"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"]
      },

//           Normalization will convert all letters to lowercase and
//           non-alphanumeric characters to '_' to make resulting names match
//           the "[a-z][a-z0-9_]*" pattern for operation argument names.
//           `inputs` cannot contain the same tensor twice.
//  noutputs - number of elements in `outputs` array
//  outputs - array of TF_Outputs that specify the outputs of the function.

not <code>3&amp;(1&lt;&lt;2)</code>.
Also, constants are always evaluated as 64-bit unsigned integers.
Thus <code>-2</code> is not the integer value minus two,
but the unsigned 64-bit integer with the same bit pattern.
The distinction rarely matters but
to avoid ambiguity, division or right shift where the right operand's
high bit is set is rejected.
</p>

<h3 id="symbols">Symbols</h3>

<p>

		(*Reader).ReadBytes,
		(*Reader).ReadSlice,
		func(r *Reader, delim byte) ([]byte, error) {
			data, err := r.ReadString(delim)
			return []byte(data), err
		},
		// ReadLine doesn't fit the data/pattern easily
		// so we leave it out. It should be covered via
		// the ReadSlice test since ReadLine simply calls
		// ReadSlice, and it's that function that handles
		// the last byte.
	}

	symbol. The optional <remote> specifies the symbol's name and
	possibly version in the dynamic library, and the optional "<library>"
	names the specific library where the symbol should be found.

	On AIX, the library pattern is slightly different. It must be
	"lib.a/obj.o" with obj.o the member of this library exporting
	this symbol.

	In the <remote>, # or @ can be used to introduce a symbol version.

	Examples:

            seen couple of use cases where the model usage pattern is not as
            expected and would not work with this change.
    *   output tensors of one layer is used in the constructor of another.
    *   symbolic tensors outside the scope of the model are used in custom loss
        functions. The flag can be disabled for these cases and ideally the
        usage pattern will need to be fixed.