def load_data_old(df_, seq_len):
    data_raw = df_.values
    data = []
    for index in range(len(data_raw) - seq_len):
        data.append(data_raw[index: index + seq_len])

    data = np.array(data);
    valid_set_size = int(np.round(valid_set_size_percentage/100*data.shape[0]));
    test_set_size = int(np.round(test_set_size_percentage/100*data.shape[0]));
    train_set_size = data.shape[0] - (valid_set_size + test_set_size);

    x_train = data[:train_set_size,:-1,:-1]
    y_train = data[:train_set_size,-1,-1:]

    x_valid = data[train_set_size:train_set_size+valid_set_size,:-1,:-1]
    y_valid = data[train_set_size:train_set_size+valid_set_size,-1,-1:]

    x_test = data[train_set_size+valid_set_size:,:-1,:-1]
    y_test = data[train_set_size+valid_set_size:,-1,-1:]
    return[x_train, y_train, x_valid, y_valid, x_test, y_test]

x_train, y_train, x_valid, y_valid, x_test, y_test = load_data(df,seq_len)
X = tf.placeholder(tf.float32, [None, n_steps, n_inputs],name="input")
y = tf.placeholder(tf.float32, [None, n_outputs],name="output")
n_inputs = x_train.shape[2]
n_outputs = y_train.shape[1]
layers = [tf.contrib.rnn.LSTMCell(num_units=n_neurons,activation=tf.nn.leaky_relu, use_peepholes = True,name="layer"+str(layer))
             for layer in range(n_layers)]
multi_layer_cell = tf.contrib.rnn.MultiRNNCell(layers)
rnn_outputs, states = tf.nn.dynamic_rnn(multi_layer_cell, X, dtype=tf.float32)
stacked_rnn_outputs = tf.reshape(rnn_outputs, [-1, n_neurons])
stacked_outputs = tf.layers.dense(stacked_rnn_outputs, n_outputs)
outputs = tf.reshape(stacked_outputs, [-1, n_steps, n_outputs])
outputs = tf.identity(outputs[:,n_steps-1,:], name="prediction")
loss = tf.reduce_mean(tf.square(outputs - y)) # loss function = mean squared error
optimizer = tf.train.AdamOptimizer(learning_rate=learning_rate)
training_op = optimizer.minimize(loss)

input1,input2,input3,input4,input5,input6,input7,input8,output
1,2,3,4,5,6,7,8,1
2,3,4,5,6,7,8,9,0
3,4,5,6,7,8,9,10,-1
4,5,6,7,8,9,10,11,-1
5,6,7,8,9,10,11,12,1
6,7,8,9,10,11,12,13,0
7,8,9,10,11,12,13,14,1

[array([[ 1,  2,  3,  4,  5,  6,  7,  8,  1],
       [ 2,  3,  4,  5,  6,  7,  8,  9,  0],
       [ 3,  4,  5,  6,  7,  8,  9, 10, -1]], dtype=int64), array([[ 2,  3,  4,  5,  6,  7,  8,  9,  0],
       [ 3,  4,  5,  6,  7,  8,  9, 10, -1],
       [ 4,  5,  6,  7,  8,  9, 10, 11, -1]], dtype=int64), array([[ 3,  4,  5,  6,  7,  8,  9, 10, -1],
       [ 4,  5,  6,  7,  8,  9, 10, 11, -1],
       [ 5,  6,  7,  8,  9, 10, 11, 12,  1]], dtype=int64), array([[ 4,  5,  6,  7,  8,  9, 10, 11, -1],
       [ 5,  6,  7,  8,  9, 10, 11, 12,  1],
       [ 6,  7,  8,  9, 10, 11, 12, 13,  0]], dtype=int64)]