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Add a docstring for the AutoencoderKL's encode #5239

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merged 3 commits into from
Oct 2, 2023
Merged

Add a docstring for the AutoencoderKL's encode #5239

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fdad302
Add docstring for the AutoencoderKL's encode
Sep 29, 2023
8f2fc80
Support Python 3.8 syntax in AutoencoderKL.decode type hints
freespirit Oct 2, 2023
6d3265b
Follow the style guidelines in AutoencoderKL's encode
Oct 2, 2023
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16 changes: 15 additions & 1 deletion src/diffusers/models/autoencoder_kl.py
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Original file line number Diff line number Diff line change
Expand Up @@ -249,7 +249,21 @@ def set_default_attn_processor(self):
self.set_attn_processor(processor, _remove_lora=True)

@apply_forward_hook
def encode(self, x: torch.FloatTensor, return_dict: bool = True) -> AutoencoderKLOutput:
def encode(
self, x: torch.FloatTensor, return_dict: bool = True
) -> Union[AutoencoderKLOutput, Tuple[DiagonalGaussianDistribution]]:
"""
Encode a batch of images into latents.

Args:
x (`torch.FloatTensor`): Input batch of images.
return_dict (`bool`, *optional*, defaults to `True`):
Whether to return a [`~models.autoencoder_kl.AutoencoderKLOutput`] instead of a plain tuple.

Returns:
The latent representations of the encoded images. If `return_dict` is True, a
[`~models.autoencoder_kl.AutoencoderKLOutput`] is returned, otherwise a plain `tuple` is returned.
"""
if self.use_tiling and (x.shape[-1] > self.tile_sample_min_size or x.shape[-2] > self.tile_sample_min_size):
return self.tiled_encode(x, return_dict=return_dict)

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