data/prs.json

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    "body_excerpt": "# What does this PR do? Fixes # (issue) change rope dtype from torch.float64 to torch.float32 to support more gpu backends.",
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    "body_excerpt": "## Problem The `--text_encoder_out_layers` CLI argument in `train_dreambooth_lora_flux2_klein.py` defaults to `[10, 20, 30]`, but the pipeline implementation (`pipeline_flux2_klein.py`) uses `(9, 18, 27)`. This off-by-one mismatch causes t\u2026",
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    "body_excerpt": "This PR resolves the unsupported atten_mask shape error when running attention with NPU (Ascend) devices. Problem: The NPU\u2019s fusion attention operator (e.g., npu_fusion_attention) does not support automatic broadcasting for attention masks\u2026",
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    "body_excerpt": "## Summary - Fix all 9 QwenImage pipeline variants where CFG is silently disabled when passing `negative_prompt_embeds` with `None` mask - `encode_prompt()` converts all-ones masks to `None` as an optimization (line 266-267), but `has_neg_\u2026",
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    "body_excerpt": "# What does this PR do? As per #13446 `trust_remote_code` fails under several circumstances: - `pretrained_model_name_or_path` as Hub repo A and `custom_pipeline` as Hub repo B, `trust_remote_code` is bypassed and remote code runs from rep\u2026",
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    "body_excerpt": "### Description **We are the JoyAI Team,** and this is the Diffusers implementation for the JoyAI-Image-Edit model. GitHub Repository: [https://github.com/jd-opensource/JoyAI-Image] Hugging Face Model: [https://huggingface.co/jdopensource/\u2026",
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    "body_excerpt": "# What does this PR do? Fixes the prior-preservation batching issue in the Qwen Image DreamBooth LoRA script. PR #13396 corrected the repeat count under `--with_prior_preservation`, but the script still repeats prompt embeddings with `repe\u2026",
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    "body_excerpt": "\u2026nstead of latent resolution # What does this PR do? Fixes #13439 prepare_cond_latents_and_mask shadows the pixel height/width parameters with latent dims from latents.shape (line 614): ``` batch, channels, frames, height, width = latents.\u2026",
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    "body_excerpt": "Support JoyAIImagePipeline * https://github.com/jd-opensource/JoyAI-Image * [ jdopensource/JoyAI-Image-Edit](https://huggingface.co/jdopensource/JoyAI-Image-Edit) | Prompt | image | |----------|-------------| |NO |<img width=\"512\" height=\"\u2026",
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    "body_excerpt": "## Summary - Adds `scripts/convert_cogvideox_to_original.py`, a reverse conversion script that converts CogVideoX models (transformer and VAE) from diffusers format back to the original CogVideo checkpoint format - Reverses all weight name\u2026",
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    "body_excerpt": "## Summary Fixes two functional bugs in the experimental guiders module, both introduced in #11311 (Modular Diffusers Guiders): ### Bug 1: `TangentialClassifierFreeGuidance.is_conditional` \u2014 AttributeError The `is_conditional` property ref\u2026",
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    "body_excerpt": "# What does this PR do? We have introduced a new text-to-image model called ERNIE-Image, which will soon be open-sourced to the community. This PR includes the model architecture definition, the pipeline, as well as the related documentati\u2026",
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    "title": "Add ernie image",
    "updated_at": "2026-04-13T05:37:37Z"
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    "author": "huemin-art",
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    "body_excerpt": "# What does this PR do? Adds an optional `decoder_block_out_channels` parameter to `AutoencoderKLFlux2` so the decoder can use different channel widths than the encoder. This is needed to support the FLUX.2 small decoder VAE (`black-forest\u2026",
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    "author": "asomoza",
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    "body_excerpt": "# What does this PR do? Fixes the use of `record_stream` with `torchao` and `group offload`. Without this, the resulting image is wrong. |Without this PR|With this PR| |---|---| |<img width=\"1024\" height=\"1024\" alt=\"flux_benchmark_dynamic_\u2026",
