Fix a typo: bfloa16 -> bfloat16 (#2243)

examples/community/composable_stable_diffusion.py

@@ -340,7 +340,7 @@ class ComposableStableDiffusionPipeline(DiffusionPipeline):
         latents = 1 / 0.18215 * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

examples/community/imagic_stable_diffusion.py

@@ -479,7 +479,7 @@ class ImagicStableDiffusionPipeline(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if self.safety_checker is not None:

examples/community/interpolate_stable_diffusion.py

@@ -379,7 +379,7 @@ class StableDiffusionWalkPipeline(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if self.safety_checker is not None:

examples/community/lpw_stable_diffusion.py

@@ -600,7 +600,7 @@ class StableDiffusionLongPromptWeightingPipeline(StableDiffusionPipeline):
         latents = 1 / 0.18215 * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

examples/community/multilingual_stable_diffusion.py

@@ -414,7 +414,7 @@ class MultilingualStableDiffusion(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if self.safety_checker is not None:

examples/community/sd_text2img_k_diffusion.py

@@ -300,7 +300,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
         latents = 1 / 0.18215 * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

examples/community/seed_resize_stable_diffusion.py

@@ -344,7 +344,7 @@ class SeedResizeStableDiffusionPipeline(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if self.safety_checker is not None:

examples/community/speech_to_image_diffusion.py

@@ -249,7 +249,7 @@ class SpeechToImagePipeline(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if output_type == "pil":

examples/community/wildcard_stable_diffusion.py

@@ -396,7 +396,7 @@ class WildcardStableDiffusionPipeline(DiffusionPipeline):
 
         image = (image / 2 + 0.5).clamp(0, 1)
 
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
 
         if self.safety_checker is not None:

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion.py

@@ -372,7 +372,7 @@ class AltDiffusionPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/alt_diffusion/pipeline_alt_diffusion_img2img.py

@@ -394,7 +394,7 @@ class AltDiffusionImg2ImgPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/paint_by_example/pipeline_paint_by_example.py

@@ -260,7 +260,7 @@ class PaintByExamplePipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_cycle_diffusion.py

@@ -477,7 +477,7 @@ class CycleDiffusionPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion.py

@@ -369,7 +369,7 @@ class StableDiffusionPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_depth2img.py

@@ -313,7 +313,7 @@ class StableDiffusionDepth2ImgPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_image_variation.py

@@ -198,7 +198,7 @@ class StableDiffusionImageVariationPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_img2img.py

@@ -403,7 +403,7 @@ class StableDiffusionImg2ImgPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint.py

@@ -469,7 +469,7 @@ class StableDiffusionInpaintPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_inpaint_legacy.py

@@ -388,7 +388,7 @@ class StableDiffusionInpaintPipelineLegacy(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image
 

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_instruct_pix2pix.py

@@ -591,7 +591,7 @@ class StableDiffusionInstructPix2PixPipeline(DiffusionPipeline):
         latents = 1 / self.vae.config.scaling_factor * latents
         image = self.vae.decode(latents).sample
         image = (image / 2 + 0.5).clamp(0, 1)
-        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloa16
+        # we always cast to float32 as this does not cause significant overhead and is compatible with bfloat16
         image = image.cpu().permute(0, 2, 3, 1).float().numpy()
         return image