explicit ExpGradientFunction(AbstractTensorHandle* exp) : exp_(exp) {
    exp->Ref();
  }
  Status Compute(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> grad_outputs,
                 absl::Span<AbstractTensorHandle*> grad_inputs) override {
    AbstractTensorHandle* conj_output;
    std::string name = "Conj_Exp_Grad";
    TF_RETURN_IF_ERROR(SafeConj(ctx, exp_.get(), &conj_output, name.c_str()));

  std::unique_ptr<GradientFunction> gradient_function(
      new PassThroughGradientFunction);
  tape.RecordOperation(inputs, {exp_output}, gradient_function.release());
  TF_RETURN_IF_ERROR(tape.ComputeGradient(ctx,
                                          /*targets*/ {exp_output},
                                          /*sources=*/inputs,
                                          /*output_gradients=*/{},

}

Status ExpModel(AbstractContext* ctx,
                absl::Span<AbstractTensorHandle* const> inputs,
                absl::Span<AbstractTensorHandle*> outputs) {
  return ops::Exp(ctx, inputs[0], &outputs[0], "Exp");
}

Status SqrtModel(AbstractContext* ctx,
                 absl::Span<AbstractTensorHandle* const> inputs,
                 absl::Span<AbstractTensorHandle*> outputs) {

    *   The Python TF Lite Interpreter bindings now have an option `experimental_disable_delegate_clustering` to turn-off delegate clustering.
    *   Added int16x8 support for the built-in op `exp`
    *   Added int16x8 support for the built-in op `mirror_pad`
    *   Added int16x8 support for the built-in ops `space_to_batch_nd` and `batch_to_space_nd`