ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
    TF_Tensor* expected_out0 = expected_csession->output_tensor(0);
    TF_Tensor* expected_out1 = expected_csession->output_tensor(1);

    CompareTensors(out0, expected_out0);
    CompareTensors(out1, expected_out1);
  }

  void CompareTensors(TF_Tensor* a, TF_Tensor* b) {
    float* a_data = static_cast<float*>(TF_TensorData(a));

  TF_Tensor* tensor =
      TF_AllocateTensor(TF_FLOAT, dims.data(), dims.size(), sizeof(float));
  float tensor_data[] = {1};
  memcpy(TF_TensorData(tensor), tensor_data, TF_TensorByteSize(tensor));
  TFE_TensorHandle* tensor_handle = TFE_NewTensorHandle(tensor, status);
  ASSERT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  TFE_OpAddInput(op, tensor_handle, status);
  TF_DeleteTensor(tensor);

                                                     TF_Tensor** value,
                                                     TF_Status* status);

// Fills in `values` with the TF_Tensor values of the attribute `attr_name` of
// `oper`. `values` must point to an array of TF_Tensor* of length at least
// `max_values` (ideally set to TF_AttrMetadata.list_size from

   *                 v     v
   *                   add
   *                    |
   *                    |
   *                    v
   */
  // Define
  TF_Tensor* tensor_123 = Int32Tensor({1, 2, 3});
  TF_Operation* c = Const(tensor_123, func_graph_, s_, "const_array");
  ASSERT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);
  TF_Operation* split = Split3(c, func_graph_, s_);

  // is no information available. A Reason clarifies an HTTP status
  // code but does not override it.
  // +optional
  optional string reason = 4;

  // Extended data associated with the reason.  Each reason may define its
  // own extended details. This field is optional and the data returned
  // is not guaranteed to conform to any schema except that defined by
  // the reason type.
  // +optional

        "//tensorflow/c:c_api_internal",
        "//tensorflow/c:c_api_no_xla",
        "//tensorflow/c:checkpoint_reader",
        "//tensorflow/c:tensor_interface",
        "//tensorflow/c:tf_status_helper",
        "//tensorflow/c:tf_tensor_internal",
        "//tensorflow/cc/saved_model:loader",
        "//tensorflow/compiler/mlir/lite/metrics:error_collector",

			t.Errorf("Test %d: %s: Expected to fail with <ERROR> \"%s\", but passed instead.", i+1, instanceType, testCase.expectedError.Error())
		}
		// Failed as expected, but does it fail for the expected reason.
		if actualErr != nil && !testCase.shouldPass {
			if testCase.expectedError.Error() != actualErr.Error() {

        val ktDiagnostic =
            resolvable.source?.let { diagnostic.asKtDiagnostic(it, element.toKtPsiSourceElement()) }
                ?: KtNonBoundToPsiErrorDiagnostic(factoryName = null, diagnostic.reason, token)
        return KtInapplicableCallCandidateInfo(call, isInBestCandidates, ktDiagnostic)
    }

    private val FirResolvable.calleeOrCandidateName: Name?

				t.Errorf("Test %d: %s: Expected to fail with <ERROR> \"%s\", but passed instead", i+1, instanceType, testCase.err.Error())
			}
			// Failed as expected, but does it fail for the expected reason.
			if err != nil && !testCase.shouldPass {
				if !strings.Contains(err.Error(), testCase.err.Error()) {

  /**
   * An unmodifiable view of a set which may be backed by other sets; this view will change as the
   * backing sets do. Contains methods to copy the data into a new set which will then remain
   * stable. There is usually no reason to retain a reference of type {@code SetView}; typically,
   * you either use it as a plain {@link Set}, or immediately invoke {@link #immutableCopy} or
   * {@link #copyInto} and forget the {@code SetView} itself.
   *