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    "title": "[torchao] Fix `record_stream` with torchao and group offloading",
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    "additions": 6,
    "author": "Akash504-ai",
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    "body_excerpt": "# What does this PR do? This PR fixes a numerical stability issue in `rescale_noise_cfg` that can lead to division by zero and produce NaN/inf values during inference. ## Problem The current implementation performs: noise_pred_rescaled = n\u2026",
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    "title": "Fix division by zero in rescale_noise_cfg causing NaNs during inference",
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    "body_excerpt": "# What does this PR do? Fixes https://github.com/huggingface/diffusers/actions/runs/24034864516/job/70092362359?pr=13417. Got missed in the earlier refactor.",
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    "title": "[tests] fix autoencoderdc tests",
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    "body_excerpt": "## Summary - Fix `LoRA's` \u2192 `LoRAs` in two places (lines 104 and 106) - plural, not possessive - Fix `trigger it` \u2192 `trigger them` (pronoun agreement: \"Some LoRAs\" is plural) ## Changes **Line 104:** > Among adapters, [LoRA's] are the most\u2026",
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    "updated_at": "2026-04-10T16:18:30Z"
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    "body_excerpt": "## What does this PR do? Fixes #13421 Adds `negative_prompt` parameter to `GLMImagePipeline.__call__()` and `encode_prompt()`. Previously, the unconditional prompt was hardcoded to `\"\"` when CFG was active, with no way for users to provide\u2026",
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    "body_excerpt": "## What does this PR do? Fixes #13416 Adds `negative_prompt` parameter to `Flux2KleinPipeline.__call__()`. Previously, the unconditional prompt was hardcoded to `\"\"` when CFG was active, with no way for users to provide a custom negative p\u2026",
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    "additions": 14,
    "author": "azolotenkov",
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    "body_excerpt": "# What does this PR do? Fixes a device mismatch in the Flux2 DreamBooth training scripts when `--offload` is used and latents are not precomputed. non-cached path: `pixel_values` were converted to `vae.dtype` but not moved onto `accelerato\u2026",
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    "title": "Fix VAE offload encode device mismatch in DreamBooth scripts",
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    "additions": 16,
    "author": "azolotenkov",
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    "body_excerpt": "# What does this PR do? Fixes a prior-preservation batch size mismatch in the `Flux2 DreamBooth LoRA` scripts. When custom instance prompts are not used, `prompt_embeds` already contains concatenated instance + class embeddings under `--wi\u2026",
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    "title": "Fix Flux2 DreamBooth prior preservation prompt repeats",
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  {
    "additions": 11,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Fix article: `a inpainting` \u2192 `an inpainting` in auto_pipeline.py - Fix article: `a aesthetic_score` \u2192 `an aesthetic_score` in SDXL pipelines - Fix docstring: remove extraneous `pass a` in quantizers/base.py - Fix grammar: `al\u2026",
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    "title": "fix: correct grammar in docstrings and error messages",
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    "additions": 35,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Fix `it's` \u2192 `its` (possessive form) in ~35 instances across ~32 model files - The phrase \"Check the superclass documentation for it's generic methods\" should use \"its\" (possessive), not \"it's\" (contraction of \"it is\") - Also\u2026",
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    "conversation_url": "https://github.com/huggingface/diffusers/pull/13413",
    "created_at": "2026-04-04T17:05:39Z",
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    "title": "fix: correct possessive 'it's' to 'its' in model docstrings",
    "updated_at": "2026-04-04T17:05:39Z"
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    "additions": 307,
    "author": "VittoriaLanzo",
    "author_association": "NONE",
    "body_excerpt": "## What does this PR do? Fixes #13411. `LTXEulerAncestralRFScheduler.set_timesteps(sigmas=...)` silently accepted non-monotone sigma schedules. In `step()`, a reversed schedule computes: ``` downstep_ratio = 1 + (sigma_next / sigma - 1) *\u2026",
