[keras] multivariate time-series data with var. len.

def create_variableTimeSeries(num_sample, max_seq_len, input_dim):
  # Parameters
  N = num_sample
  halfN = int(N/2)
  dimension = input_dim
  rand_seq_len = max_seq_len

  # Data
  np.random.seed(123)  # to generate the same numbers

  # create sequence lengths between 1 to rand_seq_len
  seq_lens = np.random.randint(1, rand_seq_len, halfN)
  X_zero = np.array([np.random.normal(0, 1, size=(seq_len, dimension)) for seq_len in seq_lens])
  y_zero = np.zeros((halfN, 1))

  X_one = np.array([np.random.normal(1, 1, size=(seq_len, dimension)) for seq_len in seq_lens])
  y_one = np.ones((halfN, 1))

  # shuffle zero and one classes
  p = np.random.permutation(N)
  X = np.concatenate((X_zero, X_one))[p]
  y = np.concatenate((y_zero, y_one))[p]

  return X, y

X_train, y_train = create_variableTimeSeries(num_sample=100, max_seq_len=5, input_dim=10)