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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def make_labels(X):
 """Helper function that generates a single 1D numpy.ndarray with labels which are good targets for stock logistic regression. Parameters: X (numpy.ndarray):
 The input data matrix. This must be a numpy.ndarray with 3 dimensions or an iterable containing 2 numpy.ndarrays with 2 dimensions each. Each correspond to the data for one of the two classes, every row corresponds to one example of the data set, every column, one different feature. Returns: numpy.ndarray: With a single dimension, containing suitable labels for all rows and for all classes defined in X (depth). """


  return numpy.hstack([k*numpy.ones(len(X[k]), dtype=int) for k in range(len(X))])