AudioLDM2UNet2DConditionModel  
A conditional 2D UNet model that takes a noisy sample, conditional state, and a timestep and returns a sample
shaped output. Compared to the vanilla [`UNet2DConditionModel`], this variant optionally includes an additional
self-attention layer in each Transformer block, as well as multiple cross-attention layers. It also allows for up
to two cross-attention embeddings, `encoder_hidden_states` and `encoder_hidden_states_1`.