import tensorflow as tf


def gen_epochs_multi(raw_data_x,raw_data_y, timeindex, num_epochs, num_steps, batch_size,epoch_overlap):
    for i in range(int(num_epochs)):
        yield gen_batch_multi(raw_data_x,raw_data_y, timeindex, batch_size, num_steps, epoch_overlap)


def reset_graph():
    if 'sess' in globals() and sess:
        sess.close()
    tf.reset_default_graph()



"""
Define RNN graph
"""
def build_multilayer_rnn_graph_with_dynamic_rnn(cell_type, activation,state_size, num_steps, num_layers, input_size_x, input_size_y , learning_rate, lambda_l2_reg,random_seed=0):

