// original framework of destruction, and this context will be deleted also.
struct TfDlManagedTensorCtx {
  TensorReference reference;
  std::vector<int64_t> shape;
  std::vector<int64_t> strides;
  DLManagedTensor tensor;

  explicit TfDlManagedTensorCtx(const TensorReference& ref) : reference(ref) {}
};

// Gets tensor from eager tensor handle.

    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

        ctr0.array = new srvsvc.ShareInfo0[2];
        ctr0.array[0] = new srvsvc.ShareInfo0();
        ctr0.array[0].netname = "Share1";
        ctr0.array[1] = new srvsvc.ShareInfo0();
        ctr0.array[1].netname = "Share2";

        // Set up mocks
        mockDeferredBuffer.index = 0; // Set field directly
        mockDeferredBuffer.deferred = mockDeferredBuffer;

        ctr0.encode(mockNdrBuffer);

fi
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.

// Represents a (partially-defined) shape.
typedef struct TF_Shape {
  int num_dims;  // Must be >= -1; -1 represents unknown rank.
  int64_t* dim_sizes;
} TF_Shape;

// Add a new parameter to a TensorFlow Function.
TF_AbstractTensor* TF_AddFunctionParameter(TF_ExecutionContext* func,
                                           TF_DataType dtype, TF_Shape shape,
                                           TF_Status* s);

      return samples;
    }

    @Override
    public Set<K> create(Object... elements) {
      @SuppressWarnings("unchecked")
      K[] keysArray = (K[]) 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 key

    }

    @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

  TF_AddInput(desc, r);
  return TF_FinishOperation(desc, s);
}

TF_Operation* RandomUniform(TF_Operation* shape, TF_DataType dtype,
                            TF_Graph* graph, TF_Status* s) {
  TF_OperationDescription* desc =
      TF_NewOperation(graph, "RandomUniform", "random_uniform");
  TF_AddInput(desc, {shape, 0});
  TF_SetAttrType(desc, "dtype", dtype);
  return TF_FinishOperation(desc, s);
}

    void testResourceCreationConsistency() throws CIFSException {
        // Test that resource creation works consistently
        String[] validUrls = { "smb://server1/share1/", "smb://server2/share2/file.txt" };

        for (String validUrl : validUrls) {
            // When
            SmbResource resource = context.get(validUrl);

            // Then

 public:
  // Add a function parameter and return the corresponding tensor.
  virtual absl::Status AddParameter(DataType dtype,
                                    const PartialTensorShape& shape,
                                    TracingTensorHandle**) = 0;

  // Finalize this context and make a function out of it. The context is in a
  // invalid state after this call and must be destroyed.