if (len > max_length_ || data_.size() >= max_length_ - len)
    return absl::ResourceExhaustedError("Buffer overflow");
  data_.resize(data_.size() + len);
  memcpy(data_.data() + offset_.back(), str, len);
  offset_.push_back(offset_.back() + len);
  return absl::OkStatus();
}

int MiniDynamicBuffer::WriteToBuffer(char** buffer) {
  // Allocate sufficient memory to tensor buffer.
  int32_t num_strings = offset_.size() - 1;

            << "Do not convert mlir module back to graph";
    return absl::OkStatus();
  }
  GraphExportConfig export_config;
  absl::flat_hash_set<Node*> control_ret_nodes;

  timings.Reset({kTfMlirCategory, "convert_mlir_to_graph"});
  // Some or all passes are enabled. Convert MLIR module and return back
  // resulted graph.

    /**
     * Disables input tracking for the current thread. Multiple calls to this method "stack", so if
     * this method was called twice then [restoreForCurrentThread] should also be called twice to
     * enable input tracking back.
     */
    fun disableForCurrentThread() {
        ++inputTrackingDisabledCounterForThread
    }

    /**
     * Restores the input tracking state to the state it was in before the last call to

		return
	}

	listObjectVersions := objectAPI.ListObjectVersions

	// Initiate a list object versions operation based on the input params.
	// On success would return back ListObjectsInfo object to be
	// marshaled into S3 compatible XML header.
	listObjectVersionsInfo, err := listObjectVersions(ctx, bucket, prefix, marker, versionIDMarker, delimiter, maxkeys)
	if err != nil {

CL 564035 - changed encoding/xml, but the change was too disrptive and rolled back in CL 570175, reopening tracking issue go.dev/issue/65691; nothing to document in Go 1.23 release notes

// Applies dynamic range quantization for the given model wehre the input_model
// type is flatbuffer but is converted to MLIR during quantization process and
// then converted back to flatbuffer for return. Note that this is part of
// reaching feature parity with the old quantizer for dynamic range
// quantization, specifically for
// third_party/tensorflow/lite/tools/optimize/quantize_weights.h.

     */
    @Nonnull
    Optional<RemoteRepository> getRepository();

    /**
     * Traverses this node and potentially its children using the specified visitor.
     *
     * @param visitor the visitor to call back, must not be {@code null}
     * @return {@code true} to visit siblings nodes of this node as well, {@code false} to skip siblings
     */
    boolean accept(@Nonnull NodeVisitor visitor);

    /**

		klog.Warningf("Failed preparing watchlist options for customresourcedefinitions, falling back to the standard LIST semantics, err = %v", watchListOptionsErr)
	} else if hasWatchListOptionsPrepared {
		result, err := c.watchList(ctx, watchListOptions)
		if err == nil {

	if watchListOptions, hasWatchListOptionsPrepared, watchListOptionsErr := watchlist.PrepareWatchListOptionsFromListOptions(opts); watchListOptionsErr != nil {
		klog.Warningf("Failed preparing watchlist options for examples, falling back to the standard LIST semantics, err = %v", watchListOptionsErr)
	} else if hasWatchListOptionsPrepared {
		result, err := c.watchList(ctx, watchListOptions)
		if err == nil {

        explaining why this is.
    */
    @Requires(IntegTestPreconditions.NotEmbeddedExecutor)
    def "daemon bootstrap classpath is bare bones"() {
        given:
        buildFile << """
            task loadClasses {
                doLast {
                    def systemLoader = ClassLoader.systemClassLoader