will be transformed into:

```mlir
func @my_fn(%arg0: tensor<i32>, %arg1: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  %identity = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>
  %identity_n:2 = "tf.IdentityN"(%arg1, %identity) : (tensor<i32>, tensor<i32>) -> (tensor<i32>, tensor<i32>)
  return %identity, %identity_n#0 : tensor<i32>, tensor<i32>
}
```
### `-tf-executor-tpu-v1-island-coarsening`

  TFE_TensorHandle* m = TestMatrixTensorHandle(ctx);
  TFE_Op* identity = TFE_NewOp(ctx, "Identity", status);
  TFE_TensorHandle* retvals[1];
  int num_retvals = 1;
  for (auto s : state) {
    TFE_OpReset(identity, "Identity", nullptr, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
    TFE_OpAddInput(identity, m, status);
    CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);

  }
};

// Replaces the Identity op with its input in either of the following scenarios
// : 1) The Identity op's input and output have same types/shapes. 2) The result
// of Identity op is only used by TF ops.
struct RemoveIdentity : public OpRewritePattern<TF::IdentityOp> {
  using OpRewritePattern<TF::IdentityOp>::OpRewritePattern;

  LogicalResult matchAndRewrite(TF::IdentityOp identity,

    -> (!tf_res, !tf_res, tensor<f32>) {
    // CHECK: "tf.Identity"
  %graph:3 = tf_executor.graph {
    // CHECK: {{.*}}, [[ctrl1:%.*]] = tf_executor.island wraps "tf.Identity"
    // CHECK: {{.*}}, [[ctrl2:%.*]] = tf_executor.island wraps "tf.Identity"
    // CHECK: "tf.Identity"
    %key, %key_control = tf_executor.island wraps "tf.Const"() {value = dense<"">: !tf_str} : () -> !tf_str

    %0 = "tf.Cast"(%arg0) {Truncate = false} : (tensor<1x3x4x3xi8>) -> tensor<1x3x4x3xi32>
    %1 = "tf.Sub"(%0, %arg4) : (tensor<1x3x4x3xi32>, tensor<i32>) -> tensor<1x3x4x3xi32>
    %identity = "tf.Identity"(%arg1) : (tensor<2x3x3x2xi8>) -> tensor<2x3x3x2xi8>
    %2 = "tf.Cast"(%identity) {Truncate = false} : (tensor<2x3x3x2xi8>) -> tensor<2x3x3x2xi32>
    %3 = "tf.Sub"(%2, %arg6) : (tensor<2x3x3x2xi32>, tensor<i32>) -> tensor<2x3x3x2xi32>

  OutputList outputs;
  CreateSwitchN(root.WithOpName("switchn"), value, constant_7, 3, &outputs);

  Output id_0 = ops::Identity(root.WithOpName("id_0"), outputs[0]);
  Output id_1 = ops::Identity(root.WithOpName("id_1"), outputs[1]);
  Output id_2 = ops::Identity(root.WithOpName("id_2"), outputs[2]);

  FixupSourceAndSinkEdges(root.graph());

  PredicateMapTy predicate_map;

// CHECK: return %cst : tensor<i32>
}

func.func @identity(%arg0: tensor<10xi32>, %arg1: tensor<20xi32>, %arg2: tensor<30xi32>) -> (tensor<10xi32>, tensor<20xi32>, tensor<30xi32>, tensor<*xi32>) {
  %0 = "tf.Identity"(%arg0) : (tensor<10xi32>) -> tensor<10xi32>
  %1:2 = "tf.IdentityN"(%arg1,%arg2) : (tensor<20xi32>, tensor<30xi32>) -> (tensor<20xi32>, tensor<30xi32>)
  %2 = "tf.Identity"(%arg0) : (tensor<10xi32>) -> tensor<*xi32>

  %outputs_32 =  "tf.AddV2"(%arg0, %outputs_6) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<*xi32>
  %outputs_34 =  "tf.Identity"(%outputs_32) {device = ""} : (tensor<*xi32>) -> tensor<*xi32>
  %outputs_36 =  "tf.Identity"(%arg1) {device = ""} : (tensor<i32>) -> tensor<*xi32>
  %outputs_38 =  "tf.Mul"(%outputs_16, %arg5) {device = ""} : (tensor<*xf32>, tensor<?xf32>) -> tensor<*xf32>

  %6 = "tf.Identity"(%3) {_xla_compile_device_type = "TPU", _replication_info = "a"} : (tensor<f32>) -> tensor<f32>
  %7 = "tf.Identity"(%4) {_xla_compile_device_type = "TPU", _replication_info = "b"} : (tensor<f32>) -> tensor<f32>
  %8 = "tf.Identity"(%5) {_xla_compile_device_type = "TPU", _replication_info = "c"} : (tensor<f32>) -> tensor<f32>

            "Identity", "IdentityN", "Relu", "Relu6", "ReluGrad", "Relu6Grad",
            "LeakyReluGrad", "Elu", "EluGrad", "Selu", "SeluGrad", "Select",
            "SelectV2", "Transpose", "ConjugateTranspose",
            "_UnaryOpsComposition", "CollectiveReduceV2",
            "CollectiveAssignGroupV2",
            // The following 5 operations are converted to identity