build --repo_env=ML_WHEEL_TYPE="snapshot"
build --repo_env=ML_WHEEL_BUILD_DATE=""
build --repo_env=ML_WHEEL_VERSION_SUFFIX=""

# For projects which use TensorFlow as part of a Bazel build process, putting
# nothing in a bazelrc will default to a monolithic build. The following line
# opts in to modular op registration support by default.
build --define framework_shared_object=true
build --define tsl_protobuf_header_only=true

    EntryComparator(@Nullable Comparator<? super K> keyComparator) {
      this.keyComparator = keyComparator;
    }

    @Override
    @SuppressWarnings("unchecked") // no less safe than putting it in the map!
    public int compare(Entry<K, V> a, Entry<K, V> b) {
      return (keyComparator == null)
          ? ((Comparable) a.getKey()).compareTo(b.getKey())
          : keyComparator.compare(a.getKey(), b.getKey());

You can also use the *path operation decorator* parameters `response_model_include` and `response_model_exclude`.

They take a `set` of `str` with the name of the attributes to include (omitting the rest) or to exclude (including the rest).

This can be used as a quick shortcut if you have only one Pydantic model and want to remove some data from the output.

/// tip

type BucketOptions struct {
	Deleted    bool // true only when site replication is enabled
	Cached     bool // true only when we are requesting a cached response instead of hitting the disk for example ListBuckets() call.
	NoMetadata bool
}

// SetReplicaStatus sets replica status and timestamp for delete operations in ObjectOptions

Previous versions of FastAPI (before <abbr title="before 2023-03">0.95.0</abbr>) required you to use `Query` as the default value of your parameter, instead of putting it in `Annotated`, there's a high chance that you will see code using it around, so I'll explain it to you.

/// tip

    @SuppressWarnings("SynchronizeOnNonFinalField")
    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;

            // When: Trying to encode (may throw exception due to deferred buffer)
            // Then: Should at least call the basic encoding methods before hitting deferred
            assertThrows(Exception.class, () -> {
                unicodeString.encode(mockNdrBuffer);
            }, "Should encounter issue with deferred buffer access");

    /**
     * This default mode for combining children DOMs during merge means that where element names match, the process will
     * try to merge the element data, rather than putting the dominant and recessive elements (which share the same
     * element name) as siblings in the resulting DOM.
     */
    @Deprecated(since = "4.0.0", forRemoval = true)

    @SuppressWarnings("SynchronizeOnNonFinalField")
    public T get() {
      // Another variant of Double Checked Locking.
      //
      // We use two volatile reads. We could reduce this to one by
      // putting our fields into a holder class, but (at least on x86)
      // the extra memory consumption and indirection are more
      // expensive than the extra volatile reads.
      long nanos = expirationNanos;

    (by default) transferred to the TensorFlow team. This means that the benefit
    of the contribution must be compared against the cost of maintaining the
    feature.
*   Full new features (e.g., a new op implementing a cutting-edge algorithm)
    typically will live in
    [tensorflow/addons](https://github.com/tensorflow/addons) to get some
    airtime before a decision is made regarding whether they are to be migrated
    to the core.