for input_key in sample_1:
        self._assert_tensorlike_all_close(
            sess, sample_1[input_key], sample_2[input_key]
        )

  def test_not_implemented_saver(self):
    with self.assertRaisesRegex(
        NotImplementedError, '"save" is not implemented.'
    ):
      repr_dataset.RepresentativeDatasetSaver().save(representative_dataset={})

    flags: --quiet
    expected-output-file: sample1.out
},{
    executable: gradle
    args: -Psample2 compileJava printArtifacts
    flags: --quiet
    expected-output-file: sample2.out
},{
     executable: gradle
     args: -Psample3 compileJava printArtifacts
     flags: --quiet
     expected-output-file: sample3.out

repositories {
    mavenCentral()
}

if (project.hasProperty('sample1')) {
// tag::exclude-transitive-dependencies-1[]
dependencies {
    implementation('commons-beanutils:commons-beanutils:1.9.4') {
        exclude group: 'commons-collections', module: 'commons-collections'
    }
}
// end::exclude-transitive-dependencies-1[]
} else if (project.hasProperty('sample2')) {
// tag::exclude-transitive-dependencies-2[]
    dependencies {

        outputContains("org.gradle:sample:1.0 (default capability)")
    }

    def "attribute combinations can be repeated if capabilities differ without a warning"() {
        given:
        settingsFile << "rootProject.name = 'sample'"
        buildFile << """
            plugins {

repositories {
    mavenCentral()
}

if (project.hasProperty("sample1")) {
// tag::exclude-transitive-dependencies-1[]
dependencies {
    implementation("commons-beanutils:commons-beanutils:1.9.4") {
        exclude(group = "commons-collections", module = "commons-collections")
    }
}
// end::exclude-transitive-dependencies-1[]
} else if (project.hasProperty("sample2")) {
// tag::exclude-transitive-dependencies-2[]
dependencies {

import (
	_ "runtime" // depends on the runtime via a linkname'd function
	"unsafe"
)

// Sample captures a single metric sample.
type Sample struct {
	// Name is the name of the metric sampled.
	//
	// It must correspond to a name in one of the metric descriptions
	// returned by All.
	Name string

	// Value is the value of the metric sample.
	Value Value
}

// Implemented in the runtime.

  TF_DeleteBuffer(result1);
  TFE_MonitoringDeleteSampler1(sampler1);

  auto* sampler2 = TFE_MonitoringNewSampler2("test/sampler2", buckets, status,
                                             "test", "label1", "label2");
  CHECK_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  auto* cell2 = TFE_MonitoringGetCellSampler2(sampler2, "foo", "bar");
  TFE_MonitoringSamplerCellAdd(cell2, 2.0);

  }

  function processSampleEl(sampleEl, prefLangId) {
    var codeEl = sampleEl.querySelector("code[data-lang]");
    if (codeEl != null) {
      sampleEl.setAttribute("data-lang", codeEl.getAttribute("data-lang"));
      if (codeEl.getAttribute("data-lang") !== prefLangId) {
        sampleEl.classList.add("hidden");
      } else {
        sampleEl.classList.remove("hidden");
      }
    }
  }

// (indicating that the batch contains only CPU samples) and adds each
// sample contained therein to the provided samples list.
func addCPUSamples(samples []cpuSample, b batch) ([]cpuSample, error) {
	if !b.isCPUSamplesBatch() {
		return nil, fmt.Errorf("internal error: addCPUSamples called on non-CPU-sample batch")
	}
	r := bytes.NewReader(b.data)

	}

	// provider.sampler > telemetry.RandomSamplingPercentage > defaultConfig.tracing.sampling > PILOT_TRACE_SAMPLING
	var sampling float64
	if useCustomSampler {
		// If the TracingProvider has a custom sampler (OTel Sampler)
		// the sampling percentage is set to 100% so all spans arrive at the sampler for its decision.
		sampling = 100
	} else if spec.RandomSamplingPercentage != nil {