// CHECK:            %[[RECV_OUTPUT1:[0-9]*]] = "tf._XlaRecvAtHostV2"(%[[PROGRAM_OUTPUT]], %[[DEVICE_ORDINAL]])
    // CHECK:            %[[B_OUTPUT:[0-9]*]] = "tf.B"(%[[RECV_OUTPUT1]])
    // CHECK:            %[[RECV_OUTPUT2:[0-9]*]] = "tf._XlaRecvAtHostV2"(%[[PROGRAM_OUTPUT]], %[[DEVICE_ORDINAL]])
    // CHECK:            %[[D_OUTPUT:[0-9]*]] = "tf.D"(%[[RECV_OUTPUT2]])

        %0 = "tf._XlaRecvAtHostV2"(%arg0, %arg1) {_xla_has_host_transfer = true, key = "host_compute_channel_0_args"} : (tensor<!tf_type.string>, tensor<i64>) -> tensor<f32>
        // expected-remark@above {{ID: 0}}
        %const = "tf.Const"() { value = dense<1.0> : tensor<f32> } : () -> tensor<f32>
        // expected-remark@above {{ID: 1}}

          /*device_ordinal=*/builder.getI64IntegerAttr(0), device_type_attr),
      builder);
}

// Creates a tf._XlaRecvAtHost or tf._XlaRecvAtHostV2 op. If device ordinal is
// present, a tf._XlaRecvAtHostV2 op is created instead.
Operation* CreateRecvAtHostOp(OpBuilder& builder, Location loc,
                              TypeRange output_types, Value compilation_key,

  );

  TF_DerivedResultTypeListAttr Toutputs = TF_DerivedResultTypeListAttr<0>;
}

def TF__XlaRecvAtHostV2Op : TF_Op<"_XlaRecvAtHostV2", [DeclareOpInterfaceMethods<TF_GetResourceInstanceInterface>, TF_RecvSideEffect]> {
  let summary = [{
A placeholder op to receive values from a running XLA computation with support for a runtime device ordinal.
  }];