Buckets:
AutoencoderKLLTX2Audio
The 3D variational autoencoder (VAE) model with KL loss used in LTX-2 was introduced by Lightricks. This is for encoding and decoding audio latent representations.
The model can be loaded with the following code snippet.
from diffusers import AutoencoderKLLTX2Audio
vae = AutoencoderKLLTX2Audio.from_pretrained("Lightricks/LTX-2", subfolder="vae", dtype=torch.float32).to("cuda")
AutoencoderKLLTX2Audio[[diffusers.AutoencoderKLLTX2Audio]]
diffusers.AutoencoderKLLTX2Audio[[diffusers.AutoencoderKLLTX2Audio]]
diffusers.AutoencoderKLLTX2Audio(base_channels: int = 128, output_channels: int = 2, ch_mult: tuple = (1, 2, 4), num_res_blocks: int = 2, attn_resolutions: tuple[int, ...] | None = None, in_channels: int = 2, resolution: int = 256, latent_channels: int = 8, norm_type: str = 'pixel', causality_axis: str | None = 'height', dropout: float = 0.0, mid_block_add_attention: bool = False, sample_rate: int = 16000, mel_hop_length: int = 160, is_causal: bool = True, mel_bins: int | None = 64, double_z: bool = True)
LTX2 audio VAE for encoding and decoding audio latent representations.
encode[[diffusers.AutoencoderKLLTX2Audio.encode]]
encode(x: Tensor, return_dict: bool = True)
decode[[diffusers.AutoencoderKLLTX2Audio.decode]]
decode(z: Tensor, return_dict: bool = True)
forward[[diffusers.AutoencoderKLLTX2Audio.forward]]
forward(sample: Tensor, sample_posterior: bool = False, return_dict: bool = True, generator: typing.Optional[torch.Generator] = None)
Parameters:
sample (torch.Tensor) : Input sample.
sample_posterior (bool, optional, defaults to False) : Whether to sample from the posterior.
return_dict (bool, optional, defaults to True) : Whether or not to return a DecoderOutput instead of a plain tuple.
generator (torch.Generator, optional) : A torch.Generator to make sampling deterministic.
Returns: DecoderOutput or tuple
If return_dict is True, a DecoderOutput is returned, otherwise a plain tuple is returned.
Xet Storage Details
- Size:
- 2.76 kB
- Xet hash:
- 92243558d0ff48eac674f01310774c54491571d8ff2f522ace9f32833cd12566
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