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    "created_at": "2026-04-04T15:49:39Z",
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    "title": "[Scheduler] Add monotonicity validation and tests for LTXEulerAncestr\u2026",
    "updated_at": "2026-04-06T22:54:31Z"
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    "additions": 40,
    "author": "yiyixuxu",
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    "body_excerpt": "follow https://github.com/huggingface/diffusers/pull/13334 moved `model-integrawtion/skillls/modular-conversion.md` to `.ai/modular.md`, and link it from `AGENTS.md`, `model-integrawtion/skillls` and `review-rules.md ` added a Gotcha secti\u2026",
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    "title": "[agent] add modular doc",
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    "additions": 32,
    "author": "awsr",
    "author_association": "FIRST_TIME_CONTRIBUTOR",
    "body_excerpt": "# What does this PR do? Fixes `NameError: name 'ftfy' is not defined` This was encountered by one of our users on SDNext. I'm not entirely sure why `ftfy` didn't get installed, but if it's optionally imported then it should also be optiona\u2026",
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    "created_at": "2026-04-04T02:02:23Z",
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    "title": "Guard against calling optional `ftfy` module if not available",
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    "additions": 7,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Fix duplicate words: `schedule schedule` \u2192 `schedule`, `obtain obtain` \u2192 `obtain` - Fix article usage: `a image` \u2192 `an image` (2 instances), `a image-text` \u2192 `an image-text` (2 instances), `a upsampling` \u2192 `an upsampling` ## T\u2026",
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    "conversation_url": "https://github.com/huggingface/diffusers/pull/13408",
    "created_at": "2026-04-03T23:40:41Z",
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    "title": "fix: remove duplicate words and fix grammar in docstrings and error messages",
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    "additions": 54,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary Add missing `f` prefix to ~50 string literals where variables like `{self.__class__}`, `{self.config}`, `{unet.config.*}`, `{type(...)}` are printed as literal text instead of being interpolated. ### Categories fixed: - Safety c\u2026",
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    "title": "fix: add missing f-string prefixes across pipelines and schedulers",
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    "additions": 25,
    "author": "akshan-main",
    "author_association": "CONTRIBUTOR",
    "body_excerpt": "## What does this PR do? Part of #13401 `QwenEmbedRope.forward()` copies `pos_freqs` and `neg_freqs` from CPU to GPU via `.to(device)` on every transformer forward call. These tensors are fixed at init and never change, so the repeated tra\u2026",
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    "created_at": "2026-04-03T21:17:17Z",
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    "title": "Cache RoPE freqs on device to avoid repeated CPU-GPU copy in QwenImage",
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    "additions": 23,
    "author": "andrewor14",
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    "body_excerpt": "**Summary:** TorchAO recently deprecated AffineQuantizedTensor and related classes (https://github.com/pytorch/ao/issues/2752). These will be removed in the next release. We should remove references of these classes in diffusers before the\u2026",
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    "conversation_url": "https://github.com/huggingface/diffusers/pull/13405",
    "created_at": "2026-04-03T20:31:12Z",
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    "title": "Remove references to torchao's AffineQuantizedTensor",
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  {
    "additions": 152,
    "author": "varaprasadtarunkumar",
    "author_association": "NONE",
    "body_excerpt": "## What does this PR do? Fixes a per-step `torch.tensor()` reconstruction in `QwenImageTransformer2DModel.forward()` that was identified as a known performance issue in the [profiling guide](https://github.com/huggingface/diffusers/tree/ma\u2026",
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    "title": "fix: cache modulate_index tensor to eliminate per-step DtoH sync",
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    "additions": 4,
    "author": "Ricardo-M-L",
