// Assert that the object is not null
        assertNotNull(msrpcLsarClose, "MsrpcLsarClose object should not be null");

        // Verify that the constructor correctly sets ptype and flags
        // These values are inherited from LsarClose, but MsrpcLsarClose sets them in its constructor
        assertEquals(0, msrpcLsarClose.getPtype(), "ptype should be 0");

        return DATA_SERVICE_THREAD_LOCAL.get();
    }

    /**
     * Sets the DataService instance for the current thread.
     * If the provided DataService is null, it removes the DataService from the current thread's local storage.
     * Otherwise, it sets the provided DataService to the current thread's local storage.
     *

    }

    /**
     * Gets the lease key for this V2 lease request
     * @return the lease key
     */
    public Smb2LeaseKey getLeaseKey() {
        return leaseKey;
    }

    /**
     * Sets the lease key for this V2 lease request
     * @param leaseKey the lease key to set
     */
    public void setLeaseKey(Smb2LeaseKey leaseKey) {
        this.leaseKey = leaseKey;
    }

    /**

    /**
     * Sets the fourth value.
     *
     * @param value4
     *            The fourth value
     */
    public void setValue4(final T4 value4) {
        this.value4 = value4;
    }

    /**
     * Returns the fifth value.
     *
     * @return The fifth value
     */
    public T5 getValue5() {
        return value5;
    }

    /**
     * Sets the fifth value.
     *

                if (c == spaceChar) {
                    return true;
                }
            }
            return false;
        }

        /**
         * Sets the initial capacity for the text normalization context.
         *
         * @param initialCapacity the initial capacity to be set
         * @return the updated TextNormalizeContext instance
         */

    return Sets.equalsImpl(this, object);
  }

  /**
   * A sensible definition of {@link #hashCode} in terms of {@link #iterator}. If you override
   * {@link #iterator}, you may wish to override {@link #equals} to forward to this implementation.
   *
   * @since 7.0
   */
  protected int standardHashCode() {
    return Sets.hashCodeImpl(this);
  }

    /**
     * Returns the XML encoding pattern.
     * @return The XML encoding pattern.
     */
    public Pattern getXmlEncodingPattern() {
        return xmlEncodingPattern;
    }

    /**
     * Sets the XML encoding pattern.
     * @param metaCharsetPattern The XML encoding pattern.
     */
    public void setXmlEncodingPattern(final Pattern metaCharsetPattern) {
        xmlEncodingPattern = metaCharsetPattern;
    }

    /**
     * Sets the index name.
     * @param index The index name.
     */
    public void setIndex(final String index) {
        this.index = index;
    }

    /**
     * Sets the size of results.
     * @param size The size.
     */
    public void setSize(final int size) {
        this.size = size;
    }

    /**
     * Sets the query string.

   
   
   *TensorFlow release binaries version 1.6 and higher are prebuilt with AVX instruction sets.*
   
   
   Therefore on any CPU that does not have these instruction sets, either CPU or GPU version of TF will fail to load.
   
   Apparently, your CPU model does not support AVX instruction sets. You can still use TensorFlow with the alternatives given below:
   
      * Try Google Colab to use TensorFlow.

        return parentKey + nestedKeySeparator + currentKey;
    }

    /**
     * Sets the maximum depth for nested structure extraction.
     *
     * @param maxDepth the maximum depth
     */
    public void setMaxDepth(final int maxDepth) {
        this.maxDepth = maxDepth;
    }

    /**
     * Sets the field separator for key-value pairs.
     *
     * @param fieldSeparator the field separator