return &nsMutex
}

// nsLock - provides primitives for locking critical namespace regions.
type nsLock struct {
	ref int32
	*lsync.LRWMutex
}

// nsLockMap - namespace lock map, provides primitives to Lock,
// Unlock, RLock and RUnlock.
type nsLockMap struct {
	// Indicates if namespace is part of a distributed setup.
	isDistErasure bool
	lockMap       map[string]*nsLock
	lockMapMutex  sync.Mutex

				prometheus.BuildFQName(s3Namespace, "errors", "total"),
				"Total number of s3 errors in current MinIO server instance",
				[]string{"api"}, nil),
			prometheus.CounterValue,
			float64(value),
			api,
		)
	}

	for api, value := range httpStats.TotalS3Canceled.APIStats {
		ch <- prometheus.MustNewConstMetric(
			prometheus.NewDesc(
				prometheus.BuildFQName(s3Namespace, "canceled", "total"),

		Namespace: namespace,
		Subsystem: replicationSubsystem,
		Name:      lastHourFailedBytes,
		Help:      "Total number of bytes failed at least once to replicate in the last hour",
		Type:      gaugeMetric,
	}
}

func getRepFailedOperationsLastHourMD(namespace MetricNamespace) MetricDescription {
	return MetricDescription{
		Namespace: namespace,
		Subsystem: replicationSubsystem,
		Name:      lastHourFailedCount,

{{ template "minio.fullname" . }}.{{ .Release.Namespace }}.{{ .Values.clusterDomain }}

To access MinIO from localhost, run the below commands:

  1. export POD_NAME=$(kubectl get pods --namespace {{ .Release.Namespace }} -l "release={{ .Release.Name }}" -o jsonpath="{.items[0].metadata.name}")

  2. kubectl port-forward $POD_NAME 9000 --namespace {{ .Release.Namespace }}

#include <utility>

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/status.h"

namespace tensorflow {
namespace tracing {
namespace graph {
GraphFunction::GraphFunction(FunctionDef fdef)
    : AbstractFunction(kGraph),
      func_record_(new FunctionRecord(std::move(fdef), {}, true)) {}
GraphFunction::~GraphFunction() {}

#include "tensorflow/c/tf_status_helper.h"
#include "tensorflow/c/tf_tensor.h"
#include "tensorflow/core/platform/tensor_float_32_utils.h"
#include "tensorflow/core/platform/test.h"

namespace tensorflow {
namespace gradients {
namespace internal {
namespace {

using tensorflow::TF_StatusPtr;

void CompareNumericalAndManualGradients(
    Model model, AbstractContext* ctx,

#define TENSORFLOW_C_EAGER_GRAPH_FUNCTION_H_

#include "tensorflow/c/eager/abstract_function.h"
#include "tensorflow/core/framework/function.h"
#include "tensorflow/core/platform/refcount.h"
namespace tensorflow {
namespace tracing {
namespace graph {
using tensorflow::AbstractFunction;
// Thin wrapper around a FunctionDef.
class GraphFunction : public AbstractFunction {
 public:
  explicit GraphFunction(FunctionDef fdef);

#define TENSORFLOW_C_EAGER_GRADIENT_CHECKER_H_

#include <memory>

#include "absl/types/span.h"
#include "tensorflow/c/eager/abstract_tensor_handle.h"
#include "tensorflow/c/eager/unified_api_testutil.h"

namespace tensorflow {
namespace gradients {

/* Returns numerical grad inside `dtheta_approx` given `forward` model and
 * parameter specified by `input_index`.
 *
 * I.e. if y = <output of the forward model> and w = inputs[input_index],

#ifndef TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_
#define TENSORFLOW_C_EAGER_GRADIENTS_INTERNAL_H_

#include "tensorflow/c/eager/gradients.h"

namespace tensorflow {
namespace gradients {
namespace internal {

// Helper functions which delegate to `AbstractOperation`, update
// the state of the ForwardOperation and call the tape as appropriate.

    }

    //
    // Infer modelVersion from namespace URI
    //
    void handleModelVersion(Model model) {
        String namespace = model.getDelegate().getNamespaceUri();
        if (model.getModelVersion() == null && namespace != null && namespace.startsWith(NAMESPACE_PREFIX)) {
            model.setModelVersion(namespace.substring(NAMESPACE_PREFIX.length()));
        }
    }

    //