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Remove Redundant Variables from Encoder and Decoder (#5569)

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* I added a new doc string to the class. This is more flexible to understanding other developers what are doing and where it's using.

* Update src/diffusers/models/unet_2d_blocks.py

This changes suggest by maintener.

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

* Update src/diffusers/models/unet_2d_blocks.py

Add suggested text

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

* Update unet_2d_blocks.py

I changed the Parameter to Args text.

* Update unet_2d_blocks.py

proper indentation set in this file.

* Update unet_2d_blocks.py

a little bit of change in the act_fun argument line.

* I run the black command to reformat style in the code

* Update unet_2d_blocks.py

similar doc-string add to have in the original diffusion repository.

* I removed the dummy variable defined in both the encoder and decoder.

* Now, I run black package to reformat my file

---------

Co-authored-by: Sayak Paul <spsayakpaul@gmail.com>
Co-authored-by: Dhruv Nair <dhruv.nair@gmail.com>
This commit is contained in:
Chi
2023-11-02 02:20:33 +05:30
committed by GitHub
parent 839c2a5ece
commit 29cf163b95
1 changed files with 6 additions and 4 deletions
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10
src/diffusers/models/vae.py
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@@ -130,9 +130,9 @@ class Encoder(nn.Module):
self.gradient_checkpointing = False
def forward(self, x: torch.FloatTensor) -> torch.FloatTensor:
def forward(self, sample: torch.FloatTensor) -> torch.FloatTensor:
r"""The forward method of the `Encoder` class."""
sample = x
sample = self.conv_in(sample)
if self.training and self.gradient_checkpointing:
@@ -273,9 +273,11 @@ class Decoder(nn.Module):
self.gradient_checkpointing = False
def forward(self, z: torch.FloatTensor, latent_embeds: Optional[torch.FloatTensor] = None) -> torch.FloatTensor:
def forward(
self, sample: torch.FloatTensor, latent_embeds: Optional[torch.FloatTensor] = None
) -> torch.FloatTensor:
r"""The forward method of the `Decoder` class."""
sample = z
sample = self.conv_in(sample)
upscale_dtype = next(iter(self.up_blocks.parameters())).dtype