remove latent input for kandinsky prior_emb2emb pipeline (#4887)

* remove latent input

* fix test

---------

Co-authored-by: yiyixuxu <yixu310@gmail,com>

src/diffusers/pipelines/kandinsky2_2/pipeline_kandinsky2_2_prior_emb2emb.py

@@ -434,7 +434,6 @@ class KandinskyV22PriorEmb2EmbPipeline(DiffusionPipeline):
         num_images_per_prompt: int = 1,
         num_inference_steps: int = 25,
         generator: Optional[Union[torch.Generator, List[torch.Generator]]] = None,
-        latents: Optional[torch.FloatTensor] = None,
         guidance_scale: float = 4.0,
         output_type: Optional[str] = "pt",  # pt only
         return_dict: bool = True,
@@ -462,10 +461,6 @@ class KandinskyV22PriorEmb2EmbPipeline(DiffusionPipeline):
             generator (`torch.Generator` or `List[torch.Generator]`, *optional*):
                 One or a list of [torch generator(s)](https://pytorch.org/docs/stable/generated/torch.Generator.html)
                 to make generation deterministic.
-            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`.
             guidance_scale (`float`, *optional*, defaults to 4.0):
                 Guidance scale as defined in [Classifier-Free Diffusion Guidance](https://arxiv.org/abs/2207.12598).
                 `guidance_scale` is defined as `w` of equation 2. of [Imagen

tests/pipelines/kandinsky_v22/test_kandinsky_prior_emb2emb.py

@@ -48,7 +48,6 @@ class KandinskyV22PriorEmb2EmbPipelineFastTests(PipelineTesterMixin, unittest.Te
         "strength",
         "generator",
         "num_inference_steps",
-        "latents",
         "negative_prompt",
         "guidance_scale",
         "output_type",