// CHECK-NEXT: "tf.Const"() <{value = dense<> : tensor<0xi32>}>
  %elem_shape = "tf.Const"() {value = dense<> : tensor<0xi32>} : () -> tensor<0xi32>
  // CHECK-NEXT: %[[NUM:.*]] = "tf.Const"() <{value = dense<10> : tensor<i32>}>
  %num = "tf.Const"() {value = dense<10> : tensor<i32>} : () -> tensor<i32>
  // CHECK-NEXT: %[[ZERO_SCALAR:.*]] = "tf.Const"() <{value = dense<0> : tensor<i32>}> : () -> tensor<i32>

  %230 = "tf.Reshape"(%229, %9) {device = ""} : (tensor<i32>, tensor<0xi32>) -> tensor<i32>
  %231 = "tf.Pack"(%7, %230) {axis = 0 : i64, device = ""} : (tensor<i32>, tensor<i32>) -> tensor<2xi32>
  %232 = "tf.Mul"(%230, %8) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
  %233 = "tf.Pack"(%232) {axis = 0 : i64, device = ""} : (tensor<i32>) -> tensor<1xi32>

	use(a1k[ui16])
	use(a100k[ui16]) // ERROR "index bounds check elided"
	use(p1[ui16])
	use(p1k[ui16])
	use(p100k[ui16]) // ERROR "index bounds check elided"

	use(s[i32])
	use(a1[i32])
	use(a1k[i32])
	use(a100k[i32])
	use(p1[i32])
	use(p1k[i32])
	use(p100k[i32])

	use(s[ui32])
	use(a1[ui32])
	use(a1k[ui32])
	use(a100k[ui32])
	use(p1[ui32])
	use(p1k[ui32])
	use(p100k[ui32])

	use(s[i64])

    // CHECK: name: "fo.o"
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<1> : tensor<i32>} : () -> (tensor<i32>) loc("fo{o")
    // CHECK: name: "foo"
    %2:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<2> : tensor<i32>} : () -> (tensor<i32>) loc("foo@1")
    // CHECK: name: "ba.r"

  %0 = tf_executor.graph {
    %outputs, %control = tf_executor.island {
      %1 = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
      "tf.AssignVariableOp"(%arg0, %1) : (tensor<*x!tf_type.resource<tensor<i32>>>, tensor<i32>) -> ()
      tf_executor.yield %1 : tensor<i32>
    }
    tf_executor.fetch %outputs : tensor<i32>
  }
  func.return %0 : tensor<i32>

        tf_device.return %1 : tensor<i32>
      }) : () -> tensor<i32>

      return %0 : tensor<i32>
    }

    func.func @pcall_func_with_resources_0(%arg0: tensor<i32>, %arg1: tensor<!tf_type.resource>) -> tensor<i32> {
      return %arg0 : tensor<i32>
    }
    ```

  // expected-error @+1 {{argument count mismatch: 'args' has 1 arguments, but '@pcall_func_2' expects 2}}
  %0 = "tf.PartitionedCall"(%arg0) {config = "", config_proto = "", executor_type = "", f = @pcall_func_2} : (tensor<i32>) -> (tensor<i32>)
  func.return %0 : tensor<i32>
}

func.func @pcall_func_2(%arg0: tensor<i32>, %arg1: tensor<i32>) -> tensor<i32> {
  func.return %arg0 : tensor<i32>
}

// -----

    "tfl.yield"(%13, %arg2, %11, %arg4, %12) : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<!tf_type.resource>, tensor<f32>) -> ()
  }) {is_stateless = false} : (tensor<i32>, tensor<i32>, tensor<i32>, tensor<!tf_type.resource>, tensor<f32>) -> (tensor<i32>, tensor<i32>, tensor<i32>, tensor<!tf_type.resource>, tensor<f32>)
  func.return %5#3 : tensor<!tf_type.resource>

// CHECK: "tfl.while"

  %us = tfrt.constant.i32 1000
  %ch0 = "tfrt_test.blocking.usleep"(%us) : (i32) -> (!tfrt.chain)

  %ch1 = tfrt.merge.chains %ch, %ch0 : !tfrt.chain, !tfrt.chain

  %ch2 = tfrt_fallback_async.createop(%ch1) key(0) device("/CPU:0") "tf.MatMul"() {T = i32} num_args(2)

  %ch3, %result = tfrt_fallback_async.executeop.seq(%ch2) key(0) cost(100) device("/CPU:0") "tf.MatMul"(%a, %b) {T = i32}  : 1

      %cluster = "tf_device.cluster_func"(%arg0) {func = @_func} : (tensor<i32>) -> tensor<i32>
      return %cluster : tensor<i32>
    }

    func @_func(%arg0: tensor<i32>) -> tensor<i32> {
      %identity = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>
      return %identity : tensor<i32>
    }
    ```
  }];

  let constructor = "TFDevice::CreateClusterOutliningPass()";
}