import tensorflow as tf

        # y_conv = tf.matmul(h_fc1_drop, W_fc2) + b_fc2
        # print("----y_conv-----")
        # print(y_conv)
        # exit()

        # Exchange dim 1 and dim 0
        # Start at: [0,1,2] = [batch_size, 128, 9] => [batch_size, 32, 36]
        feature_mat = tf.transpose(feature_mat, [1, 0, 2])
        # New feature_mat's shape: [time_steps, batch_size, n_inputs] [128, batch_size, 9]
        print("----feature_mat-----")
        print(feature_mat)
        # exit()

        # Temporarily crush the feature_mat's dimensions
