```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>
    }
    ```
  }];

					graphNode, ok := ctx.gc.dependencyGraphBuilder.uidToNode.Read(n.identity.UID)
					if !ok {
						ctx.t.Errorf("%s: no node in graph with uid=%s", n.identity.UID, n.identity.UID)
						continue
					}
					if graphNode.identity != n.identity {
						ctx.t.Errorf("%s: expected identity %v, got %v", n.identity.UID, n.identity, graphNode.identity)
					}
					if graphNode.virtual != n.virtual {

    }
  }

  public void testTransform_rejectionPropagatesToOutput() throws Exception {
    SettableFuture<Foo> input = SettableFuture.create();
    Function<Foo, Foo> identity = identity();
    ListenableFuture<Foo> transformed = transform(input, identity, REJECTING_EXECUTOR);
    input.set(new Foo());
    try {
      getDone(transformed);
      fail();
    } catch (ExecutionException expected) {

    }
  }

  public void testTransform_rejectionPropagatesToOutput() throws Exception {
    SettableFuture<Foo> input = SettableFuture.create();
    Function<Foo, Foo> identity = identity();
    ListenableFuture<Foo> transformed = transform(input, identity, REJECTING_EXECUTOR);
    input.set(new Foo());
    try {
      getDone(transformed);
      fail();
    } catch (ExecutionException expected) {

      %12 = "tf.Identity"(%11) {device = ""} : (tensor<?xf32>) -> tensor<?xf32>
      %13 = "tf.AddV2"(%arg1, %4) {device = ""} : (tensor<i32>, tensor<i32>) -> tensor<i32>
      %14 = "tf.Identity"(%13) {device = ""} : (tensor<i32>) -> tensor<i32>
      %15 = "tf.Identity"(%arg2) {device = ""} : (tensor<i32>) -> tensor<i32>

        .header("Accept-Encoding", "identity")
        .build()
    val response1 = client.newCall(request).execute()
    assertThat(response1.body.string()).isEqualTo("A")
    val request1 =
      Request.Builder()
        .url(url)
        .header("Accept-Language", "fr-CA")
        .header("Accept-Charset", "UTF-8")
        .header("Accept-Encoding", "identity")
        .build()

  while (!worklist.empty()) {
    mlir::Operation* const use = worklist.pop_back_val();

    // Follow the `CastOp`/`IdentityOp`'s users to handle the `RestoreV2` ->
    // (optionally `IdentityOp`) -> `CastOp` `AssignVariableOp` case.
    if (llvm::isa<TF::CastOp, TF::IdentityOp>(use)) {
      llvm::append_range(worklist, use->getUsers());
      continue;
    }

  %0 = "tf.AddV2"(%arg0, %arg1) {device = ""} : (tensor<4x4xf32>, tensor<4x4xf32>) -> tensor<*xf32>
  %1 = "tf.Identity"(%0) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>
  %2 = "tf.Mul"(%0, %arg2) {device = ""} : (tensor<*xf32>, tensor<4x4xf32>) -> tensor<*xf32>
  %3 = "tf.Identity"(%2) {device = ""} : (tensor<*xf32>) -> tensor<*xf32>
  func.return %1, %3 : tensor<*xf32>, tensor<*xf32>
}

#include "tensorflow/compiler/mlir/tensorflow/utils/side_effect_analysis_util.h"

namespace mlir {
namespace TF {

namespace {
// Returns the equivalent Value skipping through identity nodes.
Value LookThroughIdentity(Value result) {
  while (isa_and_nonnull<IdentityOp, IdentityNOp>(result.getDefiningOp())) {
    auto op_result = result.cast<OpResult>();
    result = op_result.getOwner()->getOperand(op_result.getResultNumber());
  }

          input_tensor, min=-0.1, max=0.2, num_bits=8, narrow_range=False
      )
      sqrt = math_ops.sqrt(q_input, name='sqrt')
      identity = array_ops.identity(sqrt, name='output')

      input_map = {'input': input_tensor}
      output_map = {'sqrt': identity}
      signature = signature_def_utils_impl.predict_signature_def(
          inputs=input_map, outputs=output_map
      )