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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. This model inherits from ModelMixin. Check the superclass documentation for it’s generic methods implemented
for all models (such as dow