func.func @identity_terminator(%arg0: tensor<i32>) -> (tensor<*xi32>, tensor<i32>) {
  // CHECK: %[[IDENTITY:.*]] = "tf.Identity"
  %0 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<*xi32>
  // CHECK-NOT: "tf.Identity"
  %1 = "tf.Identity"(%arg0) : (tensor<i32>) -> tensor<i32>
  // CHECK: return %[[IDENTITY]], %[[ARG0]]
  func.return %0, %1 : tensor<*xi32>, tensor<i32>
}

// CHECK-LABEL: func @xla_sharding

func.func @while_main(%arg0: tensor<?x256x256xf32>) -> (tensor<i32>, tensor<256x256xf32>, tensor<?x256x256xf32>) attributes {tf.entry_function = {inputs = "input", outputs = "Identity,Identity_1,Identity_2"}} {
  %cst = arith.constant dense<1.000000e+00> : tensor<256x256xf32>
  %cst_0 = arith.constant dense<0> : tensor<i32>
  %cst_1 = arith.constant dense<-1> : tensor<i32>

    // H2D transfer kernels. So fold the tf.Identity op if:
    // * the identity op is placed on TPU, and
    // * the arg to the identity op is produced by a TPUExecuteOp.
    if (op_device && op_device.getValue().contains("TPU")) {
      return true;
    }

    Operation *def_op = arg.getDefiningOp();
    // If the arg to this identity op is the arg of a function, there's no
    // defining op.

                IdentityContext identityContext = createIdentityContextInternal(work, context);
                Identity identity = identityContext.getIdentity();
                operationContext.setResult(new Operation.Result() {
                    @Override
                    public Identity getIdentity() {
                        return identity;
                    }
                });
                return identityContext;
            },

    if (!all_of(variable_v2_op.getResult().getUsers(), [&variable_v2_op](
                                                           Operation *user) {
          if (!isa<IdentityOp>(user)) {
            variable_v2_op.emitOpError()
                << "expects all users to be 'tf.Identity', but got user "
                << user->getName();
            return false;
          }
          return true;
        })) {

	"net/netip"
	"reflect"
	"testing"
)

func getSANExtension(identites []Identity, t *testing.T) *pkix.Extension {
	ext, err := BuildSANExtension(identites)
	if err != nil {
		t.Errorf("A unexpected error has been encountered (error: %v)", err)
	}
	return ext
}

func TestBuildSubjectAltNameExtension(t *testing.T) {
	uriIdentity := Identity{Type: TypeURI, Value: []byte("spiffe://test.domain.com/ns/default/sa/default")}

  // CHECK-NOT: tf.Identity
  %5 = "tf.Identity"(%4) {T = f32, _output_shapes = ["tfshape$dim { size: 3 } dim { size: 3 }"], device = "/device:CPU:0"} : (tensor<3x3xf32>) -> tensor<3x3xf32>
  // CHECK-NOT: tf.IdentityN

Aditya Manthramurthy <******@****.***> 1714599073 -0700

//
// input   min cst       max cst          input   min cst       max cst
//  \       |             |                \       |             |
//   \  (tf.Identity) (tf.Identity)   =>    \  (tf.Identity) (tf.Identity)
//    \     |             |                  \     |             |
//       tf.FakeQuantWithMinMaxVars       tf.FakeQuantWithMinMaxVars
//                   |                                 |

// convert the output type to the next op. Here are the transformations:
//
// input   min cst       max cst              input
//  \       |             |                     |
//   \  (tf.Identity) (tf.Identity)   =>   quant.qcast
//    \     |             |                     |
//       tf.FakeQuantWithMinMaxVars        quant.dcast
//                   |                          |
//