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‎docs/source/en/_toctree.yml‎

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- local: tutorials/autopipeline
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title: AutoPipeline
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- local: using-diffusers/custom_pipeline_overview
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title: Load community pipelines and components
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title: Community pipelines and components
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- local: using-diffusers/callback
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title: Pipeline callbacks
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- local: using-diffusers/reusing_seeds

‎docs/source/en/api/pipelines/overview.md‎

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## PushToHubMixin
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[[autodoc]] utils.PushToHubMixin
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## Callbacks
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[[autodoc]] callbacks.PipelineCallback
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[[autodoc]] callbacks.SDCFGCutoffCallback
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[[autodoc]] callbacks.SDXLCFGCutoffCallback
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[[autodoc]] callbacks.SDXLControlnetCFGCutoffCallback
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[[autodoc]] callbacks.IPAdapterScaleCutoffCallback
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[[autodoc]] callbacks.SD3CFGCutoffCallback

‎docs/source/en/api/pipelines/qwenimage.md‎

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- all
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- __call__
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## QwenImaggeControlNetPipeline
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- all
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- __call__
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## QwenImagePipelineOutput
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[[autodoc]] pipelines.qwenimage.pipeline_output.QwenImagePipelineOutput

‎docs/source/en/using-diffusers/callback.md‎

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‎docs/source/en/using-diffusers/custom_pipeline_overview.md‎

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‎src/diffusers/__init__.py‎

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"OmniGenTransformer2DModel",
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"PixArtTransformer2DModel",
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"PriorTransformer",
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"QwenImageControlNetModel",
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"QwenImageMultiControlNetModel",
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"QwenImageTransformer2DModel",
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"SanaControlNetModel",
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"SanaTransformer2DModel",
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"PixArtAlphaPipeline",
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"PixArtSigmaPAGPipeline",
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"PixArtSigmaPipeline",
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"QwenImageControlNetPipeline",
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"QwenImageEditPipeline",
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"QwenImageImg2ImgPipeline",
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"QwenImageInpaintPipeline",
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OmniGenTransformer2DModel,
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PixArtTransformer2DModel,
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PriorTransformer,
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QwenImageControlNetModel,
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QwenImageMultiControlNetModel,
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QwenImageTransformer2DModel,
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SanaControlNetModel,
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SanaTransformer2DModel,
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PixArtAlphaPipeline,
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PixArtSigmaPAGPipeline,
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PixArtSigmaPipeline,
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QwenImageControlNetPipeline,
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QwenImageEditPipeline,
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QwenImageImg2ImgPipeline,
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QwenImageInpaintPipeline,

‎src/diffusers/guiders/adaptive_projected_guidance.py‎

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import torch
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from ..configuration_utils import register_to_config
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from .guider_utils import BaseGuidance, rescale_noise_cfg
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from .guider_utils import BaseGuidance, GuiderOutput, rescale_noise_cfg
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data_batches.append(data_batch)
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return data_batches
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> torch.Tensor:
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> GuiderOutput:
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pred = None
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if not self._is_apg_enabled():
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if self.guidance_rescale > 0.0:
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pred = rescale_noise_cfg(pred, pred_cond, self.guidance_rescale)
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return pred, {}
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return GuiderOutput(pred=pred, pred_cond=pred_cond, pred_uncond=pred_uncond)
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@property
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def is_conditional(self) -> bool:

‎src/diffusers/guiders/auto_guidance.py‎

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from ..configuration_utils import register_to_config
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from ..hooks import HookRegistry, LayerSkipConfig
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from ..hooks.layer_skip import _apply_layer_skip_hook
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from .guider_utils import BaseGuidance, rescale_noise_cfg
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from .guider_utils import BaseGuidance, GuiderOutput, rescale_noise_cfg
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> torch.Tensor:
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> GuiderOutput:
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pred = None
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pred = rescale_noise_cfg(pred, pred_cond, self.guidance_rescale)
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return pred, {}
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return GuiderOutput(pred=pred, pred_cond=pred_cond, pred_uncond=pred_uncond)
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def is_conditional(self) -> bool:

‎src/diffusers/guiders/classifier_free_guidance.py‎

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import torch
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from ..configuration_utils import register_to_config
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from .guider_utils import BaseGuidance, rescale_noise_cfg
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from .guider_utils import BaseGuidance, GuiderOutput, rescale_noise_cfg
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> torch.Tensor:
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> GuiderOutput:
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return pred, {}
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return GuiderOutput(pred=pred, pred_cond=pred_cond, pred_uncond=pred_uncond)
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def is_conditional(self) -> bool:

‎src/diffusers/guiders/classifier_free_zero_star_guidance.py‎

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import torch
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from ..configuration_utils import register_to_config
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from .guider_utils import BaseGuidance, rescale_noise_cfg
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from .guider_utils import BaseGuidance, GuiderOutput, rescale_noise_cfg
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def forward(self, pred_cond: torch.Tensor, pred_uncond: Optional[torch.Tensor] = None) -> GuiderOutput:
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return GuiderOutput(pred=pred, pred_cond=pred_cond, pred_uncond=pred_uncond)
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def is_conditional(self) -> bool:

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