeline * apply previous fix to other SD pipelines * UNet now accepts tensor timesteps even on wrong device, to avoid errors - it shouldnt affect performance if timesteps are alrdy on correct device - it does slow down performance if they're on the wrong device * fix pipeline when timesteps are arrays with strides
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- 29 Sep, 2022 1 commit
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Partho authored
renamed x to hidden_states
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- 27 Sep, 2022 1 commit
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Yih-Dar authored
* Fix SpatialTransformer * Fix SpatialTransformer Co-authored-by:ydshieh <ydshieh@users.noreply.github.com>
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- 23 Sep, 2022 1 commit
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Younes Belkada authored
* documenting `attention_flax.py` file * documenting `embeddings_flax.py` * documenting `unet_blocks_flax.py` * Add new objs to doc page * document `vae_flax.py` * Apply suggestions from code review * modify `unet_2d_condition_flax.py` * make style * Apply suggestions from code review * make style * Apply suggestions from code review * fix indent * fix typo * fix indent unet * Update src/diffusers/models/vae_flax.py * Apply suggestions from code review Co-authored-by:
Pedro Cuenca <pedro@huggingface.co> Co-authored-by:
Mishig Davaadorj <dmishig@gmail.com> Co-authored-by:
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- 22 Sep, 2022 1 commit
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Suraj Patil authored
* add grad ckpt to downsample blocks * make it work * don't pass gradient_checkpointing to upsample block * add tests for UNet2DConditionModel * add test_gradient_checkpointing * add gradient_checkpointing for up and down blocks * add functions to enable and disable grad ckpt * remove the forward argument * better naming * make supports_gradient_checkpointing private
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- 21 Sep, 2022 1 commit
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Younes Belkada authored
replace `dropout_prob` by `dropout` in `vae`
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- 20 Sep, 2022 4 commits
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Patrick von Platen authored
* [Flax] Fix unet and ddim scheduler * correct * finish
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Mishig Davaadorj authored
* WIP: flax FlaxDiffusionPipeline & FlaxStableDiffusionPipeline * todo comment * Fix imports * Fix imports * add dummies * Fix empty init * make pipeline work * up * Use Flax schedulers (typing, docstring) * Wrap model imports inside availability checks. * more updates * make sure flax is not broken * make style * more fixes * up Co-authored-by:
Pedro Cuenca <pedro@latenitesoft.com>
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Suraj Patil authored
* rename weights to align with PT * DiagonalGaussianDistribution => FlaxDiagonalGaussianDistribution * fix name
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Younes Belkada authored
* first commit: - add `from_pt` argument in `from_pretrained` function - add `modeling_flax_pytorch_utils.py` file * small nit - fix a small nit - to not enter in the second if condition * major changes - modify FlaxUnet modules - first conversion script - more keys to be matched * keys match - now all keys match - change module names for correct matching - upsample module name changed * working v1 - test pass with atol and rtol= `4e-02` * replace unsued arg * make quality * add small docstring * add more comments - add TODO for embedding layers * small change - use `jnp.expand_dims` for converting `timesteps` in case it is a 0-dimensional array * add more conditions on conversion - add better test to check for keys conversion * make shapes consistent - output `img_w x img_h x n_channels` from the VAE * Revert "make shapes consistent" This reverts commit 4cad1aeb4aeb224402dad13c018a5d42e96267f6. * fix unet shape - channels first!
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- 19 Sep, 2022 6 commits
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Yih-Dar authored
* Fix CrossAttention._sliced_attention Co-authored-by: -
Patrick von Platen authored
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Patrick von Platen authored
* [Flax] Add Vae * correct * Apply suggestions from code review Co-authored-by:
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Yih-Dar authored
* Fix _upsample_2d Co-authored-by: -
ydshieh authored
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ydshieh authored
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- 18 Sep, 2022 1 commit
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Mishig Davaadorj authored
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- 16 Sep, 2022 2 commits
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Yuta Hayashibe authored
* Fix typos * Add a typo check action * Fix a bug * Changed to manual typo check currently Ref: https://github.com/huggingface/diffusers/pull/483#pullrequestreview-1104468010 Co-authored-by:
Anton Lozhkov <aglozhkov@gmail.com> * Removed a confusing message * Renamed "nin_shortcut" to "in_shortcut" * Add memo about NIN Co-authored-by:
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Yih-Dar authored
* Fix PT up/down sample_2d * empty commit * style * style Co-authored-by:
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- 15 Sep, 2022 2 commits
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Pedro Cuenca authored
* First UNet Flax modeling blocks. Mimic the structure of the PyTorch files. The model classes themselves need work, depending on what we do about configuration and initialization. * Remove FlaxUNet2DConfig class. * ignore_for_config non-config args. * Implement `FlaxModelMixin` * Use new mixins for Flax UNet. For some reason the configuration is not correctly applied; the signature of the `__init__` method does not contain all the parameters by the time it's inspected in `extract_init_dict`. * Import `FlaxUNet2DConditionModel` if flax is available. * Rm unused method `framework` * Update src/diffusers/modeling_flax_utils.py Co-authored-by:
