"type" : "reloadable_kuromoji_tokenizer",
        "mode" : "normal",
        "discard_punctuation" : "false"
      },
      "pattern_split" : {
        "type" : "simple_pattern_split",
        "pattern" : "__and__"
      }
    },
    "analyzer" : {
      "reading_analyzer" : {
        "type" : "custom",
        "tokenizer" : "kuromoji_neologd_normal",
        "filter" : ["reading_form"]
      },

contrib = _LazyLoader("contrib", globals(), "tensorflow.contrib",
                      _CONTRIB_WARNING)
# The templated code that replaces the placeholder above sometimes
# sets the __all__ variable. If it does, we have to be sure to add
# "contrib".
if "__all__" in vars():
  vars()["__all__"].append("contrib")

from tensorflow.python.platform import flags
# The "app" module will be imported as part of the placeholder section above.

		}
	} else if arr, ok := value.ToArray(); ok {
		v = arr
	} else {
		return nil, fmt.Errorf("unsupported sql value %v and type %v", value, value.GetTypeString())
	}

	name = strings.ReplaceAll(name, "*", "__ALL__")
	r.KVS = append(r.KVS, jstream.KV{Key: name, Value: v})
	return r, nil
}

// WriteCSV - encodes to CSV data.
func (r *Record) WriteCSV(writer io.Writer, opts sql.WriteCSVOpts) error {
	var csvRecord []string

try:
  del python
except NameError:
  pass
try:
  del core
except NameError:
  pass
try:
  del compiler
except NameError:
  pass

        settings.array().add(SuggestSettings.DefaultKeys.SUPPORTED_FIELDS, field);

        Map<String, Object> document = new HashMap<>();
        document.put(field, "商品１__and__商品２");
        suggester.indexer().indexFromDocument(new Map[] { document });
        suggester.refresh();

    truncating inputs such as from int64 to int32.
*   Adds `tf.sparse.map_values` to apply a function to the `.value`s of
    `SparseTensor` arguments.
*   The Python bitwise operators for `Tensor` (`__and__`, `__or__`, `__xor__`
    and `__invert__` now support non-`bool` arguments and apply the
    corresponding bitwise ops. `bool` arguments continue to be supported and