The hidden states output conditioned on encoder_hidden_states input. Output of last layer of model.    The output of UNet2DConditionModel.  FlaxUNet2DConditionModel  class diffusers.FlaxUNet2DConditionModel  < source > ( sample_size: int = 32 in_channels: int = 4 out_channels: int = 4 down_block_types: Tuple = ('CrossAttnDownBlock2D', 'CrossAttnDownBlock2D', 'CrossAttnDownBlock2D', 'DownBlock2D') up_block_types: Tuple = ('UpBlock2D', 'CrossAttnUpBlock2D', 'CrossAttnUpBlock2D', 'CrossAttnUpBlock2D') only_cross_attention: Union = False block_out_channels: Tuple = (320, 640, 1280, 1280) layers_per_block: int = 2 attention_head_dim: Union = 8 num_attention_heads: Union = None cross_attention_dim: int = 1280 dropout: float = 0.0 use_linear_projection: bool = False dtype: dtype = <class 'jax.numpy.float32'> flip_sin_to_cos: bool = True freq_shift: int = 0 use_memory_efficient_attention: bool = False split_head_dim: bool = False transformer_layers_per_block: Union = 1 addition_embed_type: Optional = None addition_time_embed_dim: Optional = None addition_embed_type_num_heads: int = 64 projection_class_embeddings_input_dim: Optional = None parent: Union = <flax.linen.module._Sentinel object at 0x7fb48fdbfdf0> name: Optional = None  )   Parameters   sample_size (int, optional) —