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    "body_excerpt": "## Summary - Add missing `f` prefix to 4 log messages in `bnb_quantizer.py` where `{target_dtype}` and `{current_device}` are printed as literal text instead of being interpolated - Affects both 4-bit and 8-bit BnB quantizer classes ## Tes\u2026",
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    "title": "fix: add missing f-string prefixes in BnB quantizer log messages",
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    "body_excerpt": "Two types of exception handling bugs: **1. `raise \"string\"` in attention_processor.py (lines 328-332)** \\`raise \"string\"\\` causes \\`TypeError: exceptions must derive from BaseException\\` at runtime instead of the intended error message. Ch\u2026",
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    "body_excerpt": "# What does this PR do? I found that the same problem in https://github.com/huggingface/diffusers/issues/13292 also appears in Qwen-Image's dreambooth lora script. https://github.com/huggingface/diffusers/blob/8070f6ec54a7699d5ee285090d973\u2026",
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    "body_excerpt": "# What does this PR do? This PR fixes a missing validation in `DDPMScheduler.set_timesteps`. Currently, passing `num_inference_steps=0` does not raise an error and can lead to invalid internal state or unexpected behavior. This behavior is\u2026",
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    "body_excerpt": "## Summary Fixes several typos and grammar errors across the documentation: 1. **`controlling_generation.md`**: \"allows to generate\" \u2192 \"allows you to generate\" (missing object after \"allows\") 2. **`sdxl.md`**: \"it's refiner model\" \u2192 \"its r\u2026",
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    "body_excerpt": "# What does this PR do? Adds [LongCat-AudioDiT](https://github.com/meituan-longcat/LongCat-AudioDiT) model support to diffusers. Although LongCat-AudioDiT can be used for TTS-like generation, it is fundamentally a diffusion-based audio gen\u2026",
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    "body_excerpt": "# What does this PR do? When running the `train_dreambooth_lora_qwen_image.py `script with the `--with_prior_preservation` flag, the training crashes during the text embedding extraction phase. Fixing two distinct bugs related to tensor co\u2026",
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    "body_excerpt": "## \ud83d\udd12 Pin GitHub Actions to commit SHAs This PR pins all GitHub Actions to their exact commit SHA instead of mutable tags or branch names. **Why?** Pinning to a SHA prevents supply chain attacks where a tag (e.g. `v4`) could be moved to poi\u2026",
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    "body_excerpt": "## What does this PR do? Fixes Dynamo `lru_cache` warnings when using `torch.compile` on diffusion pipelines. Two changes: 1. **`attention_dispatch.py`**: `dispatch_attention_fn` calls `is_torch_version(\">=\", \"2.5.0\")` at runtime, which is\u2026",
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    "body_excerpt": "# What does this PR do? Add a skill for all the optimizations that can be done with diffusers. At the moment it has a lot of information and still with this the LLM (Opus 4.6) is still a hit or miss with the optimizations, specially with w\u2026",
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    "body_excerpt": "# What does this PR do? Addresses suggestions brought up in #13343 by adding scripts/workflows to auto labels issues and PRs . For Issues: Use `Qwen/Qwen3.5-35B-A3B` via Inference Providers to parse issues titles and content and assign app\u2026",
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    "body_excerpt": "# What does this PR do? Adds modular pipeline support for LTX Video, covering both text-to-video and image-to-video. The implementation follows the same structure as the existing Wan modular pipeline. ### Text-to-video ``` LTXBlocks (Seque\u2026",
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    "body_excerpt": "This PR adds local flash attention 4. Package required: [flash-attn-4](https://pypi.org/project/flash-attn-4/) (flash_attn.cute) Note: flash_4_hub already in the code but points to kernels-staging/flash-attn4 not publicly available. When i\u2026",
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    "author": "HMAKT99",
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    "body_excerpt": "# What does this PR do? Adds low precision attention API from TorchAO to diffusers by updating TorchAoConfig with attn_backend option. Note: this will require torchao 0.17.0 ## Todo: - [ ] Need to add new necessary tests - [ ] Need to upda\u2026",
