namespace tensorflow {

// Set the shapes and types of the output's handle.
//
// The lengths of the arrays pointed to by `shapes`, `ranks`, and `types` must
// all be equal to `num_shapes_and_types`. If `ranks[i] != -1`, (i.e., if the
// rank is known), then it must be equal to the length of `shapes[i]`; if
// `ranks[i] == 1`, then `shapes[i]` may be nullptr.
//

        shareInfo1.type = 0;
        shareInfo1.remark = "Remark for Share1";

        srvsvc.ShareInfo1 shareInfo2 = new srvsvc.ShareInfo1();
        shareInfo2.netname = "Share2";
        shareInfo2.type = 1;
        shareInfo2.remark = "Remark for Share2";

        // Create ShareInfoCtr1 with the shares
        srvsvc.ShareInfoCtr1 shareInfoCtr1 = new srvsvc.ShareInfoCtr1();
        shareInfoCtr1.count = 2;

        SmbShareInfo share2 = (SmbShareInfo) response.results[1];
        assertEquals("IPC$", share2.getName().trim(), "Share 2 name should be correct.");
        assertEquals(3, share2.type, "Share 2 raw type should be 3.");
        assertEquals("Inter-Process Communication", share2.remark.trim(), "Share 2 remark should be correct.");
    }

    /**

        dfsEnumArray.s[0] = new DfsInfo200();
        dfsEnumArray.s[0].dfs_name = "\\domain\share1";
        dfsEnumArray.s[1] = new DfsInfo200();
        dfsEnumArray.s[1].dfs_name = "\\domain\share2";

        // Manually set the DfsEnumArray200 to the info struct
        dfsRootEnum.info.e = dfsEnumArray;

        // When
        FileEntry[] entries = dfsRootEnum.getEntries();

        // Then

    void testEquals() {
        SmbShareInfo instance1 = new SmbShareInfo("SHARE1", 0, "remark1");
        SmbShareInfo instance2 = new SmbShareInfo("SHARE1", 1, "remark2");
        SmbShareInfo instance3 = new SmbShareInfo("SHARE2", 0, "remark1");
        Object notAShareInfo = new Object();

        assertTrue(instance1.equals(instance2)); // Should be equal based on netName
        assertFalse(instance1.equals(instance3)); // Should not be equal

"$python" -m pip install *.whl $TFCI_PYTHON_VERIFY_PIP_INSTALL_ARGS
if [[ "$TFCI_WHL_IMPORT_TEST_ENABLE" == "1" ]]; then
  "$python" -c 'import tensorflow as tf; t1=tf.constant([1,2,3,4]); t2=tf.constant([5,6,7,8]); print(tf.add(t1,t2).shape)'
  "$python" -c 'import sys; import tensorflow as tf; sys.exit(0 if "keras" in tf.keras.__name__ else 1)'
fi
# Import tf nightly wheel built with numpy2 from PyPI in numpy1 env for testing.

    }

    @Test
    void testRegistrationIdUniqueness() throws Exception {
        WitnessRegistration registration2 =
                new WitnessRegistration("\\\\server\\share2", InetAddress.getByName("192.168.1.101"), WitnessServiceType.CLUSTER_WITNESS);

        assertNotEquals(registration.getRegistrationId(), registration2.getRegistrationId());
    }

    @Test

    void testHandlerEquality() throws Exception {
        // Create two URLs with the same handler
        URL url1 = new URL(null, "smb://host1/share1", handler);
        URL url2 = new URL(null, "smb://host2/share2", handler);

        // Both should use the same handler instance
        assertNotNull(url1);
        assertNotNull(url2);

        // Protocol should be consistent

      return samples;
    }

    @Override
    public Set<V> create(Object... elements) {
      @SuppressWarnings("unchecked")
      V[] valuesArray = (V[]) elements;

      // Start with a suitably shaped collection of entries
      Collection<Entry<K, V>> originalEntries = mapGenerator.getSampleElements(elements.length);

      // Create a copy of that, with the desired value for each value

inspected and debugged and it is intended to be used during the development
phase.

As part of the differences that make Eager mode easier to debug, the [shape
inference
functions](https://www.tensorflow.org/guide/create_op#define_the_op_interface)
are skipped, and any checks implemented inside the shape inference code are not
executed.

The security impact of skipping those checks should be low, since the attack