Namespace: bucketMetricNamespace,
		Subsystem: usageSubsystem,
		Name:      totalBytes,
		Help:      "Total bucket size in bytes",
		Type:      gaugeMetric,
	}
}

func getClusterUsageTotalBytesMD() MetricDescription {
	return MetricDescription{
		Namespace: clusterMetricNamespace,
		Subsystem: usageSubsystem,
		Name:      totalBytes,
		Help:      "Total cluster usage in bytes",
		Type:      gaugeMetric,
	}

    }
  }

  if (allocate_xla_tensors) {
    Tensor output_tensor;
    TF_RETURN_IF_ERROR(
        ctx->allocate_temp(output_dtype, output_shape, &output_tensor));
    if (output_tensor.TotalBytes() > 0) {
      XlaTensor* xla_tensor = XlaTensor::FromTensor(&output_tensor);
      TF_RET_CHECK(xla_tensor);
      xla_tensor->set_shaped_buffer(output.TakeSubTree({output_num}));
      if (use_multiple_streams) {

}

ElementsAttr ConvertTensorOfCustomFloatType(const Tensor& tensor,
                                            RankedTensorType type) {
  auto buffer =
      llvm::ArrayRef(static_cast<char*>(tensor.data()), tensor.TotalBytes());
  return mlir::DenseElementsAttr::getFromRawBuffer(type, buffer);
}

absl::StatusOr<ElementsAttr> ConvertStringTensor(const Tensor& input_tensor,
                                                 ShapedType type) {

			cpu.total = samples[i].Value.Float64()
		case "/cpu/classes/user:cpu-seconds":
			cpu.user = samples[i].Value.Float64()
		case "/memory/classes/total:bytes":
			totalVirtual.got = samples[i].Value.Uint64()
		case "/memory/classes/heap/objects:bytes":
			objects.totalBytes = samples[i].Value.Uint64()
		case "/gc/heap/objects:objects":
			objects.total = samples[i].Value.Uint64()
		case "/gc/heap/allocs:bytes":

			}
		}
	}()

	b.SetBytes(totalBytes)
	clientConfig := testConfig.Clone()
	clientConfig.CipherSuites = nil // the defaults may prefer faster ciphers
	clientConfig.DynamicRecordSizingDisabled = dynamicRecordSizingDisabled
	clientConfig.MaxVersion = version

	buf := make([]byte, bufsize)
	chunks := int(math.Ceil(float64(totalBytes) / float64(len(buf))))
	for i := 0; i < N; i++ {

    return 0;
  }
  const tensorflow::Tensor* tensor;
  status->status = handle->Tensor(&tensor);
  if (!status->status.ok()) {
    return 0;
  }
  return tensor->TotalBytes();
}

TFE_Op* TFE_NewOp(TFE_Context* ctx, const char* op_or_function_name,
                  TF_Status* status) {
  tensorflow::ImmediateExecutionOperation* new_op =

package cmd

import (
	"context"
	"time"
)

const (
	usageSinceLastUpdateSeconds   = "since_last_update_seconds"
	usageTotalBytes               = "total_bytes"
	usageObjectsCount             = "count"
	usageVersionsCount            = "versions_count"
	usageDeleteMarkersCount       = "delete_markers_count"
	usageBucketsCount             = "buckets_count"

        "Unsupported byte_offset (", dl_tensor->byte_offset,
        ") from DLPack, must be zero");
    return nullptr;
  }

  size_t total_bytes = dl_tensor->dtype.bits / 8;
  for (int i = 0; i < num_dims; i++) {
    total_bytes *= dims[i];
  }

  if (dl_tensor->strides != nullptr &&
      !IsValidStrideCompactRowMajorData(dl_tensor->shape, dl_tensor->strides,

)

var allDriveLabels = []string{driveL, poolIndexL, setIndexL, driveIndexL}

const (
	driveUsedBytes               = "used_bytes"
	driveFreeBytes               = "free_bytes"
	driveTotalBytes              = "total_bytes"
	driveUsedInodes              = "used_inodes"
	driveFreeInodes              = "free_inodes"
	driveTotalInodes             = "total_inodes"
	driveTimeoutErrorsTotal      = "timeout_errors_total"

			deps: makeStatDepSet(gcStatsDep),
			compute: func(in *statAggregate, out *metricValue) {
				out.kind = metricKindUint64
				out.scalar = in.gcStats.stackScan
			},
		},
		"/gc/scan/total:bytes": {
			deps: makeStatDepSet(gcStatsDep),
			compute: func(in *statAggregate, out *metricValue) {
				out.kind = metricKindUint64
				out.scalar = in.gcStats.totalScan
			},
		},