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Fix misc typos (#4479)

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Fix typos
This commit is contained in:
George He
2023-08-07 20:21:19 -04:00
committed by GitHub
parent aef11cbf66
commit f0725c5845
7 changed files with 9 additions and 9 deletions
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2
src/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py
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@@ -797,7 +797,7 @@ class StableDiffusionControlNetImg2ImgPipeline(
instead.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, `List[np.ndarray]`,:
`List[List[torch.FloatTensor]]`, `List[List[np.ndarray]]` or `List[List[PIL.Image.Image]]`):
The initial image will be used as the starting point for the image generation process. Can also accpet
The initial image will be used as the starting point for the image generation process. Can also accept
image latents as `image`, if passing latents directly, it will not be encoded again.
control_image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, `List[np.ndarray]`,:
`List[List[torch.FloatTensor]]`, `List[List[np.ndarray]]` or `List[List[PIL.Image.Image]]`):

4
src/diffusers/pipelines/kandinsky/pipeline_kandinsky_combined.py
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@@ -474,7 +474,7 @@ class KandinskyImg2ImgCombinedPipeline(DiffusionPipeline):
The prompt or prompts to guide the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
negative_prompt (`str` or `List[str]`, *optional*):
The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored
@@ -720,7 +720,7 @@ class KandinskyInpaintCombinedPipeline(DiffusionPipeline):
The prompt or prompts to guide the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
mask_image (`np.array`):
Tensor representing an image batch, to mask `image`. White pixels in the mask will be repainted, while

4
src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_combined.py
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@@ -455,7 +455,7 @@ class KandinskyV22Img2ImgCombinedPipeline(DiffusionPipeline):
The prompt or prompts to guide the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
negative_prompt (`str` or `List[str]`, *optional*):
The prompt or prompts not to guide the image generation. Ignored when not using guidance (i.e., ignored
@@ -692,7 +692,7 @@ class KandinskyV22InpaintCombinedPipeline(DiffusionPipeline):
The prompt or prompts to guide the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
mask_image (`np.array`):
Tensor representing an image batch, to mask `image`. White pixels in the mask will be repainted, while

2
src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_controlnet_img2img.py
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@@ -258,7 +258,7 @@ class KandinskyV22ControlnetImg2ImgPipeline(DiffusionPipeline):
The clip image embeddings for text prompt, that will be used to condition the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
strength (`float`, *optional*, defaults to 0.8):
Conceptually, indicates how much to transform the reference `image`. Must be between 0 and 1. `image`

2
src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_img2img.py
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@@ -230,7 +230,7 @@ class KandinskyV22Img2ImgPipeline(DiffusionPipeline):
The clip image embeddings for text prompt, that will be used to condition the image generation.
image (`torch.FloatTensor`, `PIL.Image.Image`, `np.ndarray`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch, that will be used as the starting point for the
process. Can also accpet image latents as `image`, if passing latents directly, it will not be encoded
process. Can also accept image latents as `image`, if passing latents directly, it will not be encoded
again.
strength (`float`, *optional*, defaults to 0.8):
Conceptually, indicates how much to transform the reference `image`. Must be between 0 and 1. `image`

2
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_pix2pix_zero.py
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@@ -1095,7 +1095,7 @@ class StableDiffusionPix2PixZeroPipeline(DiffusionPipeline):
The prompt or prompts to guide the image generation. If not defined, one has to pass `prompt_embeds`.
instead.
image (`torch.FloatTensor` `np.ndarray`, `PIL.Image.Image`, `List[torch.FloatTensor]`, `List[PIL.Image.Image]`, or `List[np.ndarray]`):
`Image`, or tensor representing an image batch which will be used for conditioning. Can also accpet
`Image`, or tensor representing an image batch which will be used for conditioning. Can also accept
image latents as `image`, if passing latents directly, it will not be encoded again.
num_inference_steps (`int`, *optional*, defaults to 50):
The number of denoising steps. More denoising steps usually lead to a higher quality image at the

2
src/diffusers/pipelines/text_to_video_synthesis/pipeline_text_to_video_synth_img2img.py
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@@ -561,7 +561,7 @@ class VideoToVideoSDPipeline(DiffusionPipeline, TextualInversionLoaderMixin, Lor
The prompt or prompts to guide image generation. If not defined, you need to pass `prompt_embeds`.
video (`List[np.ndarray]` or `torch.FloatTensor`):
`video` frames or tensor representing a video batch to be used as the starting point for the process.
Can also accpet video latents as `image`, if passing latents directly, it will not be encoded again.
Can also accept video latents as `image`, if passing latents directly, it will not be encoded again.
strength (`float`, *optional*, defaults to 0.8):
Indicates extent to transform the reference `video`. Must be between 0 and 1. `video` is used as a
starting point, adding more noise to it the larger the `strength`. The number of denoising steps