// template is the object that describes the pod that will be created if
  // insufficient replicas are detected. Each pod stamped out by the StatefulSet
  // will fulfill this Template, but have a unique identity from the rest
  // of the StatefulSet. Each pod will be named with the format
  // <statefulsetname>-<podindex>. For example, a pod in a StatefulSet named

        outputs a summary of the inference converted by TF-TRT. It namely shows
        each `TRTEngineOp` with their input(s)' and output(s)' shape and dtype.
        A detailed version of the summary is available which prints additionally
        all the TensorFlow OPs included in each of the `TRTEngineOp`s.

*   `tf.tpu.experimental.embedding`:

   * operations.
   *
   * <p>The iterator generated by the returned set traverses the entries in the order they were
   * added to the multimap.
   *
   * <p>Each entry is an immutable snapshot of a key-value mapping in the multimap, taken at the
   * time the entry is returned by a method call to the collection or its iterator.
   */
  @Override
  public Set<Entry<K, V>> entries() {

		}
	}
}

// TestListOnlineDisks - checks if listOnlineDisks and outDatedDisks
// are consistent with each other.
func TestListOnlineDisks(t *testing.T) {
	if runtime.GOOS == globalWindowsOSName {
		t.Skip()
	}

	ctx, cancel := context.WithCancel(context.Background())
	defer cancel()

    public <T extends @Nullable Object> T[] toArray(T[] array) {
      return Lists.newArrayList(iterator()).toArray(array);
    }
  }

  /**
   * Returns a collection that applies {@code function} to each element of {@code fromCollection}.
   * The returned collection is a live view of {@code fromCollection}; changes to one affect the
   * other.
   *

          }
        };

    ExecutionException ee1 = getExpectingExecutionException(future);
    ExecutionException ee2 = getExpectingExecutionException(future);

    // Ensure we get a unique execution exception on each get
    assertNotSame(ee1, ee2);

    assertThat(ee1).hasCauseThat().isSameInstanceAs(failure);
    assertThat(ee2).hasCauseThat().isSameInstanceAs(failure);

    checkStackTrace(ee1);
    checkStackTrace(ee2);

            }
          }
        });
      }
    ```

### Accessing Headers ([.kt][AccessHeadersKotlin], [.java][AccessHeadersJava])

And whenever you output that data, even if the source had duplicates, it will be output as a set of unique items.

And it will be annotated / documented accordingly too.

## Nested Models

Each attribute of a Pydantic model has a type.

But that type can itself be another Pydantic model.

So, you can declare deeply nested JSON "objects" with specific attribute names, types and validations.

			return dst, io.EOF
		}
	}
	// Read until next line.
	in, err := r.buf.ReadBytes('\n')
	dst = append(dst, in...)
	return dst, err
}

// csvSplitSize is the size of each block.
// Blocks will read this much and find the first following newline.
// 128KB appears to be a very reasonable default.
const csvSplitSize = 128 << 10

        * FSGroup - a special supplemental group
        * SELinux options
     * If a pod defines an FSGroup, that Pod’s system (emptyDir, secret, configMap,
etc) volumes and block-device volumes will be owned by the FSGroup, and each
container in the pod will run with the FSGroup as a supplemental group
  * Volumes that support SELinux labelling are now automatically relabeled with the
Pod’s SELinux context, if specified