* SMB tree connections and their lifecycle.
 *
 * @author mbechler
 */
public interface SmbTreeHandleInternal extends SmbTreeHandle {

    /**
     * Releases this tree handle back to the pool for reuse
     */
    void release();

    /**
     * Ensures that DFS referrals have been resolved for this tree
     * @throws SmbException if an SMB-specific error occurs

# Extra Data Types { #extra-data-types }

Up to now, you have been using common data types, like:

* `int`
* `float`
* `str`
* `bool`

But you can also use more complex data types.

And you will still have the same features as seen up to now:

* Great editor support.
* Data conversion from incoming requests.
* Data conversion for response data.
* Data validation.
* Automatic annotation and documentation.

# Tipos de Datos Extra

Hasta ahora, has estado usando tipos de datos comunes, como:

* `int`
* `float`
* `str`
* `bool`

Pero también puedes usar tipos de datos más complejos.

Y seguirás teniendo las mismas funcionalidades como hasta ahora:

* Gran soporte de editor.
* Conversión de datos de requests entrantes.
* Conversión de datos para datos de response.
* Validación de datos.
* Anotación y documentación automática.

func writeErrorResponse(w http.ResponseWriter, err error) {
	w.WriteHeader(http.StatusBadRequest)
	json.NewEncoder(w).Encode(map[string]string{
		"error": fmt.Sprintf("%v", err),
	})
}

type Result struct {
	Result bool `json:"result"`
}

func mainHandler(w http.ResponseWriter, r *http.Request) {
	body, err := io.ReadAll(r.Body)
	if err != nil {
		writeErrorResponse(w, err)
		return
	}

	var out bytes.Buffer

import (
	"gorm.io/gorm"
)

func RowQuery(db *gorm.DB) {
	if db.Error == nil {
		BuildQuerySQL(db)
		if db.DryRun || db.Error != nil {
			return
		}

		if isRows, ok := db.Get("rows"); ok && isRows.(bool) {
			db.Statement.Settings.Delete("rows")
			db.Statement.Dest, db.Error = db.Statement.ConnPool.QueryContext(db.Statement.Context, db.Statement.SQL.String(), db.Statement.Vars...)
		} else {

func (bce badConfigErr) Unwrap() error {
	return bce.Err
}

type setConfigResult struct {
	Cfg                     config.Config
	SubSys                  string
	Dynamic                 bool
	LoggerWebhookCfgUpdated bool
}

// SetConfigKVHandler - PUT /minio/admin/v3/set-config-kv
func (a adminAPIHandlers) SetConfigKVHandler(w http.ResponseWriter, r *http.Request) {
	ctx := r.Context()

# All required CUDA packages
cuda-compat-12-8
cuda-command-line-tools-12-8
cuda-cudart-dev-12-8
cuda-nvcc-12-8
cuda-cupti-12-8
cuda-nvprune-12-8
cuda-libraries-12-8
cuda-libraries-dev-12-8
cuda-nvml-dev-12-8
libcufft-12-8
libcurand-12-8
libcusolver-dev-12-8
libcusparse-dev-12-8
libcublas-12-8
libcublas-dev-12-8
libnccl-dev=2.25.1-1+cuda12.8
libnccl2=2.25.1-1+cuda12.8

# All required CUDA packages
cuda-compat-13-0
cuda-command-line-tools-13-0
cuda-cudart-dev-13-0
cuda-nvcc-13-0
cuda-cupti-13-0
cuda-nvprune-13-0
cuda-libraries-13-0
cuda-libraries-dev-13-0
cuda-nvml-dev-13-0
libcufft-13-0
libcurand-13-0
libcusolver-dev-13-0
libcusparse-dev-13-0
libcublas-13-0
libcublas-dev-13-0
libnccl-dev=2.27.7-1+cuda13.0
libnccl2=2.27.7-1+cuda13.0

TFCI_BAZEL_TARGET_SELECTING_CONFIG_PREFIX=windows_x86_cpu_2022
TFCI_BUILD_PIP_PACKAGE_WHEEL_NAME_ARG="--repo_env=WHEEL_NAME=tensorflow"
TFCI_BUILD_PIP_PACKAGE_ADDITIONAL_WHEEL_NAMES="tensorflow_cpu"
TFCI_OUTPUT_DIR=build_output
TFCI_FIND_BIN=C:/tools/msys64/usr/bin/find.exe
TFCI_LIB_SUFFIX="-cpu-windows-x86_64"
# auditwheel is not supported for Windows
TFCI_WHL_AUDIT_ENABLE=0
TFCI_WHL_AUDIT_PLAT=0
# Tests are extremely slow at the moment
TFCI_WHL_BAZEL_TEST_ENABLE=0

  python_bin=python3
  # TODO(belitskiy): Add a `python3` alias/symlink to Windows Docker image.
  if [[ $(uname -s) = MSYS_NT* ]]; then
    python_bin="python"
  fi
  tfrun "$python_bin" tensorflow/tools/ci_build/update_version.py --nightly
fi

if [[ $(uname -s) != MSYS_NT* ]]; then
  tfrun bazel $TFCI_BAZEL_BAZELRC_ARGS test $TFCI_BAZEL_COMMON_ARGS --config=linux_libtensorflow_test