namespace tac {

// Interface name here is the "hook" between the CallOp and FuncOps.
// Take the following example:
//
// call @func_1_CPU {tac.interface_name = "func_1"}
//
// "func_1" is the interface name where "func_1_cpu" is the real implementation
// we can have multiple FuncOps like "func_1_cpu" and "func_1_gpu" and they
// both implement "func_1".
//
// The attribute on the FuncOp means what it actually implements while the

func.func @func_0_GPU(%arg0: tensor<10x10x10xf32>, %arg1: tensor<f32>) -> tensor<10x10x10xf32> attributes {tac.device = "GPU", tac.interface_name = "func_0"} {
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU", tac.device = "GPU"} : (tensor<10x10x10xf32>, tensor<f32>) -> tensor<10x10x10xf32>
  func.return %0 : tensor<10x10x10xf32>
}

// -----

// CHECK: tac.cost = 2.000000e+03

func.func @func_0_CPU(%arg0: tensor<10x10x10xf32>, %arg1: tensor<10xf32>) -> tensor<10x10x10xf32> attributes {tac.device = "CPU", tac.interface_name = "func_0"} {
  // CHECK: tac.cost = 1.000000e+03
  %0 = "tfl.add"(%arg0, %arg1) {fused_activation_function = "RELU", tac.device = "CPU"} : (tensor<10x10x10xf32>, tensor<10xf32>) -> tensor<10x10x10xf32>
  func.return %0 : tensor<10x10x10xf32>
}

// -----