// CHECK: [[PI_0:%.*]] = "tf.TPUPartitionedInputV2"([[ARG0]], [[ARG1]])
  %pi_0 = "tf.TPUPartitionedInputV2"(%arg0, %arg1) {device = "", partition_dims = []} : (tensor<!tf_type.resource<tensor<10x3xf32>>>, tensor<!tf_type.resource<tensor<10x3xf32>>>) -> tensor<!tf_type.resource<tensor<10x3xf32>>>
  // CHECK: [[PI_1:%.*]] = "tf.TPUPartitionedInputV2"([[ARG2]], [[ARG3]])

// -----

// CHECK-LABEL: call_op
func.func @call_op(%arg0: !tfr.tensor<T>, %arg1: !tfr.tensor_list<TL>, %arg2: i32) -> !tfr.tensor<K> {
  %0 = tfr.call @Foo(%arg0, %arg1, %arg2) : (!tfr.tensor<T>, !tfr.tensor_list<TL>, i32) -> !tfr.tensor<K>
  func.return %0 : !tfr.tensor<K>
}

// -----

// CHECK-LABEL: call_op_arg_attr(%arg0: i32) -> !tfr.tensor<K>
func.func @call_op_arg_attr(%arg0: i32) -> !tfr.tensor<K> {

  }

  func.func private @while_cond(%arg0: tensor<i32>, %arg1: tensor<i32>, %arg2: tensor<i32>, %arg3: tensor<1x1024xbf16>, %arg4: tensor<1024x1024xbf16>) -> tensor<i1>
  {
    %cst = "tf.Const"() {value = dense<1> : tensor<i32>} : () -> tensor<i32>
    %0 = "tf.Less"(%arg0, %cst) : (tensor<i32>, tensor<i32>) -> tensor<i1>
    func.return %0 : tensor<i1>

          %id0 = "tf.Identity"(%arg3) : (!tf_res_md_f32) -> !tf_res_md_f32
          "tf._Unknown_"(%id0) : (!tf_res_md_f32) -> ()
          %newvar = "tf._SomeOp"() : () -> !tf_res_f32
          %rep:2 = tf_device.replicate([%arg0, %arg1] as %arg30: !tf_res_f32,
                                       [%arg2, %arg3] as %arg31: !tf_res_md_f32,
                                       [%newvar, %arg4] as %arg32 : !tf_res_f32)

  // CHECK-LABEL: concatenate_and_composite
  // CHECK-SAME: %[[ARG0:.*]]: tensor<3x2xf32>
  // CHECK-SAME: %[[ARG1:.*]]: tensor<1x2xf32>
  // CHECK-SAME: %[[ARG2:.*]]: tensor<2x5xf32>
  func.func private @concatenate_and_composite(%arg0: tensor<3x2xf32>, %arg1: tensor<1x2xf32>, %arg2: tensor<2x5xf32>) -> tensor<4x5xf32> {

^bb0(%arg0: tensor<8xf32>, %arg3: tensor<f32>, %arg4: tensor<f32>):
  %1 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg3, %arg4) {num_bits = 5, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32>
  func.return %1 : tensor<8xf32>

// CHECK: %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
// CHECK: return %0 : tensor<8xf32>
}

		{name: "SUBshiftRLreg", argLength: 3, reg: gp31, asm: "SUB"}, // arg0 - arg1>>arg2, unsigned shift
		{name: "SUBshiftRAreg", argLength: 3, reg: gp31, asm: "SUB"}, // arg0 - arg1>>arg2, signed shift
		{name: "RSBshiftLLreg", argLength: 3, reg: gp31, asm: "RSB"}, // arg1<<arg2 - arg0
		{name: "RSBshiftRLreg", argLength: 3, reg: gp31, asm: "RSB"}, // arg1>>arg2 - arg0, unsigned shift

^bb0(%arg0: tensor<8xf32>, %arg3: tensor<f32>, %arg4: tensor<f32>):
  %1 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg3, %arg4) {num_bits = 3, narrow_range = false} : (tensor<8xf32>, tensor<f32>, tensor<f32>) -> tensor<8xf32>
  func.return %1 : tensor<8xf32>

// CHECK: %0 = "tf.FakeQuantWithMinMaxVars"(%arg0, %arg1, %arg2)
// CHECK: return %0 : tensor<8xf32>
}

  auto arg0 = ops::_Arg(scope.WithOpName("a_0_arg"), DT_INT32, 0);
  auto arg1 = ops::_Arg(scope.WithOpName("b_0_arg"), DT_FLOAT, 1);
  auto arg2 = ops::_Arg(scope.WithOpName("c_0_arg"), DT_INT32, 2);
  auto arg3 = ops::_Arg(scope.WithOpName("d_0_arg"), DT_FLOAT, 3);

  auto arg4 = ops::_Arg(scope.WithOpName("u_0_arg"), DT_RESOURCE, 4);
  auto arg5 = ops::_Arg(scope.WithOpName("v_0_arg"), DT_RESOURCE, 5);

func.func @func_with_sharding_inside_while_body(%arg0: tensor<i32>, %arg1: tensor<128x1024xf32>) -> (tensor<128x1024xf32>) {
  %cst = "tf.Const"() <{value = dense<0> : tensor<i32>}> {device = ""} : () -> tensor<i32>
  %0:2 = "tf.WhileRegion"(%cst, %arg1) <{is_stateless = false, parallel_iterations = 1 : i64}> ({
    ^bb0(%arg2: tensor<i32>, %arg3: tensor<128x1024xf32>):
      %1 = "tf.Less"(%arg2, %arg0) : (tensor<i32>, tensor<i32>) -> tensor<i1>