EXPECT_EQ(TF_OK, TF_GetCode(status)) << TF_Message(status);
  if (!forward_input) {
    TFE_DeleteTensorHandle(n);
  }
  TFE_DeleteOp(add_op);

  TF_Tensor* t = TFE_TensorHandleResolve(retval, status);
  if (async) {
    if (forward_input) {
      // Since the input was forwarded, we released the input handle right away
      // and hence expect the input to be forwarded to the return tensor.
      EXPECT_EQ(orig_ptr, TF_TensorData(t));

    private final NavigableSet<E> forward;

    DescendingSet(NavigableSet<E> forward) {
      this.forward = forward;
    }

    @Override
    protected NavigableSet<E> delegate() {
      return forward;
    }

    @Override
    @CheckForNull
    public E lower(@ParametricNullness E e) {
      return forward.higher(e);
    }

    @Override

                          "allow_connect": true
                        },
                        "server_name": "istio-envoy",
                        "forward_client_cert_details": "APPEND_FORWARD",
                        "set_current_client_cert_details": {
                          "subject": true,
                          "dns": true,
                          "uri": true

                          "allow_connect": true
                        },
                        "server_name": "istio-envoy",
                        "use_remote_address": false,
                        "forward_client_cert_details": "APPEND_FORWARD",
                        "set_current_client_cert_details": {
                          "subject": true,
                          "dns": true,
                          "uri": true

  // The server returns only those CIDRs that it thinks that the client can match.
  // For example: the master will return an internal IP CIDR only, if the client reaches the server using an internal IP.
  // Server looks at X-Forwarded-For header or X-Real-Ip header or request.RemoteAddr (in that order) to get the client IP.
  // +optional
  repeated ServerAddressByClientCIDR serverAddressByClientCIDRs = 4;
}

  public void testPowerSetEquals_independentOfOrder() {
    ImmutableSet<Integer> elements = ImmutableSet.of(1, 2, 3, 4);
    Set<Set<Integer>> forward = powerSet(elements);
    Set<Set<Integer>> reverse = powerSet(ImmutableSet.copyOf(elements.asList().reverse()));
    new EqualsTester().addEqualityGroup(forward, reverse).testEquals();
  }

  /**
   * Test that a hash code miscomputed by "input.hashCode() * tooFarValue / 2" is correct under our

  /**
   * Returns the index of the first matching BMP character in a character sequence, or {@code -1} if
   * no matching character is present.
   *
   * <p>The default implementation iterates over the sequence in forward order calling {@link
   * #matches} for each character.
   *
   * @param sequence the character sequence to examine from the beginning
   * @return an index, or {@code -1} if no character matches
   */

  /**
   * Returns the index of the first matching BMP character in a character sequence, or {@code -1} if
   * no matching character is present.
   *
   * <p>The default implementation iterates over the sequence in forward order calling {@link
   * #matches} for each character.
   *
   * @param sequence the character sequence to examine from the beginning
   * @return an index, or {@code -1} if no character matches
   */

				{Name: "newPrefix0"},
				{Name: "newPrefix1"},
			},
			Prefixes: []string{"newzen/"},
		},
		// ListObjectsResult-27.
		// Prefix is set to "Asia/India/" in the testCase, and delimiter is set to forward slash '/' (testCase 59).
		27: {
			IsTruncated: false,
			Objects: []ObjectInfo{
				{Name: "Asia/India/India-summer-photos-1"},
			},
			Prefixes: []string{"Asia/India/Karnataka/"},
		},

# This is the same as the official TensorFlow builds.
# See https://developer.nvidia.com/cuda-gpus#compute
# `compute_XY` enables PTX embedding in addition to SASS. PTX
# is forward compatible beyond the current compute capability major
# release while SASS is only forward compatible inside the current
# major release. Example: sm_80 kernels can run on sm_89 GPUs but
# not on sm_90 GPUs. compute_80 kernels though can also run on sm_90 GPUs.