VLUXEI8V	(X10), V2, V1, V3		// ERROR "invalid vector mask register"
	VSUXEI8V	V3, V2, V1, (X10)		// ERROR "invalid vector mask register"
	VLOXEI8V	(X10), V2, V1, V3		// ERROR "invalid vector mask register"
	VSOXEI8V	V3, V2, V1, (X10)		// ERROR "invalid vector mask register"
	VLSEG2E8V	(X10), V1, V3			// ERROR "invalid vector mask register"
	VLSEG2E8FFV	(X10), V1, V3			// ERROR "invalid vector mask register"

                           const string& op_name) {
  std::vector<int64_t> input_ids(inputs.size());
  std::vector<tensorflow::DataType> input_dtypes(inputs.size());
  for (int i = 0; i < inputs.size(); i++) {
    input_ids[i] = ToId(inputs[i]);
    input_dtypes[i] = inputs[i]->DataType();
  }
  std::vector<TapeTensor> tape_tensors;
  tape_tensors.reserve(outputs.size());
  for (auto t : outputs) {

	// 31.11.15: Vector Integer Merge Instructions
	VMERGEVVM	V1, V2, V0, V3			// d781205c
	VMERGEVXM	X10, V2, V0, V3			// d741255c
	VMERGEVIM	$15, V2, V0, V3			// d7b1275c

	// 31.11.16: Vector Integer Move Instructions
	VMVVV		V2, V3				// d701015e
	VMVVX		X10, V3				// d741055e
	VMVVI		$15, V3				// d7b1075e

	// 31.12.1: Vector Single-Width Saturating Add and Subtract

		}
	}
	if opd, ok := riscv64SpecialOperand[name]; ok {
		return opd
	}
	return riscv.SPOP_END
}

// RISCV64ValidateVectorType reports whether the given configuration is a
// valid vector type.
func RISCV64ValidateVectorType(vsew, vlmul, vtail, vmask int64) error {
	_, err := riscv.EncodeVectorType(vsew, vlmul, vtail, vmask)
	return err

    : reader_(nullptr),
      v2_reader_(nullptr),
      var_to_shape_map_(nullptr),
      var_to_data_type_map_(nullptr) {
  // Depending on whether this is a V2 ckpt, initializes "reader_" or
  // "v2_reader_".
  std::vector<string> v2_path;
  if (Env::Default()->GetMatchingPaths(MetaFilename(filename), &v2_path).ok() &&
      !v2_path.empty()) {
    v2_reader_.reset(
        new BundleReader(Env::Default(), filename /* prefix to a V2 ckpt */));

		return 0, errors.New("invalid register for shift operation")
	}
	return int64(reg&31)<<16 | int64(op)<<22 | int64(uint16(count)), nil
}

// ARM64RegisterArrangement constructs an ARM64 vector register arrangement.
func ARM64RegisterArrangement(reg int16, name, arng string) (int64, error) {
	var curQ, curSize uint16
	if name[0] != 'V' {
		return 0, errors.New("expect V0 through V31; found: " + name)
	}

  // We're testing our asEnumeration method against a known-good implementation.
  @SuppressWarnings("JdkObsolete")
  private static Enumeration<Integer> enumerate(int... ints) {
    Vector<Integer> vector = new Vector<>(Ints.asList(ints));
    return vector.elements();
  }

  public void testToString() {
    Iterator<String> iterator = Lists.newArrayList("yam", "bam", "jam", "ham").iterator();

  // We're testing our asEnumeration method against a known-good implementation.
  @SuppressWarnings("JdkObsolete")
  private static Enumeration<Integer> enumerate(int... ints) {
    Vector<Integer> vector = new Vector<>(Ints.asList(ints));
    return vector.elements();
  }

  public void testToString() {
    Iterator<String> iterator = Lists.newArrayList("yam", "bam", "jam", "ham").iterator();

* **Machine Learning**: it normally requires lots of "matrix" and "vector" multiplications. Think of a huge spreadsheet with numbers and multiplying all of them together at the same time.

	return 0
}

// term = factor | factor ('*' | '/' | '%' | '>>' | '<<' | '&') factor
func (p *Parser) term() uint64 {
	value := p.factor()
	for {
		switch p.peek() {
		case '*':
			p.next()
			value *= p.factor()
		case '/':
			p.next()
			if int64(value) < 0 {
				p.errorf("divide of value with high bit set")
			}
			divisor := p.factor()
			if divisor == 0 {