def build_up_block(self, inputs, down_inputs, name, final=False):
    out_num = inputs.shape[self.channel_axis].value
    conv1 = self.deconv_func()(inputs, out_num, self.conv_size, (name + '/conv1'), self.conf.data_type, action=self.conf.action)
    conv1 = tf.concat([conv1, down_inputs], self.channel_axis, name=(name + '/concat'))
    conv2 = self.conv_func()(conv1, out_num, self.conv_size, (name + '/conv2'), self.conf.data_type)
    out_num = (self.conf.class_num if final else (out_num / 2))
    conv3 = ops.conv(conv2, out_num, self.conv_size, (name + '/conv3'), self.conf.data_type, (not final))
    return conv3
def build_up_block(self, inputs, down_inputs, name, final=False):
    out_num = inputs.shape[self.channel_axis].value
    conv1 = self.deconv_func()(inputs, out_num, self.conv_size, (name + '/conv1'), self.conf.data_type, action=self.conf.action)
    conv1 = tf.concat([conv1, down_inputs], self.channel_axis, name=(name + '/concat'))
    conv2 = self.conv_func()(conv1, out_num, self.conv_size, (name + '/conv2'), self.conf.data_type)
    out_num = (self.conf.class_num if final else (out_num / 2))
    conv3 = ops.conv(conv2, out_num, self.conv_size, (name + '/conv3'), self.conf.data_type, (not final))
    return conv3