A residual block that can optionally change the number of channels. :param channels: the number of input channels. :param emb_channels

A sequential module that passes timestep embeddings to the children that support it as an extra input.

An attention block that allows spatial positions to attend to each other. Originally ported from here, but adapted to the N-d case. ht

Transformer block for image-like data. First, project the input (aka embedding) and reshape to b, t, d. Then apply standard trans

A downsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determ

Defines a PatchGAN discriminator as in Pix2Pix --> see https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py

An upsampling layer with an optional convolution. :param channels: channels in the inputs and outputs. :param use_conv: a bool determi

Implementation of a sine-based periodic activation function Shape: - Input: (B, C, T) - Output: (B, C, T), same shape as the

A modified Snake function which uses separate parameters for the magnitude of the periodic components Shape: - Input: (B, C, T)

A module which performs QKV attention and splits in a different order.

Adapted from CLIP: https://github.com/openai/CLIP/blob/main/clip/model.py

Uses a pretrained BERT tokenizer by huggingface. Vocab size: 30522 (?)

A class for interfacing CLAP model.

A class for interfacing CLAP model.

to match AttnBlock usage

Defines a PatchGAN discriminator as in Pix2Pix --> see https://github.com/junyanz/pytorch-CycleGAN-and-pix2pix/blob/master/models/networks.py

A module which performs QKV attention. Matches legacy QKVAttention + input/ouput heads shaping

Wraps an arbitrary object with __len__ and __getitem__ into a pytorch dataset

Uses the BERT tokenizr model and add some transformer encoder layers

The half UNet model with attention and timestep embedding. For usage, see UNet.

Uses the CLAP transformer encoder for text (from huggingface)

Uses the T5 transformer encoder for text

Uses the T5 transformer encoder for text