[`Docs`] Fix typos (#7451)

* Fix typos

* Fix typos

* Fix typos

---------
Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>

examples/community/pipeline_stable_diffusion_xl_controlnet_adapter_inpaint.py

@@ -1073,7 +1073,7 @@ class StableDiffusionXLControlNetAdapterInpaintPipeline(
                 # because `num_inference_steps` might be even given that every timestep
                 # (except the highest one) is duplicated. If `num_inference_steps` is even it would
                 # mean that we cut the timesteps in the middle of the denoising step
-                # (between 1st and 2nd devirative) which leads to incorrect results. By adding 1
+                # (between 1st and 2nd derivative) which leads to incorrect results. By adding 1
                 # we ensure that the denoising process always ends after the 2nd derivate step of the scheduler
                 num_inference_steps = num_inference_steps + 1
 

examples/community/pipeline_stable_diffusion_xl_instantid.py

@@ -701,7 +701,7 @@ class StableDiffusionXLInstantIDPipeline(StableDiffusionXLControlNetPipeline):
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

examples/research_projects/promptdiffusion/pipeline_prompt_diffusion.py

@@ -1005,7 +1005,7 @@ class PromptDiffusionPipeline(DiffusionPipeline, TextualInversionLoaderMixin, Lo
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/animatediff/pipeline_animatediff.py

@@ -663,7 +663,7 @@ class AnimateDiffPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/animatediff/pipeline_animatediff_video2video.py

@@ -823,7 +823,7 @@ class AnimateDiffVideoToVideoPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet.py

@@ -1002,7 +1002,7 @@ class StableDiffusionControlNetPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet_img2img.py

@@ -1012,7 +1012,7 @@ class StableDiffusionControlNetImg2ImgPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint.py

@@ -1241,7 +1241,7 @@ class StableDiffusionControlNetInpaintPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet_inpaint_sd_xl.py

@@ -1022,7 +1022,7 @@ class StableDiffusionXLControlNetInpaintPipeline(
                 # because `num_inference_steps` might be even given that every timestep
                 # (except the highest one) is duplicated. If `num_inference_steps` is even it would
                 # mean that we cut the timesteps in the middle of the denoising step
-                # (between 1st and 2nd devirative) which leads to incorrect results. By adding 1
+                # (between 1st and 2nd derivative) which leads to incorrect results. By adding 1
                 # we ensure that the denoising process always ends after the 2nd derivate step of the scheduler
                 num_inference_steps = num_inference_steps + 1
 
@@ -1313,7 +1313,7 @@ class StableDiffusionXLControlNetInpaintPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl.py

@@ -1102,7 +1102,7 @@ class StableDiffusionXLControlNetPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/controlnet/pipeline_controlnet_sd_xl_img2img.py

@@ -1251,7 +1251,7 @@ class StableDiffusionXLControlNetImg2ImgPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/pia/pipeline_pia.py

@@ -789,7 +789,7 @@ class PIAPipeline(
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/stable_cascade/pipeline_stable_cascade_combined.py

@@ -242,7 +242,7 @@ class StableCascadeCombinedPipeline(DiffusionPipeline):
             prior_callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `prior_callback_on_step_end` function. The tensors specified in the
                 list will be passed as `callback_kwargs` argument. You will only be able to include variables listed in
-                the `._callback_tensor_inputs` attribute of your pipeine class.
+                the `._callback_tensor_inputs` attribute of your pipeline class.
             callback_on_step_end (`Callable`, *optional*):
                 A function that calls at the end of each denoising steps during the inference. The function is called
                 with the following arguments: `callback_on_step_end(self: DiffusionPipeline, step: int, timestep: int,
@@ -251,7 +251,7 @@ class StableCascadeCombinedPipeline(DiffusionPipeline):
             callback_on_step_end_tensor_inputs (`List`, *optional*):
                 The list of tensor inputs for the `callback_on_step_end` function. The tensors specified in the list
                 will be passed as `callback_kwargs` argument. You will only be able to include variables listed in the
-                `._callback_tensor_inputs` attribute of your pipeine class.
+                `._callback_tensor_inputs` attribute of your pipeline class.
 