Mishig Davaadorj <mishig.davaadorj@coloradocollege.edu> * Fix typo in transformer block. * make style * some more changes * make style * Add comment * Update src/diffusers/modeling_flax_utils.py Co-authored-by:
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Suraj Patil authored
* pass norm_num_groups to unet blocs and attention * fix UNet2DConditionModel * add norm_num_groups arg in vae * add tests * remove comment * Apply suggestions from code review
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- 14 Sep, 2022 2 commits
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Suraj Patil authored
* add different method for sliced attention * Update src/diffusers/models/attention.py * Apply suggestions from code review * Update src/diffusers/models/attention.py Co-authored-by: -
Nicolas Patry authored
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- 12 Sep, 2022 1 commit
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Kashif Rasul authored
* update expected results of slow tests * relax sum and mean tests * Print shapes when reporting exception * formatting * fix sentence * relax test_stable_diffusion_fast_ddim for gpu fp16 * relax flakey tests on GPU * added comment on large tolerences * black * format * set scheduler seed * added generator * use np.isclose * set num_inference_steps to 50 * fix dep. warning * update expected_slice * preprocess if image * updated expected results * updated expected from CI * pass generator to VAE * undo change back to orig * use orignal * revert back the expected on cpu * revert back values for CPU * more undo * update result after using gen * update mean * set generator for mps * update expected on CI server * undo * use new seed every time * cpu manual seed * reduce num_inference_steps * style * use generator for randn Co-authored-by:
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- 09 Sep, 2022 2 commits
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Partho authored
* renamed variable names q -> query k -> key v -> value b -> batch c -> channel h -> height w -> weight * rename variable names missed some in the initial commit * renamed more variable names As per code review suggestions, renamed x -> hidden_states and x_in -> residual * fixed minor typo
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Suraj Patil authored
* use torch.matmul instead of einsum * fix softmax
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- 08 Sep, 2022 3 commits
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Patrick von Platen authored
* Update black * update table
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Kashif Rasul authored
* docs for attention * types for embeddings * unet2d docstrings * UNet2DConditionModel docstrings * fix typos * style and vq-vae docstrings * docstrings for VAE * Update src/diffusers/models/unet_2d.py Co-authored-by:
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Pedro Cuenca authored
* Initial support for mps in Stable Diffusion pipeline. * Initial "warmup" implementation when using mps. * Make some deterministic tests pass with mps. * Disable training tests when using mps. * SD: generate latents in CPU then move to device. This is especially important when using the mps device, because generators are not supported there. See for example https://github.com/pytorch/pytorch/issues/84288. In addition, the other pipelines seem to use the same approach: generate the random samples then move to the appropriate device. After this change, generating an image in MPS produces the same result as when using the CPU, if the same seed is used. * Remove prints. * Pass AutoencoderKL test_output_pretrained with mps. Sampling from `posterior` must be done in CPU. * Style * Do not use torch.long for log op in mps device. * Perform incompatible padding ops in CPU. UNet tests now pass. See https://github.com/pytorch/pytorch/issues/84535 * Style: fix import order. * Remove unused symbols. * Remove MPSWarmupMixin, do not apply automatically. We do apply warmup in the tests, but not during normal use. This adopts some PR suggestions by @patrickvonplaten. * Add comment for mps fallback to CPU step. * Add README_mps.md for mps installation and use. * Apply `black` to modified files. * Restrict README_mps to SD, show measures in table. * Make PNDM indexing compatible with mps. Addresses #239. * Do not use float64 when using LDMScheduler. Fixes #358. * Fix typo identified by @patil-suraj Co-authored-by:
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- 07 Sep, 2022 1 commit
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Rashmi Margani authored
Co-authored-by:Rashmi S <rashmis@Rashmis-MacBook-Pro.local>
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- 06 Sep, 2022 2 commits
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Patrick von Platen authored
* up * add tests * correct * up * finish * better naming * Update README.md Co-authored-by:
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Pedro Cuenca authored
Use `expand` instead of ones to broadcast tensor. As suggested by @bes-dev. According the documentation this shouldn't take any memory - it just plays with the strides.
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- 05 Sep, 2022 3 commits
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Partho authored
* [Type Hint] VAE models * Update src/diffusers/models/vae.py * apply suggestions from code review Co-authored-by: -
Samuel Ajisegiri authored
* type hints: models/vae.py * modify typings in vae.py Co-authored-by:
Anton Lozhkov <anton@huggingface.co>
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Patrick von Platen authored
* add outputs for models * add for pipelines * finish schedulers * better naming * adapt tests as well * replace dict access with . access * make schedulers works * finish * correct readme * make bcp compatible * up * small fix * finish * more fixes * more fixes * Apply suggestions from code review Co-authored-by:
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