dsb_a_eliasq6_mal2_s5_p8a1_all.py 文件源码

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((None,))

    l = load_pretrained_model(l_in_rshp)

    #ins = penultimate_layer.output_shape[1]
    # l = conv3d(penultimate_layer, ins, filter_size=3, stride=2)
    # #l = feat_red(l)
    #
    #
    # l = nn.layers.DropoutLayer(l)
    # #
    # l = nn.layers.DenseLayer(l, num_units=256, W=nn.init.Orthogonal(),
    #                          nonlinearity=nn.nonlinearities.rectify)

    #l = nn.layers.DropoutLayer(l)

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

    l_out = nn_lung.LogMeanExp(l,r=16, axis=(1, 2), name='LME')

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