import static org.testng.Assert.*;

public class ParameterizedTest {

    @Test(dataProvider = "1")
	public void p1(String var1, String var2) {
        System.out.println("var1 is: " + var1);
        System.err.println("var2 is: " + var2);
       	assertEquals(var1, "1");
	}

	@DataProvider(name = "1")
	public Object[][] provider1() {
		return new Object[][] {
		   {"1", "2"},
		   {"3", "4"}

// CHECK-NEXT:  "tf.AssignVariableOp"([[VAR]], [[RES_1]])
// CHECK:       "tf.Yield"([[RES_3]], [[RES_4]])
func.func @readvariableop_is_not_hoisted_if_not_readonly(%arg0: tensor<i32>, %arg1: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  %cst_0 = "tf.Const"() { value = dense<1> : tensor<i32> } : () -> tensor<i32>

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

        '''
        file('src/main/java/org/gradle/test/Main.java') << '''
        package org.gradle.test;

        class Main {
            public static void main(String[] args) {
                if (!"value1".equals(System.getProperty("var1"))) {
                    throw new RuntimeException("Expected system property not specified (var1)");
                }

TEST_F(PjRtExecutionUtilTest, PreparePjRtExecutableArgumentsVariableInputs) {
  std::vector<VariableInfo> variables;
  Var* var1 = CreateVariable<int32>("v1", TensorShape({1, 2}), {1, 2});
  variables.emplace_back(3, "v1", var1);
  Var* var2 = CreateVariable<int32>("v2", TensorShape({1, 2}), {3, 4});
  variables.emplace_back(4, "v2", var2);

  std::vector<const Tensor*> inputs;

        compile {
            outgoing {
                variants {
                    var1 {
                        artifact file('a1.jar')
                        attributes.attribute(buildType, 'profile')
                        attributes.attribute(flavor, 'bland')
                    }
                    var2 {
                        artifact file('a2.jar')

    loop body inine):

    ```mlir
      %var0 = ...
      %var1 = ...
      tf.while (..., %var0, %var1) {
        tf_device.replicate ([%var0, %var1] as %rvar) {
          %compile:2 = "tf._TPUCompileMlir"()
          tf.TPUExecuteAndUpdateVariablesOp(%rvar, compile#1)
        }
      }
    ```

    This pass will transform it into

    ```mlir
      %var0 = ...
      %var1 = ...
      %state_var0 = ...

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 {

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>

`,
		},
		{
			desc:     "overwrite",
			baseYAML: testTreeYAML,
			path:     "a.b.c",
			value:    "val2",
			want: `
a:
  b:
    c: val2
    list1:
    - i1: val1
    - i2: val2
    - i3a: key1
      i3b:
        list2:
        - i1: val1
        - i2: val2
        - i3a: key1
          i3b:
            i1: va11
`,
		},
		{
			desc:     "partial create",