// Examples of units might be "seconds", "bytes", "bytes/second", "cpu-seconds",
	// "byte*cpu-seconds", and "bytes/second/second".
	//
	// For histograms, multiple units may apply. For instance, the units of the buckets and
	// the count. By convention, for histograms, the units of the count are always "samples"
	// with the type of sample evident by the metric's name, while the unit in the name
	// specifies the buckets' unit.
	//

// CKECK-SAME: <{calibration_method = 5 : i32, id = "0", num_bins = 32 : i32, max_percentile = 0.000000e+00 : f32, min_percentile = 0.000000e+00 : f32}> : (tensor<1x3x4x3xf32>) -> (tensor<1x3x4x3xf32>, tensor<f32>, tensor<f32>, tensor<512xi64>)
// CHECK: %[[CUSTOM_AGGREGATOR_1:.*]], %[[MIN_1:.*]], %[[MAX_1:.*]], %[[HISTOGRAM_1:.*]] = "tf.CustomAggregator"

// dataUsageHash is the hash type used.
type dataUsageHash string

// sizeHistogramV1 is size histogram V1, which has fewer intervals esp. between
// 1024B and 1MiB.
type sizeHistogramV1 [dataUsageBucketLenV1]uint64

// sizeHistogram is a size histogram.
type sizeHistogram [dataUsageBucketLen]uint64

// versionsHistogram is a histogram of number of versions in an object.
type versionsHistogram [dataUsageVersionLen]uint64

	// GaugeMT - represents a gauge metric.
	GaugeMT
	// HistogramMT - represents a histogram metric.
	HistogramMT
	// rangeL - represents a range label.
	rangeL = "range"
)

func (mt MetricType) String() string {
	switch mt {
	case CounterMT:
		return "counter"
	case GaugeMT:
		return "gauge"
	case HistogramMT:
		return "histogram"
	default:
		return "*unknown*"
	}
}

  TF_Buffer* result1 = TF_NewBuffer();
  TFE_MonitoringSamplerCellValue(cell1, result1);
  tensorflow::HistogramProto histogram1;
  EXPECT_TRUE(histogram1.ParseFromString(
      {reinterpret_cast<const char*>(result1->data), result1->length}));
  EXPECT_EQ(histogram1.sum(), 3.0);
  TF_DeleteBuffer(result1);
  TFE_MonitoringDeleteSampler1(sampler1);

// HISTOGRAM-MSE-BRUTEFORCE-CHECK-NEXT:  return [[res]] : tensor<*xf32>

// HISTOGRAM-MSE-BRUTEFORCE-CHECK: func @no_composite_func
// HISTOGRAM-MSE-BRUTEFORCE-CHECK-NEXT:  "tf.AddV2"
// HISTOGRAM-MSE-BRUTEFORCE-CHECK-NEXT:  return

// HISTOGRAM-MSE-BRUTEFORCE-CHECK: func @composite_conv2d_with_relu6_fn
// HISTOGRAM-MSE-BRUTEFORCE-CHECK-NEXT:  "tf.Conv2D"
// HISTOGRAM-MSE-BRUTEFORCE-CHECK-NEXT:  "tf.Relu6"

TEST(CalibrationStatisticsCollectorTest, SimpleMinMax) {
  auto collector = CalibrationStatisticsCollectorMinMax();

  collector.Collect(
      /*min=*/1.0f, /*max=*/10.f, /*histogram=*/{});
  collector.Collect(
      /*min=*/-5.0f, /*max=*/5.f, /*histogram=*/{});

  std::optional<CalibrationStatistics> statistics = collector.GetStatistics();

  EXPECT_TRUE(statistics.has_value());

import org.opensearch.search.aggregations.AggregationBuilders;
import org.opensearch.search.aggregations.BucketOrder;
import org.opensearch.search.aggregations.bucket.histogram.DateHistogramInterval;
import org.opensearch.search.aggregations.bucket.histogram.Histogram;
import org.opensearch.search.aggregations.bucket.terms.Terms;
import org.opensearch.search.aggregations.metrics.Avg;
import org.opensearch.search.aggregations.metrics.Cardinality;

				return
			}
		case "Histogram":
			var zb0004 uint32
			zb0004, bts, err = msgp.ReadMapHeaderBytes(bts)
			if err != nil {
				err = msgp.WrapError(err, "Histogram")
				return
			}
			if z.Histogram == nil {
				z.Histogram = make(map[string]uint64, zb0004)
			} else if len(z.Histogram) > 0 {
				for key := range z.Histogram {
					delete(z.Histogram, key)
				}
			}
			for zb0004 > 0 {

TEST_F(CompileTFGraphTest, RecordsStreamzForMlirFallback) {
  CellReader<Histogram> compilation_time(kCompilationTimeStreamzName);

  MlirToHloArgs mlir_to_hlo_args = CreateTestMlirToHloArgs();

  TF_EXPECT_OK(CompileWithComputation(mlir_to_hlo_args).status());

  Histogram histogram = compilation_time.Delta("graph_old_bridge_has_mlir");

  EXPECT_EQ(histogram.num(), 1);
}