def _as_variant_tensor(self): return gen_bigtable_ops.bigtable_scan_dataset( table=self._table._resource, # pylint: disable=protected-access prefix=self._prefix, start_key=self._start, end_key=self._end, column_families=self._column_families, columns=self._columns, probability=self._probability)
def __init__(self, table, prefix, start, end, normalized, probability): self._table = table self._prefix = prefix self._start = start self._end = end self._column_families = [i[0] for i in normalized] self._columns = [i[1] for i in normalized] self._probability = probability self._num_outputs = len(normalized) + 1 # 1 for row key variant_tensor = gen_bigtable_ops.bigtable_scan_dataset( table=self._table._resource, # pylint: disable=protected-access prefix=self._prefix, start_key=self._start, end_key=self._end, column_families=self._column_families, columns=self._columns, probability=self._probability) super(_BigtableScanDataset, self).__init__(variant_tensor)