class_docstr: Options for generating statistics.
class_docstr_tok: ["Options","for","generating","statistics","."]
code: def experimental_slice_sqls(
      self, slice_sqls: Optional[List[Text]]
  ) -> None:
      if hasattr(self, "experimental_slice_functions"):
          _validate_slicing_options(
              self.experimental_slice_functions, slice_sqls
          )
      if slice_sqls and self.schema:
          for slice_sql in slice_sqls:
              _validate_sql(slice_sql, self.schema)
      self._slice_sqls = slice_sqls
  
imports: from __future__ import absolute_import
  from __future__ import division
  from __future__ import print_function
  import copy
  import json
  import logging
  import types
  from typing import Dict, List, Optional, Text, Union
  from tensorflow_data_validation import types
  from tensorflow_data_validation.statistics.generators import stats_generator
  from tensorflow_data_validation.utils import example_weight_map
  from tensorflow_data_validation.utils import schema_util
  from tensorflow_data_validation.utils import slicing_util
  from tfx_bsl.arrow import sql_util
  from tfx_bsl.coders import example_coder
  from tfx_bsl.public.proto import slicing_spec_pb2
  from google.protobuf import json_format
  from tensorflow_metadata.proto.v0 import schema_pb2
label_desc: Use image node_id 16 for calling the StatsOptions obj's underlying member method code with example usage: obj.experimental_slice_sqls(slice_sqls) without return types