compile {
            attributes.attribute(buildType, 'debug')
            outgoing {
                variants {
                    var1 {
                        artifact oneJar
                        attributes.attribute(flavor, 'one')
                    }
                    var2 {
                        artifact twoJar
                        attributes.attribute(flavor, 'two')
                    }
                }

  template <typename T>
  Var* CreateVariable(const string& name, const TensorShape& shape,
                      const gtl::ArraySlice<T> data) {
    Tensor* init_var_value = CreateDeviceTensor<T>(shape, data);
    Var* var = new Var(DataTypeToEnum<T>::v());
    *var->tensor() = *init_var_value;
    var->is_initialized = true;

    return var;
  }

func.func @init() attributes {tf_saved_model.exported_names = ["__tf_saved_model_session_initializer_init"]} {
  %var0 = "tf.VarHandleOp"() {container = "", shared_name = "var0"} : () -> tensor<!tf_type.resource<tensor<i1>>>
  %cond = "tf.ReadVariableOp"(%var0) {device = "/CPU:0"} : (tensor<!tf_type.resource<tensor<i1>>>) -> tensor<i1>

type DurationVar struct {
	Var
}

var (
	allVars = make(map[string]Var)
	mutex   sync.Mutex
)

// VarDescriptions returns a description of this process' environment variables, sorted by name.
func VarDescriptions() []Var {
	mutex.Lock()
	sorted := make([]Var, 0, len(allVars))
	for _, v := range allVars {
		sorted = append(sorted, v)
	}
	mutex.Unlock()

	sort.Slice(sorted, func(i, j int) bool {

    tf_executor.graph {
      %out, %ctl = tf_executor.island wraps "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xf32>>>
      %out_0, %ctl_0 = tf_executor.island wraps "tf.ReadVariableOp"(%out) : (tensor<!tf_type.resource<tensor<2xf32>>>) -> tensor<2xf32>
      %out_1, %ctl_1 = tf_executor.island wraps "tf.Const"() {value = dense<"var_0"> : tensor<1x!tf_type.string>} : () -> tensor<1x!tf_type.string>

module {
// CHECK-LABEL: @serving_default
  func.func @serving_default() -> (tensor<*xi32>) {
    // expected-remark@below {{device: "", container: "", shared_name: "var_0", is_potentially_written: false}}
    %0 = "tf.VarHandleOp"() {shared_name = "var_0"} : () -> tensor<!tf_type.resource<tensor<2xi32>>>
    %1 = "tf.BatchFunction"(%0) {
        f = @called_by_batch_func,
        operandSegmentSizes = array<i32: 1, 0>,

// Test case: Basic freezing.

module {
  // CHECK: func @main()
  func.func @main() -> tensor<0xf32> {
    %handle = "tf.VarHandleOp"() {container="", shared_name="var1", device = "/job:worker/replica:0/task:1/device:CPU:0"} : () -> tensor<!tf_type.resource<tensor<0xf32>>>
    %val = "tf.ReadVariableOp"(%handle) : (tensor<!tf_type.resource<tensor<0xf32>>>) -> tensor<0xf32>

        if (!(o instanceof TypeVariableTypeWrapper)) {
            return false;
        } else {
            TypeVariableTypeWrapper var2 = (TypeVariableTypeWrapper) o;
            return Objects.equal(this.getName(), var2.getName())
                && Arrays.equals(this.bounds, var2.bounds);
        }
    }

    @Override
    public int hashCode() {
        return hashCode;
    }

// Use of this source code is governed by a BSD-style
// license that can be found in the LICENSE file.

package main

import (
	"testshared/issue47837/a"
)

func main() {
	var vara a.ImplA
	a.TheFuncWithArgA(&vara)

        if (!(o instanceof WildcardTypeWrapper)) {
            return false;
        } else {
            WildcardTypeWrapper var2 = (WildcardTypeWrapper) o;
            return Arrays.equals(this.lowerBounds, var2.lowerBounds) && Arrays.equals(this.upperBounds, var2.upperBounds);
        }
    }

    @Override
    public int hashCode() {
        return hashCode;
    }

    @Override