// (e.g. 1, 2, 3, 4, 5 ns) that aren't very useful, timeHistNumBuckets
	// is defined in terms of the least significant bit (timeHistMinBucketBits)
	// that needs to be set before we start bucketing and the most
	// significant bit (timeHistMaxBucketBits) that we bucket before we just
	// dump it into a catch-all bucket.
	//
	// As an example, consider the configuration:
	//
	//    timeHistMinBucketBits = 9

          TF::AddV2Op::getOperationName().str(),
          TF::ArgMaxOp::getOperationName().str(),
          TF::AvgPoolOp::getOperationName().str(),
          TF::BiasAddOp::getOperationName().str(),
          TF::BucketizeOp::getOperationName().str(),
          TF::ConcatV2Op::getOperationName().str(),
          TF::Conv2DBackpropInputOp::getOperationName().str(),
          TF::Conv2DOp::getOperationName().str(),

        TypeID::get<TF::BiasAddOp>(),
        TypeID::get<TF::BitwiseAndOp>(),
        TypeID::get<TF::BitwiseOrOp>(),
        TypeID::get<TF::BitwiseXorOp>(),
        TypeID::get<TF::BucketizeOp>(),
        // CaseOp isn't actually supported but is enabled for testing to
        // make sure ops with symbol ref attributes are filtered out.
        TypeID::get<TF::CaseOp>(),
        TypeID::get<TF::CastOp>(),

}

def TF_BoostedTreesBucketizeOp : TF_Op<"BoostedTreesBucketize", [Pure, SameVariadicOperandSize]> {
  let summary = "Bucketize each feature based on bucket boundaries.";

  let description = [{
An op that returns a list of float tensors, where each tensor represents the
bucketized values for a single feature.
  }];

  let arguments = (ins

	// function for hashing keys (ptr to key, seed) -> hash
	Hasher     func(unsafe.Pointer, uintptr) uintptr
	KeySize    uint8  // size of key slot
	ValueSize  uint8  // size of elem slot
	BucketSize uint16 // size of bucket
	Flags      uint32
}

// Note: flag values must match those used in the TMAP case
// in ../cmd/compile/internal/reflectdata/reflect.go:writeType.

			keysize = int64(d.arch.PtrSize)
			indirectKey = true
		}
		if valsize > abi.MapMaxElemBytes {
			valsize = int64(d.arch.PtrSize)
			indirectVal = true
		}

		// Construct type to represent an array of BucketSize keys
		keyname := d.nameFromDIESym(keytype)
		dwhks := d.mkinternaltype(ctxt, dwarf.DW_ABRV_ARRAYTYPE, "[]key", keyname, "", func(dwhk *dwarf.DWDie) {

	cacher.bookmarkWatchers.popExpiredWatchersThreadUnsafe()
	if len(cacher.bookmarkWatchers.watchersBuckets) != 0 {
		numWatchers := 0
		for bucketID, v := range cacher.bookmarkWatchers.watchersBuckets {
			numWatchers += len(v)
			t.Errorf("there are %v watchers at bucket Id %v with start Id %v", len(v), bucketID, cacher.bookmarkWatchers.startBucketID)
		}
		t.Errorf("unexpected bookmark watchers %v", numWatchers)
	}
}

    "HASHTABLE_SIZE",
    "REDUCE_ALL",
    "CONV_3D_TRANSPOSE",
    "VAR_HANDLE",
    "READ_VARIABLE",
    "ASSIGN_VARIABLE",
    "BROADCAST_ARGS",
    "RANDOM_STANDARD_NORMAL",
    "BUCKETIZE",
    "RANDOM_UNIFORM",
    "MULTINOMIAL",
    "GELU",
    "DYNAMIC_UPDATE_SLICE",
    "RELU_0_TO_1",
    "UNSORTED_SEGMENT_PROD",
    "UNSORTED_SEGMENT_MAX",
    "UNSORTED_SEGMENT_SUM",

	// a series of emptyRest cells.
	h := *(**hmap)(unsafe.Pointer(&m))
	i := any(m)
	t := *(**maptype)(unsafe.Pointer(&i))

	for x := 0; x < 1<<h.B; x++ {
		b0 := (*bmap)(add(h.buckets, uintptr(x)*uintptr(t.BucketSize)))
		n := 0
		for b := b0; b != nil; b = b.overflow(t) {
			for i := 0; i < abi.MapBucketCount; i++ {
				if b.tophash[i] != emptyRest {
					n++
				}
			}
		}
		k := 0

# Release 2.8.0

## Major Features and Improvements

*   `tf.lite`:

    *   Added TFLite builtin op support for the following TF ops:
        *   `tf.raw_ops.Bucketize` op on CPU.
        *   `tf.where` op for data types
            `tf.int32`/`tf.uint32`/`tf.int8`/`tf.uint8`/`tf.int64`.
        *   `tf.random.normal` op for output data type `tf.float32` on CPU.