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    "body_excerpt": "# What does this PR do? Fix issue #13277. QwenImagePipeline cannot run with Ulysses SP together with batch prompt inputs. It is related to the mask is not correctly broadcasted. We need to broadcast the attention mask from [B, S] to [B, H,\u2026",
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    "body_excerpt": "## Summary Fixes #13124 `log_validation()` in dreambooth training scripts runs pipeline inference using the same UNet/transformer that is being trained, without `torch.no_grad()`. With `--mixed_precision=\"fp16\"`, gradients are computed and\u2026",
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    "body_excerpt": "## Summary Fixes #12913 - **Bug**: `image_seq_len = latents.shape[1]` takes the **channel dimension** (e.g. 16) instead of the spatial sequence length. Lumina2 latents have shape `(batch, channels, height, width)` and are NOT packed before\u2026",
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    "body_excerpt": "# What does this PR do? Oversight on my part when adding #13168. We avoid passing `torch_dtype` to non `nn.Modules` such as Processors and Tokenizers because these objects do not accept that anymore and instead store it in init_kwargs whic\u2026",
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    "body_excerpt": "fix tests/models/transformers/test_models_transformer_flux.py::TestFluxTransformerContextParallel::test_context_parallel_inference[ulysses] tests/models/transformers/test_models_transformer_flux.py::TestFluxTransformerContextParallel::test\u2026",
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    "body_excerpt": "## Summary Adds support for the [DiffSynth-Studio blockwise ControlNet](https://github.com/modelscope/DiffSynth-Studio) architecture to the existing `QwenImageControlNetModel`, addressing [the maintainer's feedback on PR #12317](https://gi\u2026",
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    "body_excerpt": "# What does this PR do? One-line fix \u2014 missing self.gradient_checkpointing = False init, consistent with all other ControlNet implementations <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, you\u2026",
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    "body_excerpt": "Fixed issue #13177 ## The problem If you pass a tensor or numpy array as the image to the Klein pipeline, it errors even though the docstring explicitly says these types are supported. Three things cause this: - The image processor's valid\u2026",
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    "body_excerpt": "# What does this PR do? * Introduces `Flux2Transformer2DModelOutput` class as its outputs differ from the rest of the lot. * Test suite for Klein KV. * Docs.",
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    "body_excerpt": "Summary: Very brief writeup as I'm about to head out for the day: 1. we want to enable cuda graphs for qwen-image + nvfp4 at small batch sizes, because without cuda graphs are we bottlenecked on cpu ops 2. to make cuda graphs work, we need\u2026",
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    "body_excerpt": "# What does this PR do? Adds `Flux2KleinKVPipeline` \u2014 a KV-cached reference image conditioning pipeline for Flux2 Klein 9B. On the first denoising step, reference image tokens are included in the full transformer forward pass and their pos\u2026",
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    "body_excerpt": "## Summary Use safe dict access for alpha keys when converting non-diffusers Z-Image LoRA to diffusers format. Some LoRA formats use different alpha key naming (e.g. `layers.0.adaLN_modulation.0.alpha`), causing KeyError. ## Root Cause `st\u2026",
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    "body_excerpt": "# What does this PR do? This PR adds the `PRXPipeline` in the `AUTO_TEXT2IMAGE_PIPELINES_MAPPING`, so that PRX models e.g. https://huggingface.co/Photoroom/prx-1024-t2i-beta, can be loaded with the `AutoPipelineForText2Image` as it's curre\u2026",
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    "title": "[lora] fix z-image non-diffusers lora loading.",
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    "body_excerpt": "@yiyixuxu and @asomoza, pls help review, thx! This PR fixes bug for following sample code: ``` import torch from diffusers import PaintByExamplePipeline from PIL import Image, ImageDraw # Load the pipeline pipe = PaintByExamplePipeline.fro\u2026",
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    "body_excerpt": "- Moves cosmos to the \"video\" model section - Updates the main example - Minor updates to docstrings in cosmos transfer2.5 pipeline Review: - Docs: @stevhliu and @sayakpaul",
