std::vector<std::pair<string, Tensor>> feeds;
  feeds.reserve(inputs.size());
  for (auto const& feed : inputs) {
    TF_RETURN_IF_ERROR(feed.second.status);
    feeds.emplace_back(std::piecewise_construct,
                       std::forward_as_tuple(feed.first.name()),
                       std::forward_as_tuple(feed.second.tensor));
  }

  std::vector<string> output_tensor_names;

   * omitted} or {@linkplain #withPadChar(char) replaced}.
   *
   * <p>No line feeds are added by default, as per <a
   * href="http://tools.ietf.org/html/rfc4648#section-3.1">RFC 4648 section 3.1</a>, Line Feeds in
   * Encoded Data. Line feeds may be added using {@link #withSeparator(String, int)}.
   */
  public static BaseEncoding base64() {
    return BASE64;
  }

   * omitted} or {@linkplain #withPadChar(char) replaced}.
   *
   * <p>No line feeds are added by default, as per <a
   * href="http://tools.ietf.org/html/rfc4648#section-3.1">RFC 4648 section 3.1</a>, Line Feeds in
   * Encoded Data. Line feeds may be added using {@link #withSeparator(String, int)}.
   */
  public static BaseEncoding base64() {
    return BASE64;
  }

// <endcallsites>
// <endfuncpreamble>
func T_chained_indirect_call(x, y int) {
	// Here 'returnsFunc' returns an inlinable func that feeds
	// directly into a call (no named intermediate).
	G += returnsFunc(x - y)(x + y)
}

// returns2.go T_chained_conc_iface_call 144 0 1
// <endpropsdump>
// {"Flags":0,"ParamFlags":[0,0],"ResultFlags":null}

able to grab the feed and see the feed's actual URL in
the link rel="self", but the default value for that drops
the :port from the URL, and I cannot for the life of me
figure out how to get the Atom generator deep inside
django not to do that, or even where it is doing that,
or even what code is running to generate the Atom feed.
(I thought I knew but I added some assert False statements

    }
    i += Character.charCount(codePoint)
  }
}

/**
 * Returns a substring of `input` on the range `[pos..limit)` with the following
 * transformations:
 *
 *  * Tabs, newlines, form feeds and carriage returns are skipped.
 *
 *  * In queries, ' ' is encoded to '+' and '+' is encoded to "%2B".
 *
 *  * Characters in `encodeSet` are percent-encoded.
 *

		Status: metav1.StatusSuccess,
	}})
	metrics.IncStreamTranslatorRequest(req.Context(), strconv.Itoa(http.StatusOK))
}

// translatorSizeQueue feeds the size events from the WebSocket
// resizeChan into the SPDY client input. Implements TerminalSizeQueue
// interface.
type translatorSizeQueue struct {
	resizeChan chan remotecommand.TerminalSize
}

  // inference.
  pm.addPass(mlir::TF::CreateGuaranteeAllFuncsOneUsePass());
  pm.addPass(mlir::TF::CreateTFShapeInferencePass());
  // For V1 compatibility, we process a module where the graph does not have
  // feeds and fetched. We extract first the TPU computation in a submodule,
  // where it'll be in a function with args and returned values, much more
  // like a TF v2 module. We can then run the usual pipeline on this nested

}

TEST_F(CApiColocationTest, Proto_ColocateWith) {
  SetViaProto(desc_, {"loc:@feed2"});
  TF_ColocateWith(desc_, feed1_);
  FinishAndVerify(desc_, {"loc:@feed1", "loc:@feed2"});
}

TEST_F(CApiColocationTest, ColocateWith_ColocateWith) {
  TF_ColocateWith(desc_, feed1_);
  TF_ColocateWith(desc_, feed2_);
  FinishAndVerify(desc_, {"loc:@feed1", "loc:@feed2"});
}

}

// Returns a TPUPartitionedInput op connected to a `tf_device.cluster_func`
// operand value if it has an XLA sharding. If value is a resource type then
// TPUPartitionedInput op will be connected to a ReadVariable op that feeds into
// a `tf_device.cluster_func`.
mlir::Operation* GetXlaShardingFromOperand(Value value) {
  Value value_to_visit = value;
  if (auto read_var = value_to_visit.getDefiningOp<mlir::TF::ReadVariableOp>())