* Bria FIBO pipeline
* style fixs
* fix CR
* Refactor BriaFibo classes and update pipeline parameters
- Updated BriaFiboAttnProcessor and BriaFiboAttention classes to reflect changes from Flux equivalents.
- Modified the _unpack_latents method in BriaFiboPipeline to improve clarity.
- Increased the default max_sequence_length to 3000 and added a new optional parameter do_patching.
- Cleaned up test_pipeline_bria_fibo.py by removing unused imports and skipping unsupported tests.
* edit the docs of FIBO
* Remove unused BriaFibo imports and update CPU offload method in BriaFiboPipeline
* Refactor FIBO classes to BriaFibo naming convention
- Updated class names from FIBO to BriaFibo for consistency across the module.
- Modified instances of FIBOEmbedND, FIBOTimesteps, TextProjection, and TimestepProjEmbeddings to reflect the new naming.
- Ensured all references in the BriaFiboTransformer2DModel are updated accordingly.
* Add BriaFiboTransformer2DModel import to transformers module
* Remove unused BriaFibo imports from modular pipelines and add BriaFiboTransformer2DModel and BriaFiboPipeline classes to dummy objects for enhanced compatibility with torch and transformers.
* Update BriaFibo classes with copied documentation and fix import typo in pipeline module
- Added documentation comments indicating the source of copied code in BriaFiboTransformerBlock and _pack_latents methods.
- Corrected the import statement for BriaFiboPipeline in the pipelines module.
* Remove unused BriaFibo imports from __init__.py to streamline modular pipelines.
* Refactor documentation comments in BriaFibo classes to indicate inspiration from existing implementations
- Updated comments in BriaFiboAttnProcessor, BriaFiboAttention, and BriaFiboPipeline to reflect that the code is inspired by other modules rather than copied.
- Enhanced clarity on the origins of the methods to maintain proper attribution.
* change Inspired by to Based on
* add reference link and fix trailing whitespace
* Add BriaFiboTransformer2DModel documentation and update comments in BriaFibo classes
- Introduced a new documentation file for BriaFiboTransformer2DModel.
- Updated comments in BriaFiboAttnProcessor, BriaFiboAttention, and BriaFiboPipeline to clarify the origins of the code, indicating copied sources for better attribution.
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Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
* rename photon to prx
* rename photon into prx
* Revert .gitignore to state before commit b7fb0fe9d6
* rename photon to prx
* rename photon into prx
* Revert .gitignore to state before commit b7fb0fe9d6
* make fix-copies
* purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet
* purge HF_HUB_ENABLE_HF_TRANSFER; promote Xet x2
* restrict docker build test to the ones we actually use in CI.
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Co-authored-by: YiYi Xu <yixu310@gmail.com>
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
* Add Photon model and pipeline support
This commit adds support for the Photon image generation model:
- PhotonTransformer2DModel: Core transformer architecture
- PhotonPipeline: Text-to-image generation pipeline
- Attention processor updates for Photon-specific attention mechanism
- Conversion script for loading Photon checkpoints
- Documentation and tests
* just store the T5Gemma encoder
* enhance_vae_properties if vae is provided only
* remove autocast for text encoder forwad
* BF16 example
* conditioned CFG
* remove enhance vae and use vae.config directly when possible
* move PhotonAttnProcessor2_0 in transformer_photon
* remove einops dependency and now inherits from AttentionMixin
* unify the structure of the forward block
* update doc
* update doc
* fix T5Gemma loading from hub
* fix timestep shift
* remove lora support from doc
* Rename EmbedND for PhotoEmbedND
* remove modulation dataclass
* put _attn_forward and _ffn_forward logic in PhotonBlock's forward
* renam LastLayer for FinalLayer
* remove lora related code
* rename vae_spatial_compression_ratio for vae_scale_factor
* support prompt_embeds in call
* move xattention conditionning out computation out of the denoising loop
* add negative prompts
* Use _import_structure for lazy loading
* make quality + style
* add pipeline test + corresponding fixes
* utility function that determines the default resolution given the VAE
* Refactor PhotonAttention to match Flux pattern
* built-in RMSNorm
* Revert accidental .gitignore change
* parameter names match the standard diffusers conventions
* renaming and remove unecessary attributes setting
* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* quantization example
* added doc to toctree
* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
* use dispatch_attention_fn for multiple attention backend support
* naming changes
* make fix copy
* Update docs/source/en/api/pipelines/photon.md
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
* Add PhotonTransformer2DModel to TYPE_CHECKING imports
* make fix-copies
* Use Tuple instead of tuple
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
* restrict the version of transformers
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
* Update tests/pipelines/photon/test_pipeline_photon.py
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
* Update tests/pipelines/photon/test_pipeline_photon.py
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
* change | for Optional
* fix nits.
