samples=samples.slice().sort(function(a,b){return a-b;});const low=Math.min.apply(null,samples);const high=Math.max.apply(null,samples);const newLow=0.5/samples.length;const newHigh=(samples.length-0.5)/samples.length;if(high-low===0.0){samples=Array.apply(null,new Array(samples.length)).map(function(){return 0.5;});return{normalized_samples:samples,scale:1.0};}...

  }

  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");
      }
    }
  }

        dataset_file_map
    ).load()
    self.assertCountEqual(dataset_map.keys(), ['serving_default'])
    samples = dataset_map['serving_default']
    for sample in samples:
      self.assertCountEqual(sample.keys(), {'x'})
      self.assertAllEqual(sample['x'], np.array([1, 2]))

    self.assertLen(samples, num_samples)

  def test_tf_record_saver_when_signature_def_key_mismatch_raises_error(self):

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.

    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

	}
}

//
// Normal distribution tests
//

func generateNormalSamples(nsamples int, mean, stddev float64, seed int64) []float64 {
	r := New(NewSource(seed))
	samples := make([]float64, nsamples)
	for i := range samples {
		samples[i] = r.NormFloat64()*stddev + mean
	}
	return samples
}

	}
}

//
// Normal distribution tests
//

func generateNormalSamples(nsamples int, mean, stddev float64, seed uint64) []float64 {
	r := New(NewPCG(seed, seed))
	samples := make([]float64, nsamples)
	for i := range samples {
		samples[i] = r.NormFloat64()*stddev + mean
	}
	return samples
}

                });
        emlExtractor = container.getComponent("emlExtractor");
    }

    public void test_getText() throws IOException {
        try (final InputStream in = ResourceUtil.getResourceAsStream("extractor/eml/sample1.eml")) {
            ExtractData data = emlExtractor.getText(in, null);
            final String content = data.getContent();
            logger.info(content);
            assertTrue(content.contains("プレイステーション"));

        readmeTemplates.convention(layout.projectDirectory.dir("src/samples/readme-templates"))
        target.convention(layout.buildDirectory.dir("generated-samples/$buildInitType" + if (modularizationOption.isMulti()) "-with-libraries" else ""))
        type = buildInitType
        modularization = modularizationOption
    }
    samples.publishedSamples.create(sampleName) {
        dsls = setOf(Dsl.GROOVY, Dsl.KOTLIN)

// (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)