104B6         ; mapped                 ; 104DE         # 9.0  OSAGE CAPITAL LETTER EHCHA
104B7         ; mapped                 ; 104DF         # 9.0  OSAGE CAPITAL LETTER E
104B8         ; mapped                 ; 104E0         # 9.0  OSAGE CAPITAL LETTER EIN
104B9         ; mapped                 ; 104E1         # 9.0  OSAGE CAPITAL LETTER HA

		{"ErrorHandling", Type, 0},
		{"ExitOnError", Const, 0},
		{"Flag", Type, 0},
		{"Flag.DefValue", Field, 0},
		{"Flag.Name", Field, 0},
		{"Flag.Usage", Field, 0},
		{"Flag.Value", Field, 0},
		{"FlagSet", Type, 0},
		{"FlagSet.Usage", Field, 0},
		{"Float64", Func, 0},
		{"Float64Var", Func, 0},
		{"Func", Func, 16},
		{"Getter", Type, 2},
		{"Int", Func, 0},
		{"Int64", Func, 0},

            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.

  let summary = [{
Returns the index with the largest value across dimensions of a tensor.
  }];

  let description = [{
Note that in case of ties the identity of the return value is not guaranteed.

Usage:
  ```python
  import tensorflow as tf
  a = [1, 10, 26.9, 2.8, 166.32, 62.3]
  b = tf.math.argmax(input = a)
  c = tf.keras.backend.eval(b)
  # c = 4

              }
            ],