### Per-bucket Metrics

Metrics with a `/bucket` component in the path return results for each specified bucket in the deployment. These endpoints **require** providing a list of buckets as a `bucket` query parameter.  The endpoint then returns only metrics for the given buckets, with the bucket name in a `bucket` label.

It can be configured via MinIO's standard configuration API (i.e. using `mc admin config set/get`), or equivalently with environment variables. For brevity we show only environment variables here:

```sh

## `Depends()`

Dependencies are handled mainly with the special function `Depends()` that takes a callable.

Here is the reference for it and its parameters.

You can import it directly from `fastapi`:

```python
from fastapi import Depends
```

::: fastapi.Depends

## `Security()`

For many scenarios, you can handle security (authorization, authentication, etc.) with dependencies, using `Depends()`.

                   tensorflow::unwrap(tensor)->DebugString(),
                   " on to a parallel device. Pack non-parallel "
                   "tensors for each device into a parallel tensor explicitly.")
          .c_str());
  return nullptr;
}

// For TFE_CustomDevice::copy_tensor_from_device in the parallel device
// registration.
//
// Currently this is an error, and un-packing ParallelTensors must be performed

 * total combined across the variables maintaining the sum.
 *
 * <p>This class is usually preferable to {@link AtomicLong} when multiple threads update a common
 * sum that is used for purposes such as collecting statistics, not for fine-grained synchronization
 * control. Under low update contention, the two classes have similar characteristics. But under

   *
   * <p>Creates an empty {@code HashSet} for a collection of values for one key.
   *
   * @return a new {@code HashSet} containing a collection of values for one key
   */
  @Override
  Set<V> createCollection() {
    return Platform.<V>newHashSetWithExpectedSize(expectedValuesPerKey);
  }

  /**
   * @serialData expectedValuesPerKey, number of distinct keys, and then for each distinct key: the

//
// This program is distributed in the hope that it will be useful
// but WITHOUT ANY WARRANTY; without even the implied warranty of
// MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.  See the
// GNU Affero General Public License for more details.
//
// You should have received a copy of the GNU Affero General Public License
// along with this program.  If not, see <http://www.gnu.org/licenses/>.

package grid

## Overview

void Range(vector<int32_t>* data, int32_t start, int32_t end,
           int32_t step = 1) {
  for (int32_t i = start; i < end; i += step) {
    (*data)[i] = i;
  }
}

// Fills out_dims with the dimensions of the given tensor.
void GetDims(const TF_Tensor* t, int64_t* out_dims) {
  int num_dims = TF_NumDims(t);
  for (int i = 0; i < num_dims; i++) {
    out_dims[i] = TF_Dim(t, i);
  }
}

	var fullStatus []*xdsWriterStatus
	mappedResp := map[string]string{}
	w := new(tabwriter.Writer).Init(s.Writer, 0, 8, 5, ' ', 0)
	_, _ = fmt.Fprintln(w, "NAME\tCLUSTER\tCDS\tLDS\tEDS\tRDS\tECDS\tISTIOD\tVERSION")
	for _, dr := range drs {
		for _, resource := range dr.Resources {
			clientConfig := xdsstatus.ClientConfig{}
			err := resource.UnmarshalTo(&clientConfig)
			if err != nil {