* use typing Dict
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Co-authored-by: davidb <davidb@worker-10.soperator-worker-svc.soperator.svc.cluster.local>
Co-authored-by: David Briand <david@photoroom.com>
Co-authored-by: davidb <davidb@worker-8.soperator-worker-svc.soperator.svc.cluster.local>
Co-authored-by: Steven Liu <59462357+stevhliu@users.noreply.github.com>
Co-authored-by: dg845 <58458699+dg845@users.noreply.github.com>
Co-authored-by: sayakpaul <spsayakpaul@gmail.com>
I noticed that the test should be for the option check_compiled="ignore"
but it was using check_compiled="warn". This has been fixed, now the
correct argument is passed.
However, the fact that the test passed means that it was incorrect to
begin with. The way that logs are collected does not collect the
logger.warning call here (not sure why). To amend this, I'm now using
assertNoLogs. With this change, the test correctly fails when the wrong
argument is passed.
* cache non lora pipeline outputs.
* up
* up
* up
* up
* Revert "up"
This reverts commit 772c32e433.
* up
* Revert "up"
This reverts commit cca03df7fc.
* up
* up
* add .
* up
* up
* up
* up
* up
* up
* Convert alphas for embedders for sd-scripts to ai toolkit conversion
* Add kohya embedders conversion test
* Apply style fixes
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Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* support Wan2.2-VACE-Fun-A14B
* support Wan2.2-VACE-Fun-A14B
* support Wan2.2-VACE-Fun-A14B
* Apply style fixes
* test
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Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>
* Add Bria model and pipeline to diffusers
- Introduced `BriaTransformer2DModel` and `BriaPipeline` for enhanced image generation capabilities.
- Updated import structures across various modules to include the new Bria components.
- Added utility functions and output classes specific to the Bria pipeline.
- Implemented tests for the Bria pipeline to ensure functionality and output integrity.
* with working tests
* style and quality pass
* adding docs
* add to overview
* fixes from "make fix-copies"
* Refactor transformer_bria.py and pipeline_bria.py: Introduce new EmbedND class for rotary position embedding, and enhance Timestep and TimestepProjEmbeddings classes. Add utility functions for handling negative prompts and generating original sigmas in pipeline_bria.py.
* remove redundent and duplicates tests and fix bf16
slow test
* style fixes
* small doc update
* Enhance Bria 3.2 documentation and implementation
- Updated the GitHub repository link for Bria 3.2.
- Added usage instructions for the gated model access.
- Introduced the BriaTransformerBlock and BriaAttention classes to the model architecture.
- Refactored existing classes to integrate Bria-specific components, including BriaEmbedND and BriaPipeline.
- Updated the pipeline output class to reflect Bria-specific functionality.
- Adjusted test cases to align with the new Bria model structure.
* Refactor Bria model components and update documentation
- Removed outdated inference example from Bria 3.2 documentation.
- Introduced the BriaTransformerBlock class to enhance model architecture.
- Updated attention handling to use `attention_kwargs` instead of `joint_attention_kwargs`.
- Improved import structure in the Bria pipeline to handle optional dependencies.
- Adjusted test cases to reflect changes in model dtype assertions.
* Update Bria model reference in documentation to reflect new file naming convention
* Update docs/source/en/_toctree.yml
* Refactor BriaPipeline to inherit from DiffusionPipeline instead of FluxPipeline, updating imports accordingly.
* move the __call__ func to the end of file
* Update BriaPipeline example to use bfloat16 for precision sensitivity for better result
* make style && make quality && make fix-copiessource
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Co-authored-by: Linoy Tsaban <57615435+linoytsaban@users.noreply.github.com>
Co-authored-by: Aryan <contact.aryanvs@gmail.com>
