}

// ReadAll is a raw call, reads content at any path and returns the buffer.
func (s *xlStorage) ReadAll(ctx context.Context, volume string, path string) (buf []byte, err error) {
	// Specific optimization to avoid re-read from the drives for `format.json`
	// in-case the caller is a network operation.
	if volume == minioMetaBucket && path == formatConfigFile {
		s.RLock()
		formatData := make([]byte, len(s.formatData))

    *   Performance optimizations:
    *   Add `tf.data.experimental.OptimizationOptions()`, to configure options
        to enable `tf.data` performance optimizations. Add nested option,
        `experimental_optimization` (which takes a
        `tf.data.experimental.OptimizationOptions` object), to
        `tf.data.Options`. Remove performance optimization options from

};

// Returns the number of elements in the gradient tensor.
int64_t TapeVSpace::NumElements(AbstractTensorHandle* tensor) const {
  // TODO(srbs): It seems like this is used only for performance optimization
  // and not for correctness. The only downside of keeping this 1 seems to be
  // that the gradient accumulation is unbounded and we will never
  // aggressively aggregate accumulated gradients to recover memory.

	return dst
}

type metadataResolutionParams struct {
	dirQuorum int // Number if disks needed for a directory to 'exist'.
	objQuorum int // Number of disks needed for an object to 'exist'.

	// An optimization request only an 'n' amount of versions from xl.meta
	// to avoid resolving all versions to figure out the latest 'version'
	// for ListObjects, ListObjectsV2
	requestedVersions int

			if length > 0 && field.Size > 0 {
				alterColumn = true
			} else {
				// has size in data type and not equal
				// Since the following code is frequently called in the for loop, reg optimization is needed here
				matches2 := regFullDataType.FindAllStringSubmatch(fullDataType, -1)
				if !field.PrimaryKey &&
					(len(matches2) == 1 && matches2[0][1] != fmt.Sprint(length) && ok) {
					alterColumn = true

      tensorflow::strings::StrCat("/job:", job_name, "/replica:0/task:", 0));
  auto* rewrite_options =
      config->mutable_graph_options()->mutable_rewrite_options();
  rewrite_options->set_scoped_allocator_optimization(
      tensorflow::RewriterConfig::ON);
  rewrite_options->mutable_scoped_allocator_opts()->add_enable_op(
      "CollectiveReduce");

  if ((tensorflow::IsGoogleCudaEnabled() || tensorflow::IsBuiltWithROCm()) &&

      return checkNotNull(otherConverter, "otherConverter");
    }

    /*
     * We *could* override convertAll() to return its input, but it's a rather pointless
     * optimization and opened up a weird type-safety problem.
     */

    @Override
    public String toString() {
      return "Converter.identity()";
    }

    private Object readResolve() {

		reader = etag.Wrap(s2c, actualReader)
		size = -1   // Since compressed size is un-predictable.
		md5hex = "" // Do not try to verify the content.
		sha256hex = ""
	}

	var forceMD5 []byte
	// Optimization: If SSE-KMS and SSE-C did not request Content-Md5. Use uuid as etag. Optionally enable this also
	// for server that is started with `--no-compat`.

$(foreach bin,$(LINUX_AGENT_BINARIES),$(eval $(call build-linux,$(bin),$(AGENT_TAGS))))

# Create helper targets for each binary, like "pilot-discovery"
# As an optimization, these still build everything
$(foreach bin,$(BINARIES),$(shell basename $(bin))): build
ifneq ($(TARGET_OUT_LINUX),$(LOCAL_OUT))

    }
  }

  /**
   * Exactly like signalNextWaiter, but caller guarantees that guardToSkip need not be considered,
   * because caller has previously checked that guardToSkip.isSatisfied() returned false. An
   * optimization for the case that guardToSkip.isSatisfied() may be expensive.
   *
   * <p>We decided against using this method, since in practice, isSatisfied() is likely to be very