Fix typo: 'will ge generated' -> 'will be generated' (#12231)

examples/community/stable_diffusion_controlnet_img2img.py

@@ -670,7 +670,7 @@ class StableDiffusionControlNetImg2ImgPipeline(DiffusionPipeline, StableDiffusio
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_controlnet_inpaint.py

@@ -810,7 +810,7 @@ class StableDiffusionControlNetInpaintPipeline(DiffusionPipeline, StableDiffusio
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_controlnet_inpaint_img2img.py

@@ -804,7 +804,7 @@ class StableDiffusionControlNetInpaintImg2ImgPipeline(DiffusionPipeline, StableD
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_controlnet_reference.py

@@ -179,7 +179,7 @@ class StableDiffusionControlNetReferencePipeline(StableDiffusionControlNetPipeli
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_ipex.py

@@ -615,7 +615,7 @@ class StableDiffusionIPEXPipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_reference.py

@@ -885,7 +885,7 @@ class StableDiffusionReferencePipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_repaint.py

@@ -678,7 +678,7 @@ class StableDiffusionRepaintPipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/stable_diffusion_xl_reference.py

@@ -380,7 +380,7 @@ class StableDiffusionXLReferencePipeline(StableDiffusionXLPipeline):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/community/text_inpainting.py

@@ -180,7 +180,7 @@ class TextInpainting(DiffusionPipeline, StableDiffusionMixin):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             output_type (`str`, *optional*, defaults to `"pil"`):
                 The output format of the generate image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.

examples/community/tiled_upscaling.py

@@ -231,7 +231,7 @@ class StableDiffusionTiledUpscalePipeline(StableDiffusionUpscalePipeline):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             tile_size (`int`, *optional*):
                 The size of the tiles. Too big can result in an OOM-error.
             tile_border (`int`, *optional*):

examples/community/wildcard_stable_diffusion.py

@@ -209,7 +209,7 @@ class WildcardStableDiffusionPipeline(DiffusionPipeline, StableDiffusionMixin):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             output_type (`str`, *optional*, defaults to `"pil"`):
                 The output format of the generate image. Choose between
                 [PIL](https://pillow.readthedocs.io/en/stable/): `PIL.Image.Image` or `np.array`.

examples/research_projects/pixart/pipeline_pixart_alpha_controlnet.py

@@ -860,7 +860,7 @@ class PixArtAlphaControlnetPipeline(DiffusionPipeline):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

examples/research_projects/rdm/pipeline_rdm.py

@@ -202,7 +202,7 @@ class RDMPipeline(DiffusionPipeline, StableDiffusionMixin):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/allegro/pipeline_allegro.py

@@ -760,7 +760,7 @@ class AllegroPipeline(DiffusionPipeline):
             latents (`torch.Tensor`, *optional*):
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for video
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/animatediff/pipeline_animatediff_sdxl.py

@@ -971,7 +971,7 @@ class AnimateDiffSDXLPipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for video
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/aura_flow/pipeline_aura_flow.py

@@ -497,7 +497,7 @@ class AuraFlowPipeline(DiffusionPipeline, AuraFlowLoraLoaderMixin):
             latents (`torch.FloatTensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.FloatTensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/blip_diffusion/pipeline_blip_diffusion.py

@@ -228,7 +228,7 @@ class BlipDiffusionPipeline(DeprecatedPipelineMixin, DiffusionPipeline):
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by random sampling.
+                tensor will be generated by random sampling.
             guidance_scale (`float`, *optional*, defaults to 7.5):
                 Guidance scale as defined in [Classifier-Free Diffusion
                 Guidance](https://huggingface.co/papers/2207.12598). `guidance_scale` is defined as `w` of equation 2.

src/diffusers/pipelines/bria/pipeline_bria.py

@@ -506,7 +506,7 @@ class BriaPipeline(DiffusionPipeline):
             latents (`torch.FloatTensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.FloatTensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/chroma/pipeline_chroma.py

@@ -676,7 +676,7 @@ class ChromaPipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.

src/diffusers/pipelines/chroma/pipeline_chroma_img2img.py

@@ -744,7 +744,7 @@ class ChromaImg2ImgPipeline(
             latents (`torch.Tensor`, *optional*):
                 Pre-generated noisy latents, sampled from a Gaussian distribution, to be used as inputs for image
                 generation. Can be used to tweak the same generation with different prompts. If not provided, a latents
-                tensor will ge generated by sampling using the supplied random `generator`.
+                tensor will be generated by sampling using the supplied random `generator`.
             prompt_embeds (`torch.Tensor`, *optional*):
                 Pre-generated text embeddings. Can be used to easily tweak text inputs, *e.g.* prompt weighting. If not
                 provided, text embeddings will be generated from `prompt` input argument.