* **Bilgisayar görüsü**: bir görüntü milyonlarca pikselden oluşur, her pikselin 3 değeri / rengi vardır, bu pikseller üzerinde aynı anda bir şeyler hesaplamayı gerektiren işleme.
* **Makine Öğrenimi**: Çok sayıda "matris" ve "vektör" çarpımı gerektirir. Sayıları olan ve hepsini aynı anda çarpan büyük bir elektronik tablo düşünün.

	}

	key := getResourceKey(name, labels)
	metric, found := subsysMetrics[key]
	if !found {
		metric = ResourceMetric{
			Name:   name,
			Labels: labels,
		}
	}

	if isCumulative {
		metric.Current = val - metric.Cumulative
		metric.Cumulative = val
	} else {
		metric.Current = val
	}

	if metric.Current > metric.Max {
		metric.Max = val
	}

	metric.Sum += metric.Current

	desc *prometheus.Desc
}

// Describe sends the super-set of all possible descriptors of metrics
func (c *minioCollector) Describe(ch chan<- *prometheus.Desc) {
	ch <- c.desc
}

// Collect is called by the Prometheus registry when collecting metrics.
func (c *minioCollector) Collect(ch chan<- prometheus.Metric) {
	// Expose MinIO's version information
	minioVersionInfo.WithLabelValues(Version, CommitID).Set(1.0)

)

// loadAPIRequestsHTTPMetrics - reads S3 HTTP metrics.
//
// This is a `MetricsLoaderFn`.
//
// This includes node level S3 HTTP metrics.
//
// This function currently ignores `opts`.
func loadAPIRequestsHTTPMetrics(ctx context.Context, m MetricValues, _ *metricsCache) error {
	// Collect node level S3 HTTP metrics.
	httpStats := globalHTTPStats.toServerHTTPStats(false)

			for _, d := range mg.Descriptors {
				labels := slices.Clone(d.VariableLabels)
				labels = append(labels, commonLabels...)
				metric := metricDisplay{
					Name:   mg.MetricFQN(d.Name),
					Help:   d.Help,
					Type:   d.Type.String(),
					Labels: labels,
				}
				metrics = append(metrics, metric)
			}
		}
	}

	return http.HandlerFunc(func(w http.ResponseWriter, r *http.Request) {

jobs:
  # Label of the container job
  sqlite:
    strategy:
      matrix:
        go: ['1.22', '1.21', '1.20']
        platform: [ubuntu-latest] # can not run in windows OS
    runs-on: ${{ matrix.platform }}

    steps:
    - name: Set up Go 1.x
      uses: actions/setup-go@v4
      with:
        go-version: ${{ matrix.go }}

    - name: Check out code into the Go module directory

type InQueueStats struct {
	nowBytes   int64 `json:"-"`
	nowCount   int64 `json:"-"`
	histCounts metrics.Histogram
	histBytes  metrics.Histogram
}

func newInQueueStats(r metrics.Registry, lbl string) InQueueStats {
	histCounts := metrics.NewHistogram(metrics.NewUniformSample(100))
	histBytes := metrics.NewHistogram(metrics.NewUniformSample(100))

	r.Register("replication.queue.counts."+lbl, histCounts)

  /* Want to test simple MatMul example with abstract tensors:
    [[1,2],   *  [[5,6],   =   [[19,22],
     [3,4]]       [7,8]]        [43,50]]
  */

  // Build 1st Matrix.
  int64_t dims[] = {2, 2};  // Matrices will be 2 x 2
  int num_dims = sizeof(dims) / sizeof(dims[0]);

  float vals1[] = {1.0f, 2.0f, 3.0f, 4.0f};
  TFE_Context* eager_ctx = TF_ExecutionContextGetTFEContext(ctx, status.get());

# updated.
concurrency:
  group: ${{ github.workflow }}-${{ github.head_ref }}
  cancel-in-progress: true

permissions:
  contents: read

jobs:
  iam-matrix-test:
    name: "[Go=${{ matrix.go-version }}|ldap=${{ matrix.ldap }}|etcd=${{ matrix.etcd }}|openid=${{ matrix.openid }}]"
    runs-on: ubuntu-latest

    services:
      openldap:
        image: quay.io/minio/openldap
        ports:
          - "389:389"

        env:
          COVERAGE_FILE: coverage/.coverage.${{ runner.os }}-py${{ matrix.python-version }}
          CONTEXT: ${{ runner.os }}-py${{ matrix.python-version }}
      - name: Store coverage files
        uses: actions/upload-artifact@v4
        with:
          name: coverage-${{ matrix.python-version }}-${{ matrix.pydantic-version }}
          path: coverage
          include-hidden-files: true

  coverage-combine: