diff --git a/nnUnet/initialization.py b/nnUnet/initialization.py new file mode 100644 index 0000000000000000000000000000000000000000..901c4b132d23b794e3f0137d61ea963a4aeddabb --- /dev/null +++ b/nnUnet/initialization.py @@ -0,0 +1,38 @@ +# Copyright 2020 Division of Medical Image Computing, German Cancer Research Center (DKFZ), Heidelberg, Germany +# +# Licensed under the Apache License, Version 2.0 (the "License"); +# you may not use this file except in compliance with the License. +# You may obtain a copy of the License at +# +# http://www.apache.org/licenses/LICENSE-2.0 +# +# Unless required by applicable law or agreed to in writing, software +# distributed under the License is distributed on an "AS IS" BASIS, +# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. +# See the License for the specific language governing permissions and +# limitations under the License. + + +from torch import nn + + +class InitWeights_He(object): + def __init__(self, neg_slope=1e-2): + self.neg_slope = neg_slope + + def __call__(self, module): + if isinstance(module, nn.Conv3d) or isinstance(module, nn.Conv2d) or isinstance(module, nn.ConvTranspose2d) or isinstance(module, nn.ConvTranspose3d): + module.weight = nn.init.kaiming_normal_(module.weight, a=self.neg_slope) + if module.bias is not None: + module.bias = nn.init.constant_(module.bias, 0) + + +class InitWeights_XavierUniform(object): + def __init__(self, gain=1): + self.gain = gain + + def __call__(self, module): + if isinstance(module, nn.Conv3d) or isinstance(module, nn.Conv2d) or isinstance(module, nn.ConvTranspose2d) or isinstance(module, nn.ConvTranspose3d): + module.weight = nn.init.xavier_uniform_(module.weight, self.gain) + if module.bias is not None: + module.bias = nn.init.constant_(module.bias, 0)