map BACKEND_RESET_MAX_MEMORY_ALLOCATED to reset_peak_memory_stats on XPU #11191
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Signed-off-by: YAO Matrix <matrix.yao@intel.com>
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@sayakpaul , pls help review, thx very much. |
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The docs for this PR live here. All of your documentation changes will be reflected on that endpoint. The docs are available until 30 days after the last update. |
hlky
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Apr 2, 2025
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Hi @yao-matrix. Thanks for the PR. Feel free to ping me for any XPU related changes as I have been reviewing the others from your colleague. We appreciate the efforts in improving XPU support.
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Failing tests are unrelated. |
jonluca
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Apr 3, 2025
* Raise warning and round down if Wan num_frames is not 4k + 1 (huggingface#11167) * update * raise warning and round to nearest multiple of scale factor * [Docs] Fix environment variables in `installation.md` (huggingface#11179) * Add `latents_mean` and `latents_std` to `SDXLLongPromptWeightingPipeline` (huggingface#11034) * Bug fix in LTXImageToVideoPipeline.prepare_latents() when latents is already set (huggingface#10918) * Bug fix in ltx * Assume packed latents. --------- Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> Co-authored-by: YiYi Xu <yixu310@gmail.com> * [tests] no hard-coded cuda (huggingface#11186) no cuda only * [WIP] Add Wan Video2Video (huggingface#11053) * update * update * update * update * update * update * update * update * update * update * update * update * update * update * update * update * map BACKEND_RESET_MAX_MEMORY_ALLOCATED to reset_peak_memory_stats on XPU (huggingface#11191) Signed-off-by: YAO Matrix <matrix.yao@intel.com> * fix autocast (huggingface#11190) Signed-off-by: jiqing-feng <jiqing.feng@intel.com> * fix: for checking mandatory and optional pipeline components (huggingface#11189) fix: optional componentes verification on load * remove unnecessary call to `F.pad` (huggingface#10620) * rewrite memory count without implicitly using dimensions by @ic-synth * replace F.pad by built-in padding in Conv3D * in-place sums to reduce memory allocations * fixed trailing whitespace * file reformatted * in-place sums * simpler in-place expressions * removed in-place sum, may affect backward propagation logic * removed in-place sum, may affect backward propagation logic * removed in-place sum, may affect backward propagation logic * reverted change * allow models to run with a user-provided dtype map instead of a single dtype (huggingface#10301) * allow models to run with a user-provided dtype map instead of a single dtype * make style * Add warning, change `_` to `default` * make style * add test * handle shared tensors * remove warning --------- Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * [tests] HunyuanDiTControlNetPipeline inference precision issue on XPU (huggingface#11197) * add xpu part * fix more cases * remove some cases * no canny * format fix * Revert `save_model` in ModelMixin save_pretrained and use safe_serialization=False in test (huggingface#11196) * [docs] `torch_dtype` map (huggingface#11194) * Fix enable_sequential_cpu_offload in CogView4Pipeline (huggingface#11195) * Fix enable_sequential_cpu_offload in CogView4Pipeline * make fix-copies * SchedulerMixin from_pretrained and ConfigMixin Self type annotation (huggingface#11192) * Update import_utils.py (huggingface#10329) added onnxruntime-vitisai for custom build onnxruntime pkg * Add CacheMixin to Wan and LTX Transformers (huggingface#11187) * update * update * update * feat: [Community Pipeline] - FaithDiff Stable Diffusion XL Pipeline (huggingface#11188) * feat: [Community Pipeline] - FaithDiff Stable Diffusion XL Pipeline for Image SR. * added pipeline * [Model Card] standardize advanced diffusion training sdxl lora (huggingface#7615) * model card gen code * push modelcard creation * remove optional from params * add import * add use_dora check * correct lora var use in tags * make style && make quality --------- Co-authored-by: Aryan <aryan@huggingface.co> Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> * Change KolorsPipeline LoRA Loader to StableDiffusion (huggingface#11198) Change LoRA Loader to StableDiffusion Replace the SDXL LoRA Loader Mixin inheritance with the StableDiffusion one * Update Style Bot workflow (huggingface#11202) update style bot workflow --------- Signed-off-by: YAO Matrix <matrix.yao@intel.com> Signed-off-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: Aryan <aryan@huggingface.co> Co-authored-by: Mark <remarkablemark@users.noreply.github.com> Co-authored-by: hlky <hlky@hlky.ac> Co-authored-by: kakukakujirori <63725741+kakukakujirori@users.noreply.github.com> Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com> Co-authored-by: YiYi Xu <yixu310@gmail.com> Co-authored-by: Fanli Lin <fanli.lin@intel.com> Co-authored-by: Yao Matrix <matrix.yao@intel.com> Co-authored-by: jiqing-feng <jiqing.feng@intel.com> Co-authored-by: Eliseu Silva <elismasilva@gmail.com> Co-authored-by: Bruno Magalhaes <bruno.magalhaes@synthesia.io> Co-authored-by: Sayak Paul <spsayakpaul@gmail.com> Co-authored-by: lakshay sharma <31830611+Lakshaysharma048@users.noreply.github.com> Co-authored-by: Abhipsha Das <ad6489@nyu.edu> Co-authored-by: Basile Lewandowski <basile.lewan@gmail.com> Co-authored-by: célina <hanouticelina@gmail.com>
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why do this
In CUDA implementation,
reset_max_memory_allocatedis directly routed toreset_peak_memory_statsimplicitly, as in code https://github.com/pytorch/pytorch/blob/main/torch/cuda/memory.py#L471. So, for pytorch xpu, we didn't implementreset_max_memory_allocatedand suggest users to directly usereset_peak_memory_statsexplicitly.