* `refactor`: Refactors
    * This is normally for changes to the internal code that don't change the behavior. Normally it improves maintainability, or enables future features, etc.
* `upgrade`: Upgrades

	Bucket string

	// Name of the object.
	Name string

	// Date and time when the object was last modified.
	ModTime time.Time

	// Total object size.
	Size int64

	// Actual size is the real size of the object uploaded by client.
	ActualSize *int64

	// IsDir indicates if the object is prefix.
	IsDir bool

	// Hex encoded unique entity tag of the object.
	ETag string

   *
   * <p>This fit minimizes the root-mean-square error in {@code y} as a function of {@code x}. This
   * error is defined as the square root of the mean of the squares of the differences between the
   * actual {@code y} values of the data and the values predicted by the fit for the {@code x}
   * values (i.e. it is the square root of the mean of the squares of the vertical distances between

	// the diskWithAllParts needs to reach the drive to ensure
	// validity of the metadata content, we should make sure that
	// we pass in disks as is for it to be verified. Once verified
	// the disksWithAllParts() returns the actual disks that can be
	// used here for reconstruction. This is done to ensure that
	// we do not skip drives that have inconsistent metadata to be
	// skipped from purging when they are stale.

                       const std::unordered_set<string>& nodes) {
    ASSERT_EQ(nodes.size(), fdef.node_def_size())
        << "Got unexpected number of nodes. Expected: ["
        << absl::StrJoin(nodes, ", ")
        << "] Actual nodes in fdef: " << fdef.DebugString();
    for (const NodeDef& node_def : fdef.node_def()) {
      ASSERT_TRUE(nodes.find(node_def.name()) != nodes.end())
          << "Got unexpected node: " << node_def.name()

 * amortized since some operations can trigger a hash table resize.
 *
 * <p>Unlike {@code java.util.HashSet}, iteration is only proportional to the actual {@code size()},
 * which is optimal, and <i>not</i> the size of the internal hashtable, which could be much larger
 * than {@code size()}. Furthermore, this structure only depends on a fixed number of arrays; {@code

  }

  /**
   * Returns a new immutable array containing the values in the specified range.
   *
   * <p><b>Performance note:</b> The returned array has the same full memory footprint as this one
   * does (no actual copying is performed). To reduce memory usage, use {@code subArray(start,
   * end).trimmed()}.
   */
  public ImmutableLongArray subArray(int startIndex, int endIndex) {

  }

  /**
   * Returns a new immutable array containing the values in the specified range.
   *
   * <p><b>Performance note:</b> The returned array has the same full memory footprint as this one
   * does (no actual copying is performed). To reduce memory usage, use {@code subArray(start,
   * end).trimmed()}.
   */
  public ImmutableIntArray subArray(int startIndex, int endIndex) {

  int rank = shape.dims();
  if (num_dims != rank) {
    status->status = InvalidArgument("Expected rank is ", num_dims,
                                     " but actual rank is ", rank);
    return;
  }
  for (int i = 0; i < num_dims; i++) {
    dims[i] = shape.dim_size(i);
  }
}

int TF_CheckpointReaderGetVariableNumDims(TF_CheckpointReader* reader,

* `name`
* `age`

{* ../../docs_src/sql_databases/tutorial002_an_py310.py ln[7:9] hl[7:9] *}

#### `Hero` - the *table model*

Then let's create `Hero`, the actual *table model*, with the **extra fields** that are not always in the other models:

* `id`
* `secret_name`