         Examples:
 

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_img2img.py

@@ -647,7 +647,7 @@ class StableDiffusionXLImg2ImgPipeline(
                 # because `num_inference_steps` might be even given that every timestep
                 # (except the highest one) is duplicated. If `num_inference_steps` is even it would
                 # mean that we cut the timesteps in the middle of the denoising step
-                # (between 1st and 2nd devirative) which leads to incorrect results. By adding 1
+                # (between 1st and 2nd derivative) which leads to incorrect results. By adding 1
                 # we ensure that the denoising process always ends after the 2nd derivate step of the scheduler
                 num_inference_steps = num_inference_steps + 1
 

src/diffusers/pipelines/stable_diffusion_xl/pipeline_stable_diffusion_xl_inpaint.py

@@ -1027,7 +1027,7 @@ class StableDiffusionXLInpaintPipeline(
                 # because `num_inference_steps` might be even given that every timestep
                 # (except the highest one) is duplicated. If `num_inference_steps` is even it would
                 # mean that we cut the timesteps in the middle of the denoising step
-                # (between 1st and 2nd devirative) which leads to incorrect results. By adding 1
+                # (between 1st and 2nd derivative) which leads to incorrect results. By adding 1
                 # we ensure that the denoising process always ends after the 2nd derivate step of the scheduler
                 num_inference_steps = num_inference_steps + 1
 

tests/models/autoencoders/test_models_vae.py

@@ -392,7 +392,7 @@ class ConsistencyDecoderVAETests(ModelTesterMixin, unittest.TestCase):
         ...
 
 
-class AutoncoderKLTemporalDecoderFastTests(ModelTesterMixin, unittest.TestCase):
+class AutoencoderKLTemporalDecoderFastTests(ModelTesterMixin, unittest.TestCase):
     model_class = AutoencoderKLTemporalDecoder
     main_input_name = "sample"
     base_precision = 1e-2

tests/pipelines/test_pipelines.py

@@ -914,7 +914,7 @@ class CustomPipelineTests(unittest.TestCase):
         with self.assertRaises(ValueError):
             pipeline = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sdxl-custom-components")
 
-        # Check that only loading custom componets "my_unet", "my_scheduler" works
+        # Check that only loading custom components "my_unet", "my_scheduler" works
         pipeline = DiffusionPipeline.from_pretrained(
             "hf-internal-testing/tiny-sdxl-custom-components", trust_remote_code=True
         )
@@ -928,7 +928,7 @@ class CustomPipelineTests(unittest.TestCase):
 
         assert images.shape == (1, 64, 64, 3)
 
-        # Check that only loading custom componets "my_unet", "my_scheduler" and explicit custom pipeline works
+        # Check that only loading custom components "my_unet", "my_scheduler" and explicit custom pipeline works
         pipeline = DiffusionPipeline.from_pretrained(
             "hf-internal-testing/tiny-sdxl-custom-components", custom_pipeline="my_pipeline", trust_remote_code=True
         )
@@ -947,7 +947,7 @@ class CustomPipelineTests(unittest.TestCase):
         with self.assertRaises(ValueError):
             pipeline = DiffusionPipeline.from_pretrained("hf-internal-testing/tiny-sdxl-custom-all")
 
-        # Check that only loading custom componets "my_unet", "my_scheduler" and auto custom pipeline works
+        # Check that only loading custom components "my_unet", "my_scheduler" and auto custom pipeline works
         pipeline = DiffusionPipeline.from_pretrained(
             "hf-internal-testing/tiny-sdxl-custom-all", trust_remote_code=True
         )

tests/pipelines/test_pipelines_common.py

@@ -634,7 +634,7 @@ class PipelineTesterMixin:
             "treatment when `do_classifier_free_guidance` is `True`. `pipeline_params.py` provides some common"
             " sets of parameters such as `TEXT_TO_IMAGE_CALLBACK_CFG_PARAMS`. If your pipeline's "
             "set of cfg arguments has minor changes from one of the common sets of cfg arguments, "
-            "do not make modifications to the existing common sets of cfg arguments. I.e. for inpaint pipeine, you "
+            "do not make modifications to the existing common sets of cfg arguments. I.e. for inpaint pipeline, you "
             " need to adjust batch size of `mask` and `masked_image_latents` so should set the attribute as"
             "`callback_cfg_params = TEXT_TO_IMAGE_CFG_PARAMS.union({'mask', 'masked_image_latents'})`"
         )
@@ -1235,7 +1235,7 @@ class PipelineTesterMixin:
         )
 
         def callback_inputs_subset(pipe, i, t, callback_kwargs):
-            # interate over callback args
+            # iterate over callback args
             for tensor_name, tensor_value in callback_kwargs.items():
                 # check that we're only passing in allowed tensor inputs
                 assert tensor_name in pipe._callback_tensor_inputs
@@ -1246,7 +1246,7 @@ class PipelineTesterMixin:
             for tensor_name in pipe._callback_tensor_inputs:
                 assert tensor_name in callback_kwargs
 
-            # interate over callback args
+            # iterate over callback args
             for tensor_name, tensor_value in callback_kwargs.items():
                 # check that we're only passing in allowed tensor inputs
                 assert tensor_name in pipe._callback_tensor_inputs