code: def get_nd4j_dtype(np_dtype):
      
      if type(np_dtype) == type:
          np_dtype = np_dtype.__name__
      elif type(np_dtype) == np.dtype:
          np_dtype = np_dtype.name
      mapping = {
          'float64': 'double',
          'float32': 'float',
          'float16': 'half'
      }
      nd4j_dtype = mapping.get(np_dtype)
      if not nd4j_dtype:
          raise Exception('Invalid numpy data type : ' + np_dtype)
      return nd4j_dtype
docs: Gets the equivalent nd4j data type
      for a given numpy data type.
      # Arguments
          np_dtype: Numpy data type. One of
              ['float64', 'float32', 'float16']