3j4SSKJr SSKJr SSKJr SSKJr \"SS9\"SS \555r\"S S9\"S S \\555r S S /r g ))strict)BackboneConfigMixin)PreTrainedConfig)auto_docstringzfacebook/sapiens2-seg-0.4b) checkpointc^\rSrSr%SrSrSrSr\\ S-\ S'Sr \\ S-\ S'Sr \ \ S 'Sr \S-\ S 'Sr\\ S-\ S 'Sr\\ S-\ S 'S r\ \ S'Sr\\ S-\ S'Sr\\ S-\ S'S r\ \ S'Sr\ S-\ S'Sr\\ S-\ S'U4SjrS\ \\ -\\ \ 4-S\ \\ -\\ \ 4-SS4SjrSrU=r$)Sapiens2HeadConfiga upsample_out_channels (`list[int]`, *optional*): Output channel counts for each upsample block. The first block takes `hidden_size` channels as input; subsequent blocks use the previous output. upsample_kernel_sizes (`list[int]`, *optional*): Kernel size for each upsample block. Auto-filled with `[4, ...]` when `upsample_out_channels` is set but this is `None`. Must have the same length as `upsample_out_channels`. upsample_kernel_size (`int`, defaults to 4): Default kernel size for upsample blocks when `upsample_kernel_sizes` is not set. use_pixel_shuffle (`bool`, *optional*): Whether the upsample head uses pixel-shuffle upsampling instead of transposed convolutions. When `None` (default), the head uses transposed convolutions. conv_out_channels (`list[int]`, *optional*): Output channel counts for the refinement conv layers that follow the upsample blocks. conv_kernel_sizes (`list[int]`, *optional*): Kernel size for each refinement conv layer. Auto-filled with `[1, ...]` when `conv_out_channels` is set but this is `None`. Must have the same length as `conv_out_channels`. conv_kernel_size (`int`, defaults to 1): Default kernel size for conv layers when `conv_kernel_sizes` is not set. scale_conv_out_channels (`list[int]`, *optional*): Output channel counts for the stride-2 conv layers used to predict the focal-length scale. When `None` (default), no scale branch is built. scale_conv_kernel_sizes (`list[int]`, *optional*): Kernel size for each scale conv layer. Auto-filled with `[1, ...]` when `scale_conv_out_channels` is set but this is `None`. Must have the same length as `scale_conv_out_channels`. scale_conv_kernel_size (`int`, defaults to 1): Default kernel size for scale conv layers when `scale_conv_kernel_sizes` is not set. scale_final_input_size (`int`, *optional*): Flattened feature size passed into the scale MLP. When `None` (default), it is automatically inferred from `image_size` and `patch_size` in the parent [`Sapiens2Config`]. scale_final_hidden_sizes (`list[int]`, *optional*): Hidden-layer sizes for the MLP that maps flattened scale features to the scalar scale output. When `None` (default), no scale branch is built. sapiens2_head head_configNupsample_out_channelsupsample_kernel_sizesupsample_kernel_sizeuse_pixel_shuffleconv_out_channelsconv_kernel_sizesconv_kernel_sizescale_conv_out_channelsscale_conv_kernel_sizesscale_conv_kernel_sizescale_final_input_sizescale_final_hidden_sizesc >URb5URc(UR/[UR5-UlURb5UR c(UR /[UR5-UlURb5URc(UR/[UR5-Ul[TU],"S0UD6 g)N) rrrlenrrrrrrsuper __post_init__)selfkwargs __class__s m/home/wildlama/miniconda3/lib/python3.13/site-packages/transformers/models/sapiens2/configuration_sapiens2.pyr Sapiens2HeadConfig.__post_init__Ts  % % 1d6P6P6X*.*C*C)Ds4KeKeGf)fD &  ! ! -$2H2H2P&*&;&;%