import tensorflow as tf

                                                                        name='conv_batch_norm_{}'.format(k))
                    if encoder.conv_activation is not None and encoder.conv_activation.lower() == 'relu':
                        encoder_inputs_ = tf.nn.relu(encoder_inputs_)

                    encoder_input_length_ = tf.to_int32(tf.ceil(encoder_input_length_ / strides[1]))

                feature_size = encoder_inputs_.shape[2].value
                channels = encoder_inputs_.shape[3].value