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    "body_excerpt": "## Summary The `_convert_non_diffusers_z_image_lora_to_diffusers` function did not consume LoKr-format keys (`.lokr_w1`, `.lokr_w2`, `.alpha`) from external Z-image LoRA checkpoints (e.g. Kohya/LyCORIS), causing a `ValueError` when the sta\u2026",
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    "body_excerpt": "a few maintenance items: - move \"Guiders\" out of Modular Diffusers (because its not exclusive to it). i think after \"Schedulers\" is the most logical place for guiders as they're both swappable components and it has a much higher visibility\u2026",
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    "body_excerpt": "# What does this PR do? Implements a test suite for the conditional blocks for the following functionalities: * `get_workflow()` works as expected. * `select_blocks()` works as expected. * Automatic workflow selection works as expected. Th\u2026",
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    "body_excerpt": "# What does this PR do? Fixes a bug where `sigma_min` and `sigma_max` were computed from already-shifted sigmas in `__init__`, causing `set_timesteps()` to apply the shift formula twice. Fixes #13243 ## Root cause In `__init__`, the shift\u2026",
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    "body_excerpt": "# What does this PR do? Add tests (two tests: loading from a modular repo and loading from a local path) to ensure `load_components()` always loads the expected components. Here, I took the liberty of defining `expected_components` as the\u2026",
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    "body_excerpt": "## Summary Fixes #12771 \u2014 `DPMSolverMultistepScheduler` crashes with `IndexError: index 21 is out of bounds for dimension 0 with size 21` when using `beta_schedule='squaredcos_cap_v2'` with `use_karras_sigmas=True`. ## Root Cause When usin\u2026",
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    "title": "fix: deduplicate timesteps in DPMSolverMultistep for squaredcos_cap_v2 + karras/lu sigmas",
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    "body_excerpt": "## What does this PR do? Fixes #12771 \u2014 `DPMSolverMultistepScheduler` crashes with `IndexError: index N is out of bounds` when using `beta_schedule='squaredcos_cap_v2'` with `use_karras_sigmas=True` (or `use_lu_lambdas=True`). ### Root cau\u2026",
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    "body_excerpt": "## Description In `_offload_to_memory()`, when using CUDA streams (`self.stream is not None`), module buffers from `self.modules` were not being restored to their CPU tensor copies during offload. This created an asymmetry with both `_buil\u2026",
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    "body_excerpt": "# What does this PR do? It enables detection of FLUX.2 Klein models when loading transformers from single file, like in the following example: ```python import torch from diffusers import Flux2KleinPipeline, Flux2Transformer2DModel, GGUFQu\u2026",
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    "body_excerpt": "# What does this PR do? I believe that the error message was wrong, since the shapes mentionned did not match the test trigering the error. I think that there is also an ambiguity on what is meant by \"quantized\" shape: the value returned b\u2026",
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    "body_excerpt": "# What does this PR do? - [x] Refactor MagCache tests. - [x] Include TaylorSeer in our model-level caching test mixin. - [ ] Consider removing caching-related mixins from `test_pipelines_common.py`.",
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    "body_excerpt": "Potential fix for [https://github.com/huggingface/diffusers/security/code-scanning/2147](https://github.com/huggingface/diffusers/security/code-scanning/2147) In general, the fix is to explicitly set a `permissions` block in the workflow (\u2026",
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    "body_excerpt": "# What does this PR do? This PR adds support for [Diffusion Transformers with Representation Autoencoders](https://rae-dit.github.io) in Diffusers. It implements the Stage-2 side of the RAE setup: - `RAEDiT2DModel` - `RAEDiTPipeline` - che\u2026",
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    "body_excerpt": "This PR adds LTX-VAE support for SANA-Video. Cc: @dg845 @sayakpaul GPU memory needed: 47GB for LTX refiner ### SANA-Video with LTX2-Refiner: ```python \"\"\"Sana Video + LTX2 Refiner: Stage 1 generate latent \u2192 Stage 2 refine (3 steps).\"\"\" imp\u2026",
