* followed by <dfn>flattening</dfn> and <dfn>resolution</dfn>.
 * The version selection is done for each dependency during the collection phase.
 * The flatten phase will keep only a single version per ({@code groupId}, {@code artifactId}) pair.
 * The resolution will actually download the dependencies (or artifacts) that have been computed.
 *
 * @since 4.0.0
 */
@Experimental
@Immutable

//    "/job:localhost/replica:0/task:0/device:GPU:1"}
// Then executing an operation on CUSTOM:0 will execute it on GPU:0 and GPU:1.
//
// Implicit copies onto `device_name` are allowed, replicating the value once
// per device in `underlying_devices`. Implicit copies off of the device throw
// an error.
//
// All component tensors must have the same dtype. Currently they must also have

# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.

SHELL := /usr/bin/env bash

# allow optional per-repo overrides
-include Makefile.overrides.mk

# Set the environment variable BUILD_WITH_CONTAINER to use a container
# to build the repo. The only dependencies in this mode are to have make and

 * **ExchangeFinder** chooses which connection carries each exchange. Where possible it will use the same connection for all exchanges in a single call. It prefers reusing pooled connections over establishing new connections.      

#### Per-Connection Locks

If your lambda target expects an authorization token then you can enable it per function target as follows

```
MINIO_LAMBDA_WEBHOOK_ENABLE_function=on MINIO_LAMBDA_WEBHOOK_ENDPOINT_function=http://localhost:5000 MINIO_LAMBDA_WEBHOOK_AUTH_TOKEN="mytoken" minio server /data &
```

### Lambda Target with mTLS authentication

If your lambda target expects mTLS client you can enable it per function target as follows
```

This command finds a Prometheus pod running in the specified istio system
namespace. It then executes a series of queries per requested workload to
find the following top-level workload metrics: total requests per second,
error rate, and request latency at p50, p90, and p99 percentiles. The
query results are printed to the console, organized by workload name.

import java.util.concurrent.ExecutionException;

/**
 * A cache which forwards all its method calls to another cache. Subclasses should override one or
 * more methods to modify the behavior of the backing cache as desired per the <a
 * href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p>Note that {@link #get}, {@link #getUnchecked}, and {@link #apply} all expose the same

### One Process per Container

In this type of scenario, you probably would want to have **a single (Uvicorn) process per container**, as you would already be handling replication at the cluster level.

/**
 * A {@link BlockingDeque} which forwards all its method calls to another {@code BlockingDeque}.
 * Subclasses should override one or more methods to modify the behavior of the backing deque as
 * desired per the <a href="http://en.wikipedia.org/wiki/Decorator_pattern">decorator pattern</a>.
 *
 * <p><b>Warning:</b> The methods of {@code ForwardingBlockingDeque} forward <b>indiscriminately</b>

import jakarta.servlet.ServletContext;
import jakarta.servlet.ServletException;
import jakarta.servlet.http.HttpServletRequest;

/**
 * The handler of multipart request (fileupload request). <br>
 * This instance is created per one multipart request.
 * @author modified by jflute (originated in Seasar)
 */
public class FessMultipartRequestHandler implements MultipartRequestHandler {