dsb_a_eliasx2_c3_s2_p8a1.py 文件源码

def build_model():
    l_in = nn.layers.InputLayer((None, n_candidates_per_patient, 1,) + 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 = drop(penultimate_layer, name='drop_final2')

    l = dense(l, 256, name='dense_final1')

    l = drop(l, name='drop_final2')

    l = dense(l, 256, name='dense_final2')

    l = nn.layers.DenseLayer(l, num_units=1, W=nn.init.Orthogonal(),
                             nonlinearity=None, name='dense_p_benign')

    l = nn.layers.ReshapeLayer(l, (-1, n_candidates_per_patient, 1), name='reshape2patients')

    l_out = nn_lung.AggAllBenignExp(l, name='aggregate_all_nodules_benign')

    return namedtuple('Model', ['l_in', 'l_out', 'l_target'])(l_in, l_out, l_target)