import tensorflow as tf

    #   squeeze and 2d resize
    squeeze_b_z = tf.reshape(reoriented, [-1, y_size_new, x_size, c_size], name='reshape_bz')
    resize_b_z = tf.compat.v1.image.resize_bilinear(squeeze_b_z, [y_size_new, x_size_new], align_corners=align)
    resume_b_z = tf.reshape(resize_b_z, [-1, z_size_new, y_size_new, x_size_new, c_size], name='resume_bz')
    
    output_tensor = tf.transpose(resume_b_z, [0, 3, 2, 1, 4])
    return output_tensor


def conv3d(x, kernel_size, filters, padding='SYMMETRIC', activation=None, initialization=None, use_bias=True):
