}

def TF_EluOp : TF_Op<"Elu", [Pure, TF_SameOperandsAndResultTypeResolveRef]> {
  let summary = "Computes the exponential linear function.";

  let description = [{
The ELU function is defined as:

 * $ e ^ x - 1 $ if $ x < 0 $
 * $ x $ if $ x >= 0 $

Examples:

>>> tf.nn.elu(1.0)
<tf.Tensor: shape=(), dtype=float32, numpy=1.0>
>>> tf.nn.elu(0.0)

*   `tf.lite`:

    *   Added TFLite builtin op support for the following TF ops:
        *   `tf.math.argmin`/`tf.math.argmax` for input data type `tf.bool` on
            CPU.
        *   `tf.nn.gelu` op for output data type `tf.float32` and quantization
            on CPU.
    *   Add nominal support for unsigned 16-bit integer tensor types. Note that