// CHECK: size: 10

func.func @main() {
  tf_executor.graph {
    %0:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<10xi32>} : () -> tensor<10xi32>
    %1:2 = tf_executor.island wraps "tf.Const"() {dtype = "tfdtype$DT_INT32", value = dense<0> : tensor<i32>} : () -> tensor<i32>
    %2:2 = tf_executor.island wraps "tf.PlaceholderWithDefault"(%1#0) {type = i32} : (tensor<i32>) -> tensor<*xi32> loc("unranked")

    %0 = tf_executor.graph {
      %outputs, %control = tf_executor.island wraps "tf.Identity"(%arg0) {device = ""} : (tensor<2x3xi32>) -> tensor<2x3xi32>
      %outputs_0, %control_1 = tf_executor.island wraps "tf.XlaSharding"(%outputs) {_XlaSharding = "", device = "", sharding = "", unspecified_dims = []} : (tensor<2x3xi32>) -> tensor<2x3xi32>

// RUN: tf-opt %s -tf-executor-tpu-v1-island-inlining | FileCheck %s

// Check that the nested module is inlined and erased.

module {
// CHECK-LABEL: func @func0
  func.func @func0(%arg0: tensor<i1>) -> tensor<f32> {
    %0 = tf_executor.graph {
// CHECK-NOT: PartitionedCall
// CHECK: "tf.opA"

      return mlir::WalkResult::interrupt();
    }

    for (mlir::Operation& op : graph.GetBody()) {
      auto island = llvm::dyn_cast<mlir::tf_executor::IslandOp>(op);
      if (!island) continue;

      if (!island.WrapsSingleOp()) {
        island.emitError(kInvalidExecutorGraphMsg)
            << "tf_executor.island must perfectly wrap a single op";
        return mlir::WalkResult::interrupt();
      }
    }

  func.func @device_ordinal_attr_added_multiple_devices() {
    tf_executor.graph {
      %0 = tf_executor.island {
        "tf_device.launch"() ({
          %1 = "tf.opA"() : () -> tensor<!tf_type.string>

    %0 = tf_executor.graph {
      %outputs_0, %control_0 = tf_executor.island wraps "tf.VarHandleOp"() {container = "", shared_name = ""} : () -> tensor<!tf_type.resource<tensor<501000x128xf32>>>
      %outputs_1, %control_1 = tf_executor.island wraps "tf.Cast"(%outputs_0) {Truncate = false} : (tensor<!tf_type.resource<tensor<501000x128xf32>>>) -> tensor<*x!tf_type.resource>

		Married   bool
		Address
		Comment string `xml:",comment"`
	}

	v := &Person{Id: 13, FirstName: "John", LastName: "Doe", Age: 42}
	v.Comment = " Need more details. "
	v.Address = Address{"Hanga Roa", "Easter Island"}

	output, err := xml.MarshalIndent(v, "  ", "    ")
	if err != nil {
		fmt.Printf("error: %v\n", err)
	}

	os.Stdout.Write(output)
	// Output:
	//   <person id="13">
	//       <name>

Übergeben Sie der Funktion `*` als ersten Parameter.

// tf_executor.island {_parallel_execution_ids=r0:0,p0:0} wraps "tf.OpC"
// tf_executor.island {_parallel_execution_ids=r0:0,p0:1} wraps "tf.OpD"
// tf_executor.island {_parallel_execution_ids=r0:1} wraps "tf.OpB"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:0} wraps "tf.OpC"
// tf_executor.island {_parallel_execution_ids=r0:1,p0:1} wraps "tf.OpD"
//
// "tf.OpA" will not have `_parallel_execution_ids` attr,

 * See the License for the specific language governing permissions and
 * limitations under the License.
 */

package org.gradle.kotlin.dsl.execution

import org.jetbrains.kotlin.lexer.KtTokens.ANDAND
import org.jetbrains.kotlin.lexer.KtTokens.ARROW
import org.jetbrains.kotlin.lexer.KtTokens.AT
import org.jetbrains.kotlin.lexer.KtTokens.CLASS_KEYWORD
import org.jetbrains.kotlin.lexer.KtTokens.COLON