TF_TString tstr[1];
  TF_TString_Init(&tstr[0]);
  TF_TString_Copy(&tstr[0], test_string, sizeof(test_string) - 1);

  auto deallocator = [](void* data, size_t len, void* arg) {};
  unique_tensor_ptr t_in(TF_NewTensor(TF_STRING, nullptr, 0, &tstr[0],
                                      sizeof(tstr), deallocator, nullptr),
                         TF_DeleteTensor);

// Used to return strings across the C API. The caller does not take ownership
// of the underlying data pointer and is not responsible for freeing it.
typedef struct TF_StringView {
  const char* data;
  size_t len;
} TF_StringView;

// --------------------------------------------------------------------------
// TF_SessionOptions holds options that can be passed during session creation.
typedef struct TF_SessionOptions TF_SessionOptions;

				Description:    e.Message,
				HTTPStatusCode: e.Code,
			}
			// GCS may send multiple errors, just pick the first one
			// since S3 only sends one Error XML response.
			if len(e.Errors) >= 1 {
				apiErr.Code = e.Errors[0].Reason
			}
		case *azcore.ResponseError:
			apiErr = APIError{
				Code:           e.ErrorCode,
				Description:    e.Error(),

- Fixed a regression since `v1.27.0` in the scheduler framework when running score plugins. 
  The `skippedScorePlugins` number might be greater than `enabledScorePlugins`, 
  so when initializing a slice the `cap(len(skippedScorePlugins) - len(enabledScorePlugins))` is negative, 
  which is not allowed. ([#121632](https://github.com/kubernetes/kubernetes/pull/121632), [@kerthcet](https://github.com/kerthcet))

ArrayLike","length","nodeName","elem","name","toLowerCase","prototype","jquery","constructor","toArray","get","num","pushStack","elems","ret","merge","prevObject","each","callback","map","arguments","first","eq","last","even","grep","_elem","odd","len","j","end","sort","splice","extend","options","copy","copyIsArray","clone","target","deep","isPlainObject","Array","isArray","undefined","expando","Math","random","replace","isReady","error","msg","noop","proto","Ctor","isEmptyObject","globalEval",...

ArrayLike","length","nodeName","elem","name","toLowerCase","prototype","jquery","constructor","toArray","get","num","pushStack","elems","ret","merge","prevObject","each","callback","map","arguments","first","eq","last","even","grep","_elem","odd","len","j","end","sort","splice","extend","options","copy","copyIsArray","clone","target","deep","isPlainObject","Array","isArray","undefined","expando","Math","random","replace","isReady","error","msg","noop","proto","Ctor","isEmptyObject","globalEval",...

- Fixed a regression since 1.27.0 in scheduler framework when running score plugins. 
  The `skippedScorePlugins` number might be greater than `enabledScorePlugins`, 
  so when initializing a slice the cap(len(skippedScorePlugins) - len(enabledScorePlugins)) is negative, 
  which is not allowed. ([#121666](https://github.com/kubernetes/kubernetes/pull/121666), [@kerthcet](https://github.com/kerthcet)) [SIG Scheduling]

- Fixed a regression since 1.27.0 in scheduler framework when running score plugins. 
  The `skippedScorePlugins` number might be greater than `enabledScorePlugins`, 
  so when initializing a slice the cap(len(skippedScorePlugins) - len(enabledScorePlugins)) is negative, 
  which is not allowed. ([#121667](https://github.com/kubernetes/kubernetes/pull/121667), [@kerthcet](https://github.com/kerthcet)) [SIG Scheduling]

dated","iso","parsedDateParts","era","meridiem","rfc2822","weekdayMismatch","isValid","_isValid","flags","parsedParts","isNowValid","isNaN","_d","getTime","invalidWeekday","_strict","undefined","bigHour","isFrozen","createInvalid","NaN","fun","t","len","momentProperties","updateInProgress","copyConfig","to","from","prop","val","_isAMomentObject","_i","_f","_l","_tzm","_isUTC","_offset","_locale","Moment","config","updateOffset","isMoment","warn","msg","suppressDeprecationWarnings","console","dep...

*   `tf.data.experimental.dense_to_ragged_batch` to output variable ragged rank.
*   `tf.data.experimental.cardinality` is now a method on `tf.data.Dataset`.
*   `tf.data.Dataset` now supports `len(Dataset)` when the cardinality is
    finite.

### `tf.distribute`:

*   Expose experimental