mlir::TFL::NumericVerifyOp op, const std::vector<int32_t>& operands,
    const std::vector<int32_t>& results) {
  float tolerance = op.getTolerance().convertToFloat();
  bool log_if_failed = op.getLogIfFailed();
  auto fbb = std::make_unique<flexbuffers::Builder>();
  fbb->Map([&]() {
    fbb->Float("tolerance", tolerance);
    fbb->Bool("log_if_failed", log_if_failed);
  });
  fbb->Finish();

    register a dataset with the tf.data service, and another process to consume
    data from the dataset.
*   Adds support for dispatcher fault tolerance. To enable fault tolerance,
    configure a `work_dir` when running your dispatcher server and set
    `dispatcher_fault_tolerance=True`. The dispatcher will store its state to

}

def TF_ApproximateEqualOp : TF_Op<"ApproximateEqual", [Commutative, Pure]> {
  let summary = "Returns the truth value of abs(x-y) < tolerance element-wise.";

  let arguments = (ins
    TF_NumberTensor:$x,
    TF_NumberTensor:$y,

    DefaultValuedOptionalAttr<F32Attr, "1e-05f">:$tolerance
  );

  let results = (outs
    TF_BoolTensor:$z
  );

  TF_DerivedOperandTypeAttr T = TF_DerivedOperandTypeAttr<0>;