diff --git a/src/diffusers/models/unets/unet_spatio_temporal_condition.py b/src/diffusers/models/unets/unet_spatio_temporal_condition.py index d38be0b0675f..7d6b861df82b 100644 --- a/src/diffusers/models/unets/unet_spatio_temporal_condition.py +++ b/src/diffusers/models/unets/unet_spatio_temporal_condition.py @@ -50,7 +50,7 @@ class UNetSpatioTemporalConditionModel(ModelMixin, AttentionMixin, ConfigMixin, block_out_channels (`tuple[int]`, *optional*, defaults to `(320, 640, 1280, 1280)`): The tuple of output channels for each block. addition_time_embed_dim: (`int`, defaults to 256): - Dimension to to encode the additional time ids. + Dimension to encode the additional time ids. projection_class_embeddings_input_dim (`int`, defaults to 768): The dimension of the projection of encoded `added_time_ids`. layers_per_block (`int`, *optional*, defaults to 2): The number of layers per block. diff --git a/src/diffusers/modular_pipelines/anima/before_denoise.py b/src/diffusers/modular_pipelines/anima/before_denoise.py index dbfe82d7f35d..1015781ee7d8 100644 --- a/src/diffusers/modular_pipelines/anima/before_denoise.py +++ b/src/diffusers/modular_pipelines/anima/before_denoise.py @@ -109,7 +109,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_images_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_images_per_prompt diff --git a/src/diffusers/modular_pipelines/flux/before_denoise.py b/src/diffusers/modular_pipelines/flux/before_denoise.py index 2d41cd76cd93..243f9e927d74 100644 --- a/src/diffusers/modular_pipelines/flux/before_denoise.py +++ b/src/diffusers/modular_pipelines/flux/before_denoise.py @@ -470,7 +470,7 @@ def intermediate_outputs(self) -> list[OutputParam]: def check_inputs(image_latents, latents): if image_latents.shape[0] != latents.shape[0]: raise ValueError( - f"`image_latents` must have have same batch size as `latents`, but got {image_latents.shape[0]} and {latents.shape[0]}" + f"`image_latents` must have same batch size as `latents`, but got {image_latents.shape[0]} and {latents.shape[0]}" ) if image_latents.ndim != 3: diff --git a/src/diffusers/modular_pipelines/helios/before_denoise.py b/src/diffusers/modular_pipelines/helios/before_denoise.py index 64407db63cca..fbe9a7f30cc6 100644 --- a/src/diffusers/modular_pipelines/helios/before_denoise.py +++ b/src/diffusers/modular_pipelines/helios/before_denoise.py @@ -168,7 +168,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_videos_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_videos_per_prompt diff --git a/src/diffusers/modular_pipelines/qwenimage/before_denoise.py b/src/diffusers/modular_pipelines/qwenimage/before_denoise.py index 51b5c6ac8c3d..b928bf7fce9e 100644 --- a/src/diffusers/modular_pipelines/qwenimage/before_denoise.py +++ b/src/diffusers/modular_pipelines/qwenimage/before_denoise.py @@ -426,7 +426,7 @@ def intermediate_outputs(self) -> list[OutputParam]: def check_inputs(image_latents, latents): if image_latents.shape[0] != latents.shape[0]: raise ValueError( - f"`image_latents` must have have same batch size as `latents`, but got {image_latents.shape[0]} and {latents.shape[0]}" + f"`image_latents` must have same batch size as `latents`, but got {image_latents.shape[0]} and {latents.shape[0]}" ) if image_latents.ndim != 3: diff --git a/src/diffusers/modular_pipelines/qwenimage/inputs.py b/src/diffusers/modular_pipelines/qwenimage/inputs.py index faec7db245df..e82d6ad7a245 100644 --- a/src/diffusers/modular_pipelines/qwenimage/inputs.py +++ b/src/diffusers/modular_pipelines/qwenimage/inputs.py @@ -68,7 +68,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_images_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_images_per_prompt diff --git a/src/diffusers/modular_pipelines/stable_diffusion_3/inputs.py b/src/diffusers/modular_pipelines/stable_diffusion_3/inputs.py index 401ff2db5c61..af892bf4c12c 100644 --- a/src/diffusers/modular_pipelines/stable_diffusion_3/inputs.py +++ b/src/diffusers/modular_pipelines/stable_diffusion_3/inputs.py @@ -71,7 +71,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_images_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_images_per_prompt diff --git a/src/diffusers/modular_pipelines/wan/before_denoise.py b/src/diffusers/modular_pipelines/wan/before_denoise.py index 6b0874037b0d..1e14f1efcd83 100644 --- a/src/diffusers/modular_pipelines/wan/before_denoise.py +++ b/src/diffusers/modular_pipelines/wan/before_denoise.py @@ -81,7 +81,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_videos_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_videos_per_prompt diff --git a/src/diffusers/modular_pipelines/z_image/before_denoise.py b/src/diffusers/modular_pipelines/z_image/before_denoise.py index 9b6c1976a1bf..60cf3af84c8a 100644 --- a/src/diffusers/modular_pipelines/z_image/before_denoise.py +++ b/src/diffusers/modular_pipelines/z_image/before_denoise.py @@ -81,7 +81,7 @@ def repeat_tensor_to_batch_size( repeat_by = num_images_per_prompt else: raise ValueError( - f"`{input_name}` must have have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" + f"`{input_name}` must have batch size 1 or {batch_size}, but got {input_tensor.shape[0]}" ) # expand the tensor to match the batch_size * num_images_per_prompt diff --git a/src/diffusers/pipelines/flux/pipeline_flux_kontext_inpaint.py b/src/diffusers/pipelines/flux/pipeline_flux_kontext_inpaint.py index 9a79aafd8760..a77c60e6dbc5 100644 --- a/src/diffusers/pipelines/flux/pipeline_flux_kontext_inpaint.py +++ b/src/diffusers/pipelines/flux/pipeline_flux_kontext_inpaint.py @@ -923,7 +923,7 @@ def __call__( Args: image (`torch.Tensor`, `PIL.Image.Image`, `np.ndarray`, `list[torch.Tensor]`, `list[PIL.Image.Image]`, or `list[np.ndarray]`): - `Image`, numpy array or tensor representing an image batch to be be inpainted (which parts of the image + `Image`, numpy array or tensor representing an image batch to be inpainted (which parts of the image to be masked out with `mask_image` and repainted according to `prompt` and `image_reference`). For both numpy array and pytorch tensor, the expected value range is between `[0, 1]` If it's a tensor or a list or tensors, the expected shape should be `(B, C, H, W)` or `(C, H, W)`. If it is a numpy array or a diff --git a/src/diffusers/pipelines/ltx2/pipeline_ltx2_condition.py b/src/diffusers/pipelines/ltx2/pipeline_ltx2_condition.py index ecc89ae79a30..79aa527d856a 100644 --- a/src/diffusers/pipelines/ltx2/pipeline_ltx2_condition.py +++ b/src/diffusers/pipelines/ltx2/pipeline_ltx2_condition.py @@ -235,7 +235,7 @@ def rescale_noise_cfg(noise_cfg, noise_pred_text, guidance_rescale=0.0): class LTX2ConditionPipeline(DiffusionPipeline, FromSingleFileMixin, LTX2LoraLoaderMixin): r""" - Pipeline for video generation which allows image conditions to be inserted at arbitary parts of the video. + Pipeline for video generation which allows image conditions to be inserted at arbitrary parts of the video. Reference: https://github.com/Lightricks/LTX-Video