↓ 14 callersFunctionconv3d(inputs, weight, bias, meta_step_size=0.001, stride=1, padding=1, dilation=1, groups=1, meta_loss=None,
mldg-seg/ops.py:133
↓ 5 callersFunctionflattenFlattens a given tensor such that the channel axis is first. The shapes are transformed as follows: (N, C, D, H, W) -> (C, N * D * H * W)
mldg-seg/dice_loss.py:317
↓ 2 callersMethod__init__(self, inplanes, planes, dropout=0.3, norm='gn', first=False)
mldg-seg/Unet3D_meta_learning_orig.py:26
↓ 2 callersMethod__init__(self, inplanes, planes, meta_loss, meta_step_size, stop_gradient, dropout=0.3, norm='gn', first=False)
mldg-seg/Unet3D_meta_learning.py:26
Method__init__(self, epsilon=1e-5, weight=None, ignore_index=None, sigmoid_normalization=False, num_classes=2)
mldg-seg/dice_loss.py:105
Method__init__(self, planes, meta_loss, meta_step_size, stop_gradient, norm='gn', first=False)
mldg-seg/Unet3D_meta_learning.py:71
Method__init__(self, image_list, modality, transform=False, patch_size=32, n_patches_transform=30, all_patches=False, is_tes
mldg-seg/data_reader_unet_spine.py:456