pyspark/bigdl/util/common.py
def to_ndarray(self):
        """
        Transfer JTensor to ndarray.
        As SparseTensor may generate an very big ndarray, so we don't support this function for SparseTensor.
        :return: a ndarray
        """
        assert self.indices is None, "sparseTensor to ndarray is not supported"
        return np.array(self.storage, dtype=get_dtype(self.bigdl_type)).reshape(self.shape)
def to_ndarray(self):
        """
        Transfer JTensor to ndarray.
        As SparseTensor may generate an very big ndarray, so we don't support this function for SparseTensor.
        :return: a ndarray
        """
        assert self.indices is None, "sparseTensor to ndarray is not supported"
        return np.array(self.storage, dtype=get_dtype(self.bigdl_type)).reshape(self.shape)
def to_ndarray ( self ) : assert self . indices is None , "sparseTensor to ndarray is not supported" return np . array ( self . storage , dtype = get_dtype ( self . bigdl_type ) ) . reshape ( self . shape )
Transfer JTensor to ndarray.
        As SparseTensor may generate an very big ndarray, so we don't support this function for SparseTensor.
        :return: a ndarray
Transfer JTensor to ndarray . As SparseTensor may generate an very big ndarray so we don t support this function for SparseTensor . : return : a ndarray