RepConTUR / plans.json
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Add RepConTUR-1B weights, remote code, tokenizer and model card
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{
"dataset_name": "VoxTellDataset",
"image_reader_writer": "NibabelIOWithReorient",
"configurations": {
"3d_fullres": {
"data_identifier": "nnUNetResEncUNetLPlans_noResampling_3d_fullres",
"preprocessor_name": "DefaultPreprocessor",
"batch_size": 2,
"patch_size": [
192,
192,
192
],
"normalization_schemes": [
"ZScoreNormalization"
],
"architecture": {
"network_class_name": "dynamic_network_architectures.architectures.unet.ResidualEncoderUNet",
"arch_kwargs": {
"n_stages": 6,
"features_per_stage": [
32,
64,
128,
256,
320,
320
],
"conv_op": "torch.nn.modules.conv.Conv3d",
"kernel_sizes": [
[
3,
3,
3
],
[
3,
3,
3
],
[
3,
3,
3
],
[
3,
3,
3
],
[
3,
3,
3
],
[
3,
3,
3
]
],
"strides": [
[
1,
1,
1
],
[
2,
2,
2
],
[
2,
2,
2
],
[
2,
2,
2
],
[
2,
2,
2
],
[
2,
2,
2
]
],
"n_blocks_per_stage": [
1,
3,
4,
6,
6,
6
],
"n_conv_per_stage_decoder": [
1,
1,
1,
1,
1
],
"conv_bias": true,
"norm_op": "torch.nn.modules.instancenorm.InstanceNorm3d",
"norm_op_kwargs": {
"eps": 1e-05,
"affine": true
},
"dropout_op": null,
"dropout_op_kwargs": null,
"nonlin": "torch.nn.LeakyReLU",
"nonlin_kwargs": {
"inplace": true
}
},
"_kw_requires_import": [
"conv_op",
"norm_op",
"dropout_op",
"nonlin"
]
},
"batch_dice": false
}
},
"experiment_planner_used": "nnUNetPlannerResEncL_noResampling"
}