[ldm3d] documentation fixing typos (#4284)

* fixed typo

* updated doc to be consistent in naming

* make style/quality

* preprocessing for 4 channels and not 6

* make style

* test for 4c

* make style/quality

* fixed test on cpu

* fixed doc typo

* changed default ckpt to 4c

* Update pipeline_stable_diffusion_ldm3d.py

---------
Co-authored-by: Aflalo <estellea@isl-iam1.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu33.rr.intel.com>
Co-authored-by: Aflalo <estellea@isl-gpu38.rr.intel.com>

docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.md

@@ -30,8 +30,8 @@ Make sure to check out the Stable Diffusion [Tips](overview#tips) section to lea
 	- all
 	- __call__
 
-## StableDiffusionPipelineOutput
+## LDM3DPipelineOutput
 
-[[autodoc]] pipelines.stable_diffusion.StableDiffusionPipelineOutput
+[[autodoc]] pipelines.stable_diffusion.pipeline_stable_diffusion_ldm3d.LDM3DPipelineOutput
 	- all
 	- __call__

src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py

@@ -41,11 +41,10 @@ logger = logging.get_logger(__name__)  # pylint: disable=invalid-name
 
 EXAMPLE_DOC_STRING = """
     Examples:
-        ```py
-        >>> import torch
-        >>> from diffusers import StableDiffusionPipeline
+        ```python
+        >>> from diffusers import StableDiffusionLDM3DPipeline
 
-        >>> pipe = StableDiffusionLDM3DPipeline.from_pretrained("Intel/ldm3d")
+        >>> pipe = StableDiffusionLDM3DPipeline.from_pretrained("Intel/ldm3d-4c")
         >>> pipe = pipe.to("cuda")
 
         >>> prompt = "a photo of an astronaut riding a horse on mars"
@@ -63,7 +62,10 @@ class LDM3DPipelineOutput(BaseOutput):
     Output class for Stable Diffusion pipelines.
 
     Args:
-        images (`List[PIL.Image.Image]` or `np.ndarray`)
+        rgb (`List[PIL.Image.Image]` or `np.ndarray`)
+            List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width,
+            num_channels)`.
+        depth (`List[PIL.Image.Image]` or `np.ndarray`)
             List of denoised PIL images of length `batch_size` or NumPy array of shape `(batch_size, height, width,
             num_channels)`.
         nsfw_content_detected (`List[bool]`)