// In the TFv1 convention, TF_Tensor can hold a string serialization of
// DT_RESOURCE. The string serialization is converted back to a
// ResourceHandle during Session run where the TF_Tensor is converted to a
// Tensor.
// TFv2 does not depend on this conversion. There is no matching
// TF_TensorFromTensorV1 because the conversion to string is performed by the
// python side of Session.

    # in instructions that are too modern being generated. Users that want
    # maximum performance should compile TF in their environment and can pass
    # `-march=native` there.
    # See https://github.com/tensorflow/tensorflow/issues/45744 and duplicates
    default_cc_opt_flags = '-Wno-sign-compare'
  question = ('Please specify optimization flags to use during compilation when'

* Fixes a bug in previous releases where a pod could be placed inside another pod's cgroup when specifying --cgroup-root ([#70678](https://github.com/kubernetes/kubernetes/pull/70678), [@dashpole](https://github.com/dashpole))

    public int hashCode() {
      return map.hashCode();
    }

    private static final long serialVersionUID = 7845222491160860175L;
  }

  /**
   * Returns a view of a multimap where each value is transformed by a function. All other
   * properties of the multimap, such as iteration order, are left intact. For example, the code:
   *
   * <pre>{@code
   * Multimap<String, Integer> multimap =

        ? ((Collection<T>) iterable).stream()
        : StreamSupport.stream(iterable.spliterator(), false);
  }

  /**
   * Returns {@link Collection#stream}.
   *
   * @deprecated There is no reason to use this; just invoke {@code collection.stream()} directly.
   */
  @Deprecated
  @InlineMe(replacement = "collection.stream()")

	// FIXME: network calls made in this manner such as one goroutine per node,
	// can easily eat into the internode bandwidth. This function would be mostly
	// TX saturating, however there are situations where a RX might also saturate.
	// To avoid these problems we must split the work at scale. With 1000 node
	// setup becoming a reality we must try to shard the work properly such as

                }
                else if ( last == null ) {
                    // don't have enough credits/space for the first request, block until available
                    // for space there is nothing we can do, callers need to make sure that a single message fits

                    try {
                        long timeout = getResponseTimeout(chain);

# --incompatible_remove_legacy_whole_archive flag does.
# This flag is set to true in Bazel 1.0 and newer versions. We tried to migrate
# Tensorflow to the default, however test coverage wasn't enough to catch the
# errors.
# There is ongoing work on Bazel team's side to provide support for transitive
# shared libraries. As part of migrating to transitive shared libraries, we
# hope to provide a better mechanism for control over symbol exporting, and

* Fix issue where on re-registration of device plugin, `allocatable` was not getting updated. This issue makes devices invisible to the Kubelet if device plugin restarts. Only work-around, if this fix is not there, is to restart the kubelet and then start device plugin. ([#63118](https://github.com/kubernetes/kubernetes/pull/63118), [@vikaschoudhary16](https://...

            List<Dependency> dependencies,
            String prefix,
            ModelBuildingRequest request) {
        // We only check for groupId/artifactId/version/classifier cause if there is another
        // module with the same groupId/artifactId/version/classifier this will fail the build
        // earlier like "Project '...' is duplicated in the reactor.