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[ldm3d] documentation fixing typos (#4284)

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* 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>
This commit is contained in:
estelleafl
2023-08-01 19:03:29 +03:00
committed by GitHub
parent c69526a3d5
commit 05a1cb902c
2 changed files with 9 additions and 7 deletions
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4
docs/source/en/api/pipelines/stable_diffusion/ldm3d_diffusion.md
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@@ -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__

12
src/diffusers/pipelines/stable_diffusion/pipeline_stable_diffusion_ldm3d.py
View File

@@ -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]`)