<img src="/img/tutorial/path-params/image03.png">

### Trabajando con *enumeraciones* de Python

El valor del *path parameter* será un *miembro* de enumeración.

#### Comparar *miembros* de enumeraciones

Puedes compararlo con el *miembro* de enumeración en tu enum creada `ModelName`:

{* ../../docs_src/path_params/tutorial005.py hl[17] *}

#### Obtener el valor de *enumeración*

        EnumSet<RdmaAccess> access = EnumSet.of(RdmaAccess.LOCAL_READ, RdmaAccess.LOCAL_WRITE);

        RdmaMemoryRegion region = provider.registerMemory(buffer, access);
        assertNotNull(region, "Memory region should not be null");
        assertEquals(buffer, region.getBuffer(), "Buffer should match");
        assertEquals(1024, region.getSize(), "Size should match buffer size");

    false

-   type: input id: Cuda attributes: label: CUDA/cuDNN version description:
    placeholder: validations: required: false

-   type: input id: Gpu attributes: label: GPU model and memory description: if
    compiling from source placeholder: validations: required: false

-   type: textarea id: what-happened attributes: label: Current Behaviour?

    int NT_STATUS_NOT_IMPLEMENTED = 0xC0000002;
    /** The specified information class is invalid */
    int NT_STATUS_INVALID_INFO_CLASS = 0xC0000003;
    /** Invalid access to memory location */
    int NT_STATUS_ACCESS_VIOLATION = 0xC0000005;
    /** The handle is invalid */
    int NT_STATUS_INVALID_HANDLE = 0xC0000008;
    /** The parameter is incorrect */

//
// Returns a TF_Buffer. The memory pointed to by the result is owned by
// lib_handle. The data in the buffer will be the serialized OpList proto for
// ops defined in the library.
TF_CAPI_EXPORT extern TF_Buffer TF_GetOpList(TF_Library* lib_handle);

// Frees the memory associated with the library handle.
// Does NOT unload the library.

    int NT_STATUS_NOT_IMPLEMENTED = 0xC0000002;
    /** The specified information class is invalid */
    int NT_STATUS_INVALID_INFO_CLASS = 0xC0000003;
    /** Invalid access to memory location */
    int NT_STATUS_ACCESS_VIOLATION = 0xC0000005;
    /** The handle is invalid */
    int NT_STATUS_INVALID_HANDLE = 0xC0000008;
    /** The parameter is incorrect */

     */
    protected boolean done = false;

    /**
     * Constructs a ContentOutputStream with a specified threshold and temporary directory.
     *
     * @param threshold the threshold in bytes for writing to memory before writing to a file
     * @param tmpDir the temporary directory to create the file in
     */
    public ContentOutputStream(final int threshold, final File tmpDir) {
        super(threshold, PREFIX, SUFFIX, tmpDir);

        user.setGroups(groupList.stream().distinct().toArray(n -> new String[n]));
        user.setRoles(roleList.stream().distinct().toArray(n -> new String[n]));
    }

    /**
     * Processes member-of information from Microsoft Graph API.
     * @param user The Azure AD user.
     * @param groupList The list to add group names to.
     * @param roleList The list to add role names to.

   - sanjoy
# filesystem path
filesystem_path:
   - tensorflow/c/experimental/filesystem
# security path
security_path:
   - tensorflow/security
# words checklist
segfault_memory:
   - segfault
   - memory leaks
# assignees
filesystem_security_assignee:
   - mihaimaruseac
   
# Cuda Comment
cuda_comment: >
   From the template it looks like you are installing **TensorFlow** (TF) prebuilt binaries:

        }
        return response.getStatus().getStatus();
    }

    /**
     * Calculates the memory size of a document data map.
     * This is useful for monitoring memory usage during indexing operations.
     *
     * @param dataMap the document data as a map of field names to values
     * @return the estimated memory size in bytes
     */
    public long calculateDocumentSize(final Map<String, Object> dataMap) {