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    "body_excerpt": "Allow pass cpu generator for helios. w/o this fix, helios distilled pipeline will raise an device mismatch error if we use cpu generator. we should use the device from generator for torch.randn. ```bash File \"/workspace/deftruth/dev/minico\u2026",
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    "body_excerpt": "cc @dg845 @sayakpaul @yiyixuxu ### Helios-Distilled ``` # CUDA_VISIBLE_DEVICES=0,1,2,3 torchrun --master_port 12311 --nproc_per_node 2 infer_distilled.py import os import argparse import torch import torch.distributed as dist from diffuser\u2026",
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    "body_excerpt": "# What does this PR do? This PR refactors `AttentionProcessorSkipHook` to support attention processors with a `_skip_attn_scores` flag, which is meant to allow attention processors to specify custom [spatio-temporal guidance (STG)](https:/\u2026",
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    "body_excerpt": "# What does this PR do? This PR fixes wrapped transformer config access in the Flux2 Klein DreamBooth LoRA training scripts. When the transformer is wrapped by Accelerate, DDP, or FSDP, accessing `transformer.config.guidance_embeds` direct\u2026",
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    "body_excerpt": "In helios pipeline, the latents are always in FP32 format: [L798](https://github.com/huggingface/diffusers/blob/main/src/diffusers/pipelines/helios/pipeline_helios.py#L798), hence we should skip the test_save_load_float16 test case, rather\u2026",
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    "body_excerpt": "# What does this PR do? This PR adds support for LTX-2.3 ([official code](https://github.com/Lightricks/LTX-2), [model weights](https://huggingface.co/Lightricks/LTX-2.3)), a new model in the LTX-2.X family of audio-video models. LTX-2.3 h\u2026",
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    "body_excerpt": "```py import torch from diffusers import ModularPipeline, ClassifierFreeGuidance, ClassifierFreeZeroStarGuidance from diffusers.utils import export_to_video, load_image, load_video import gc branch = \"\" ############################# # heli\u2026",
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    "title": "post release 0.37.0",
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    "title": "Convert tensors to float in Helios's optimized_scale function",
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    "title": "Fix Helios paper link in documentation",
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    "body_excerpt": "Just an extension of #13183 to the other Z-Image pipleines @yiyixuxu @sayakpaul",
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    "body_excerpt": "Related to https://github.com/huggingface/diffusers/pull/13208 and https://github.com/huggingface/diffusers/pull/13210 cc @yiyixuxu cc @sayakpaul cc @dg845",
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    "title": "Fix Helios related (optimize docs & remove redudant)",
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    "body_excerpt": "# What does this PR do? This PR adds pipelines for the Helios-14B video generation model ([project page](https://pku-yuangroup.github.io/Helios-Page/), [official code](https://github.com/PKU-YuanGroup/Helios), [model weights](https://huggi\u2026",
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    "body_excerpt": "Currently, every process encodes the entire dataset through the VAE during preprocessing. This is redundant in multi-GPU training \u2014 each process does the same full encoding work independently. This PR shards the VAE encoding across process\u2026",
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    "body_excerpt": "## Summary - Add `scheduler.set_begin_index(0)` before the denoising loop in all flow-matching pipelines that were missing it - For img2img pipelines with strength-based schedule truncation (`wan_video2video`, `ltx_condition`), set the beg\u2026",
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    "body_excerpt": "# What does this PR do? Fixes invalid type annotation for the `image` parameter in `Flux2Pipeline.__call__`. `list[PIL.Image.Image, PIL.Image.Image]` passes two type arguments to `list`, which only accepts one. Fixed to `PIL.Image.Image |\u2026",
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    "body_excerpt": "# What does this PR do? Why not use `pytest` features haha.",
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    "body_excerpt": "so that we are able to correctly load repos like https://huggingface.co/diffusers/flux2-modular When creating a pipeline using `SequentialPipelineBlocks.from_blocks_dict()` and saving it, the `modular_model_index.json` stores `_blocks_clas\u2026",
