%1 = "tf.TPUCompileMlirAndExecute"(%0) {metadata = "metadata", mlir_module = "mlir_module", operandSegmentSizes = array<i32: 1, 0>, producer_name = "producer_name"} : (tensor<i32>) -> tensor<i32>
  func.return %1 : tensor<i32>
}

// -----

func.func @executeop_input(%arg0: tensor<i32>) -> (tensor<i32>, tensor<i32>) {
  // CHECK-NOT: tf_mlrt.executeop(

    constant_operand_indices is sorted in ascending order.
    $operands_with_static_shape are indices of operands that are tagged with a maximum static shape.
    $producer_name is a string describing the name of the framework that added support for running this portion of the model on TPUs.

    Example:

  %5 = "tf.TPUExecute"(%3#0, %1, %program#0) {_producer_name = "UNKNOWN", device = "/TPU:0"} : (tensor<1x1xf32>, tensor<1x1xf32>, tensor<3x!tf_type.string>) -> tensor<1x1xf32>
  %6 = "tf.TPUExecute"(%3#1, %1, %program#1) {_producer_name = "UNKNOWN", device = "/TPU:1"} : (tensor<1x1xf32>, tensor<1x1xf32>, tensor<3x!tf_type.string>) -> tensor<1x1xf32>

    constant_operand_indices is sorted in ascending order.
    $operands_with_static_shape are indices of operands that are tagged with a maximum static shape.
    $producer_name is a string describing the name of the framework that added support for running this portion of the model on TPUs.

    Example:

target computation.
'metadata' is a serialized TPUCompileMetadataProto describing the shapes and
types of the inputs to the computation, as well as a mapping onto the TPU pod
topology.
'producer_name' is a string describing the name of the framework that add support for running this portion of the model on TPUs.
  }];

  let arguments = (ins
    Variadic<TF_Tensor>:$args,

// tag::use-plugin[]
pluginManagement {
    repositories {
        maven {
// end::use-plugin[]
            val producerName: String? by settings
            val repoLocation = "../$producerName/build/repo"
// tag::use-plugin[]
            url = uri(repoLocation)
        }
    }
// end::use-plugin[]
// tag::use-legacy-plugin[]
    resolutionStrategy {
        eachPlugin {
            if (requested.id.namespace == "org.example") {

// tag::use-plugin[]
pluginManagement {
    repositories {
        maven {
// end::use-plugin[]
            def repoLocation = "../$producerName/build/repo"
// tag::use-plugin[]
            url = uri(repoLocation)
        }
    }
// end::use-plugin[]
// tag::use-legacy-plugin[]
    resolutionStrategy {
        eachPlugin {
            if (requested.id.namespace == 'org.example') {

func.func @serving_default(%arg0: tensor<1x3xf32>) -> (tensor<1x3xf32>) {
  %outputs  =  "tf.TPUCompilationResult"() {_tpu_compilation_status = "cluster", device = ""} : () -> tensor<!tf_type.string>

        assert target.buildArgumentsString == '-Porg.gradle.internal.xcode.bridge.ACTION="${ACTION}" -Porg.gradle.internal.xcode.bridge.PRODUCT_NAME="${PRODUCT_NAME}" -Porg.gradle.internal.xcode.bridge.CONFIGURATION="${CONFIGURATION}" -Porg.gradle.internal.xcode.bridge.BUILT_PRODUCTS_DIR="${BUILT_PRODUCTS_DIR}" :_xcode__${ACTION}_${PRODUCT_NAME}_${CONFIGURATION}'

        def expectedArchitecture = archName == 'aarch64' ? 'arm64e' : 'x86_64'

        expect:
        XcodePropertyAdapter.adapterCommandLine == [
                '-Porg.gradle.internal.xcode.bridge.ACTION="${ACTION}"',
                '-Porg.gradle.internal.xcode.bridge.PRODUCT_NAME="${PRODUCT_NAME}"',
                '-Porg.gradle.internal.xcode.bridge.CONFIGURATION="${CONFIGURATION}"',
                '-Porg.gradle.internal.xcode.bridge.BUILT_PRODUCTS_DIR="${BUILT_PRODUCTS_DIR}"',
        ]
    }