import tensorflow as tf

def batch_to_seq(h, nbatch, nsteps, flat=False):
    if flat:
        h = tf.reshape(h, [nbatch, nsteps])
    else:
        h = tf.reshape(h, [nbatch, nsteps, -1])
    return [tf.squeeze(v, [1]) for v in tf.split(axis=1, num_or_size_splits=nsteps, value=h)]


def seq_to_batch(h, flat = False):
    shape = h[0].get_shape().as_list()
