e at the start remain the same, while other parameters can still be adjusted during inference. Some of the most important parameters are: sample_size: the height and width dimension of the input sample. in_channels: the number of input channels of the input sample. down_block_types and up_block_types: the type of down- and upsampling blocks used to create the UNet architecture. block_out_channels: the number of output channels of the downsampli