AutoencoderDC  
An Autoencoder model introduced in [DCAE](https://arxiv.org/abs/2410.10733) and used in
[SANA](https://arxiv.org/abs/2410.10629).  
This model inherits from [`ModelMixin`]. Check the superclass documentation for it's generic methods implemented
for all models (such as downloading or saving).  
Args:
in_channels (`int`, defaults to `3`):
The number of input channels in samples.
latent_channels (`int`, defaults to `32`):
The number of channels in the latent space representation.
encoder_block_types (`Union[str, Tuple[str]]`, defaults to `"ResBlock"`):
The type(s) of block to use in the encoder.
decoder_block_types (`Union[str, Tuple[str]]`, defaults to `"ResBlock"`):
The type(s) of block to use in the decoder.
encoder_block_out_channels (`Tuple[int, ...]`, defaults to `(128, 256, 512, 512, 1024, 1024)`):
The number of output channels for each block in the encoder.
decoder_block_out_channels (`Tuple[int, ...]`, defaults to `(128, 256, 512, 512, 1024, 1024)`):
The number of output channels for each block in the decoder.
encoder_layers_per_block (`Tuple[int]`, defaults to `(2, 2, 2, 3, 3, 3)`):
The number of layers per block in the encoder.
decoder_layers_per_block (`Tuple[int]`, defaults to `(3, 3, 3, 3, 3, 3)`):
The number of layers per block in the decoder.
encoder_qkv_multiscales (`Tuple[Tuple[int, ...], ...]`, defaults to `((), (), (), (5,), (5,), (5,))`):
Multi-scale configurations for the encoder's QKV (query-key-value) transformations.
decoder_qkv_multiscales (`Tuple[Tuple[int, ...], ...]`, defaults to `((), (), (), (5,), (5,), (5,))`):
Multi-scale configurations for the decoder's QKV (query-key-value) transformations.
upsample_block_type (`str`, defaults to `"pixel_shuffle"`):
The type of block to use for upsampling in the decoder.
downsample_block_type (`str`, defaults to `"pixel_unshuffle"`):
The type of block to use for downsampling in the encoder.
decoder_norm_types (`Union[str, Tuple[str]]`, defaults to `"rms_norm"`):
The normalization type(s) to use in the decoder.
decoder_act_fns (`Union[str, Tuple[str]]`, defaults to `"silu"`):
The activation function(s) to use in the decoder.
scaling_factor (`float`, defaults to `1.0`):
The multiplicative inverse of the root mean square of the latent features. This is used to scale the latent
space to have unit variance when training the diffusion model. The latents are scaled with the formula `z =
z * scaling_factor` before being passed to the diffusion model. When decoding, the latents are scaled back
to the original scale with the formula: `z = 1 / scaling_factor * z`.  
- encode
- decode
- all
/Users/nielsrogge/Documents/python_projecten/diffusers/docs/source/en/api/models/autoencoder_dc.md