GitLab

* Add torch_xla support to pipeline_aura_flow.py

* make style

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Co-authored-by: hlky <hlky@hlky.ac>

* feat: support unload_lora_weights() for Flux Control.

* tighten test

* minor

* updates

* meta device fixes.

* Revert "Add support for sharded models when TorchAO quantization is enabled (#10256)"

This reverts commit 41ba8c0b

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* update tests

* udpate

* update

* update

* update device map tests

* apply review suggestions

* update

* make style

* fix

* update docs

* update tests

* update workflow

* update

* improve tests

* allclose tolerance

* Update src/diffusers/models/modeling_utils.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* Update tests/quantization/torchao/test_torchao.py
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* improve tests

* fix

* update correct slices

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

* fix: registration of out_channels in the control flux scripts.

* free memory.

fix bug on xpu

Make passing the IP Adapter mask to the attention mechanism optional if there is no need to apply it to a given IP Adapter.

* fix bug for torch.uint1-7 not support in torch<2.6

* up

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Co-authored-by: baymax591 <cbai@mail.nwpu.edu.cn>

Update community_projects.md

fix

* post release 0.32.0

* stylew

* update

* make style

* update

* update

* update

* make style

* single file related changes

* update

* fix

* update single file urls and docs

* update

* fix

* fixes to tests

* fixture

* fixes

updates

* rename blocks and docs

* fix docs

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Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>

fix

* misc lora test improvements.

* updates

* fixes to tests

update

* sana lora training tests and misc.

* remove push to hub

* Update examples/dreambooth/train_dreambooth_lora_sana.py
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

refactor

fix: torchao example.

* bump min torchao version to 0.7.0

* update

Add missing `.shape`

* fix the Positinoal Embedding bug in 2K model;

* Change the default model to the BF16 one for more stable training and output

* make style

* substract buffer size

* add compute_module_persistent_sizes

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Co-authored-by: yiyixuxu <yixu310@gmail.com>

* update

* Update src/diffusers/loaders/single_file_utils.py
Co-authored-by: Aryan <aryan@huggingface.co>

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Co-authored-by: Aryan <aryan@huggingface.co>

add:
q

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

update docs and example to use community weights

* flux controlnet inpaint config bug

* Update src/diffusers/pipelines/flux/pipeline_flux_controlnet_inpainting.py

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Co-authored-by: yigitozgenc <yigit@quantuslabs.ai>
Co-authored-by: hlky <hlky@hlky.ac>

* Flux IP-Adapter

* test cfg

* make style

* temp remove copied from

* fix test

* fix test

* v2

* fix

* make style

* temp remove copied from

* Apply suggestions from code review
Co-authored-by: YiYi Xu <yixu310@gmail.com>

* Move encoder_hid_proj to inside FluxTransformer2DModel

* merge

* separate encode_prompt, add copied from, image_encoder offload

* make

* fix test

* fix

* Update src/diffusers/pipelines/flux/pipeline_flux.py

* test_flux_prompt_embeds change not needed

* true_cfg -> true_cfg_scale

* fix merge conflict

* test_flux_ip_adapter_inference

* add fast test

* FluxIPAdapterMixin not test mixin

* Update pipeline_flux.py
Co-authored-by: YiYi Xu <yixu310@gmail.com>

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Co-authored-by: YiYi Xu <yixu310@gmail.com>

Update gguf.md to remove generator from the pipeline from_pretrained

add 2K related model for Sana

Update overview.md

[BUG FIX] [Stable Audio Pipeline] Resolve torch.Tensor.new_zeros() TypeError in function prepare_latents caused by audio_vae_length (#10306)

[BUG FIX] [Stable Audio Pipeline] TypeError: new_zeros(): argument 'size' failed to unpack the object at pos 3 with error "type must be tuple of ints,but got float"

torch.Tensor.new_zeros() takes a single argument size (int...) – a list, tuple, or torch.Size of integers defining the shape of the output tensor.

in function prepare_latents:
audio_vae_length = self.transformer.config.sample_size * self.vae.hop_length
audio_shape = (batch_size // num_waveforms_per_prompt, audio_channels, audio_vae_length)
...
audio = initial_audio_waveforms.new_zeros(audio_shape)

audio_vae_length evaluates to float because self.transformer.config.sample_size returns a float
Co-authored-by: hlky <hlky@hlky.ac>

Update pipeline_hunyuan_video.py

docs: fix a mistake

Update ltx_video.md to remove generator from `from_pretrained()`

* update

* update

* update

* update

* update

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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

add integration tests for lora expansion stuff in Flux.