super-gradients/src/super_gradients/recipes/arch_params/unet_arch_params.yaml

defaults:
  - unet_default_arch_params
  - _self_

backbone_params:
  strides_list: [1, 2, 2, 2, 2]   #  list of stride per stage.
  width_list: [64, 128, 256, 512, 512]   # list of num channels per stage.
  num_blocks_list: [2, 2, 2, 2, 2]    # list of num blocks per stage.
  block_types_list: [ConvStage, ConvStage, ConvStage, ConvStage, ConvStage]   # list of block types per stage. See unet_encoder.DownBlockType for options.
  is_out_feature_list: [ True, True, True, True, True ]   # list of flags whether stage features should be an output.
  block_params:
    downsample_mode: max_pool


context_module:

decoder_params:
  # skip expansion ratio value, before fusing the skip features from the encoder with the decoder features, a projection
  # convolution is applied upon the encoder features to project the num_channels by skip_expansion.
  skip_expansion: 1.
  decoder_scale: .5   # num_channels width ratio between encoder stages and decoder stages.
  up_block_types: [UpCatBlock, UpCatBlock, UpCatBlock, UpCatBlock]    # See unet_decoder.UpBlockType for options.
  up_block_repeat_list: [ 2, 2, 2, 1]   # num of blocks per decoder stage, the `block` implementation depends on the up-block type.
  mode: bilinear
  align_corners: False
  up_factor: 2

final_upsample_factor: 1    # Final upsample scale factor after the segmentation head.

_convert_: all