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    "body_excerpt": "# What does this PR do? `modular_model_index.json` is a fundamental block for sharing and loading modular blocks and pipelines. This PR adds a test to ensure the integrity and consistency of a `modular_model_index.json`. I think this will\u2026",
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    "body_excerpt": "## What does this PR do? Fixes None dereference crashes and a mutable default argument bug: **1. `models/model_loading_utils.py`** - `_fetch_remapped_cls_from_config` used chained `.get().get()` without a fallback on the first call. If `pr\u2026",
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    "body_excerpt": "I added support for Kohya's Flux.2 loras to the PR as well. Reproducer code is: FLUX.2 Dev ```python import torch from diffusers import Flux2Pipeline pipe = Flux2Pipeline.from_pretrained(\"black-forest-labs/FLUX.2-dev\", torch_dtype=torch.bf\u2026",
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    "body_excerpt": "Text encoder lora layers are dropped for some loras such as [this one](https://huggingface.co/scenario-labs/big-head-kontext-lora/blob/main/flux_kontext_lora.safetensors) A log message confirms it: `No LoRA keys associated to CLIPTextModel\u2026",
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    "body_excerpt": "# What does this PR do? Add `regisiter_for_auto_class` method to `ConfigMixin` so that we don't have to manually edit the `config.json` file to add the `auto_map` field that we need to load custom code models. <!-- Congratulations! You've\u2026",
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    "body_excerpt": "## What does this PR do? Fixes several latent bugs across the codebase: **Mutable default arguments** (shared state across calls): - `_replace_with_gguf_linear`: `modules_to_not_convert=[]` -> `None` with guard - `_dequantize_gguf_and_rest\u2026",
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    "body_excerpt": "## Summary - Z-Image uses a different CFG formula: `pred = pos + guidance_scale * (pos - neg)`, where `guidance_scale = 0` corresponds to no guidance - The `do_classifier_free_guidance` property was checking `> 1` (standard diffusers conve\u2026",
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    "body_excerpt": "# What does this PR do? * Fixes support for ring attention for Flash and Flash 3 * Adds a test suite for CP backends x attention backends <img width=\"1024\" height=\"1024\" alt=\"image\" src=\"https://github.com/user-attachments/assets/2600632f-\u2026",
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    "body_excerpt": "# What does this PR do? Since Quanto is now in maintenance mode. I think we can deprecate it and remove by 1.0.0 <!-- Congratulations! You've made it this far! You're not quite done yet though. Once merged, your PR is going to appear in th\u2026",
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    "body_excerpt": "## Summary Closes #13104 Issue #13104 reports a `NameError: name 'logger' is not defined` that occurs at import time when `_update_torch_safe_globals()` in `torchao_quantizer.py` raises an `ImportError` (e.g. when `torchao.dtypes.uintx.uin\u2026",
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    "body_excerpt": "# What does this PR do? k-diffusion package is no longer maintained (last release was 3 years ago). We've already deprecated the pipeline, but I think we can remove it completely since it's introducing dependency issues in the CI. <!-- Con\u2026",
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    "body_excerpt": "was reverted in https://github.com/huggingface/diffusers/pull/12524/changes#r2807900601 z-image generate blury image otherwise ``` import torch from diffusers import ModularPipeline device = \"cuda\" # 1. Load the pipeline # Use bfloat16 for\u2026",
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    "body_excerpt": "otherwise cannot load modular blocks like this with `ModularPipeline.from_pretrained()` directly https://huggingface.co/diffusers/flux2-modular",
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    "body_excerpt": "# What does this PR do? LTX2 has the incorrect lora mixing which prevents using LTX2 lora with it. This PR fixes that. ## Who can review? @sayakpaul @dg845",
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    "body_excerpt": "# What does this PR do? This PR fixes a dimension mismatch in the attention mask handling for the HunyuanVideo1.5 VAE implementation in `autoencoder_kl_hunyuanvideo15.py`. #### Problem In the current implementation (line 148 of `autoencode\u2026",
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