%0:2 = "tf_device.parallel_execute"() ({
      %1 = "tf_device.launch"() ({
        %2 = "tf._XlaCompileMlirPlaceholderProgramKey"() : () -> tensor<3x!tf_type.string>
        %3 = "tf._XlaRecvAtHost"(%2) {_xla_has_host_transfer = true, device_ordinal = 0 : i64, key = "host_compute_channel_0_args"} : (tensor<3x!tf_type.string>) -> tensor<?xi32>
        %4 = "tf.B"(%3) : (tensor<?xi32>) -> tensor<?x!tf_type.string>

  let extraClassDeclaration = [{
    func::FuncOp GetHostFunc(mlir::OwningOpRef<mlir::ModuleOp>* mlir_module);
  }];

  let hasVerifier = 1;
}

def TF__XlaRecvAtHostOp : TF_Op<"_XlaRecvAtHost", [DeclareOpInterfaceMethods<TF_GetResourceInstanceInterface>, TF_RecvSideEffect]> {
  let summary = [{
A placeholder op to receive values from a running XLA computation.
  }];

  let arguments = (ins