Gets the equivalent nd4j data type
    for a given numpy data type.
    # Arguments
        np_dtype: Numpy data type. One of
            ['float64', 'float32', 'float16']

def get_nd4j_dtype(np_dtype):
    """
    Gets the equivalent nd4j data type
    for a given numpy data type.
    # Arguments
        np_dtype: Numpy data type. One of
            ['float64', 'float32', 'float16']
    """
    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