def build_model():
l_in = nn.layers.InputLayer((None, n_candidates_per_patient, ) + p_transform['patch_size'])
l_in_rshp = nn.layers.ReshapeLayer(l_in, (-1, 1,) + p_transform['patch_size'])
l_target = nn.layers.InputLayer((batch_size,))
penultimate_layer = load_pretrained_model(l_in_rshp)
l = nn.layers.DenseLayer(penultimate_layer, num_units=1, W=nn.init.Orthogonal(),
nonlinearity=nn.nonlinearities.sigmoid, name='dense_p_benign')
l = nn.layers.ReshapeLayer(l, (-1, n_candidates_per_patient, 1), name='reshape2patients')
l_out = nn_lung.LogMeanExp(l, r=8, axis=(1, 2), name='LME')
return namedtuple('Model', ['l_in', 'l_out', 'l_target'])(l_in, l_out, l_target)
dsb_a_eliasx35_relias18_s5_p8a1.py 文件源码
python
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