code: def add_sequence_padding(data):
      n_sampels = len(data)
      max_seq_length = max(map(len, data))
  
      data_matrix = np.zeros((n_sampels, max_seq_length))
      for i, sample in enumerate(data):
          data_matrix[i, -len(sample) :] = sample
  
      return data_matrix
  
imports: import numpy
  import tensorflow
  from sklearn.model_selection import train_test_split
  from neupy.datasets import reber
  from neupy.utils import asfloat, tensorflow_session
  from neupy.exceptions import LayerConnectionError
  from neupy.layers.recurrent import clip_gradient
  from neupy import layers, algorithms, init
  from base import BaseTestCase
label_desc: Use image node_id 1 for calling a global function with example usage: add_sequence_padding(data) and returns: data_matrix