pyspark/bigdl/util/common.py
def to_sample_rdd(x, y, numSlices=None):
    """
    Conver x and y into RDD[Sample]
    :param x: ndarray and the first dimension should be batch
    :param y: ndarray and the first dimension should be batch
    :param numSlices:
    :return:
    """
    sc = get_spark_context()
    from bigdl.util.common import Sample
    x_rdd = sc.parallelize(x, numSlices)
    y_rdd = sc.parallelize(y, numSlices)
    return x_rdd.zip(y_rdd).map(lambda item: Sample.from_ndarray(item[0], item[1]))
def to_sample_rdd(x, y, numSlices=None):
    """
    Conver x and y into RDD[Sample]
    :param x: ndarray and the first dimension should be batch
    :param y: ndarray and the first dimension should be batch
    :param numSlices:
    :return:
    """
    sc = get_spark_context()
    from bigdl.util.common import Sample
    x_rdd = sc.parallelize(x, numSlices)
    y_rdd = sc.parallelize(y, numSlices)
    return x_rdd.zip(y_rdd).map(lambda item: Sample.from_ndarray(item[0], item[1]))
Conver x and y into RDD[Sample]
    :param x: ndarray and the first dimension should be batch
    :param y: ndarray and the first dimension should be batch
    :param numSlices:
    :return: