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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

Crops the given PIL Image on the long edge. Args: size (sequence or int): Desired output size of the crop. If size is an int i

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

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

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

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

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

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

Uses the CLIP transformer encoder for text (from Hugging Face)

to match AttnBlock usage

to match AttnBlock usage