case *networking.StringMatch_Exact:
		return &matcher.StringMatcher{MatchPattern: &matcher.StringMatcher_Exact{Exact: m.Exact}}
	case *networking.StringMatch_Prefix:
		return &matcher.StringMatcher{MatchPattern: &matcher.StringMatcher_Prefix{Prefix: m.Prefix}}
	case *networking.StringMatch_Regex:
		return &matcher.StringMatcher{
			MatchPattern: &matcher.StringMatcher_SafeRegex{
				SafeRegex: &matcher.RegexMatcher{

  // Get the tensors.
  DenseElementsAttr input_tensor, weights_tensor, bias_tensor;
  if (!matchPattern(getInput(), m_Constant(&input_tensor)) ||
      !matchPattern(getFilter(), m_Constant(&weights_tensor)) ||
      (has_bias && !matchPattern(getBias(), m_Constant(&bias_tensor)))) {
    return failure();
  }

  // Get the tensor types.

LogicalResult QuantizedConstRewrite::matchAndRewrite(
    QuantizeCastOp qbarrier, PatternRewriter &rewriter) const {
  Attribute value;

  // Is the operand a constant?
  if (!matchPattern(qbarrier.getArg(), m_Constant(&value))) {
    return failure();
  }

  // Does the qbarrier convert to a quantized type. This will not be true

	if m.IsLiteral() {
		m.Pkgs = []string{m.pattern}
		return
	}

	match := func(string) bool { return true }
	treeCanMatch := func(string) bool { return true }
	if !m.IsMeta() {
		match = pkgpattern.MatchPattern(m.pattern)
		treeCanMatch = pkgpattern.TreeCanMatchPattern(m.pattern)
	}

	have := map[string]bool{
		"builtin": true, // ignore pseudo-package that exists only for documentation
	}

// data so that the iota dimension does not need to be the (inner) z-dimension.
bool MatchIotaConst(DenseIntElementsAttr dimensions, Value iota) {
  DenseIntElementsAttr iota_const_attr;
  if (!matchPattern(iota, m_Constant(&iota_const_attr))) return false;

  auto iota_type = iota_const_attr.getType();
  auto iota_shape = iota_type.getShape();
  auto reduce_dim = (*dimensions.value_begin<APInt>()).getSExtValue();

  LogicalResult matchAndRewrite(mlir::stablehlo::UniformQuantizeOp op,
                                PatternRewriter& rewriter) const override {
    DenseFPElementsAttr attr;
    if (matchPattern(op.getOperand(), m_Constant(&attr))) {
      const Type qtype = op.getResult().getType();
      ElementsAttr quantized_attr = Quantize(attr, qtype);
      if (quantized_attr) {

    ElementsAttr block_shape;
    ElementsAttr paddings;
    llvm::SmallVector<int64_t, 4> block_shape_ints;
    auto padded_shape = llvm::to_vector<4>(input_shape);
    if (matchPattern(op.getBlockShape(), m_Constant(&block_shape)) &&
        matchPattern(op.getPaddings(), m_Constant(&paddings))) {
      for (uint64_t i = 0; i < block_rank; i++) {
        int64_t paddings_sum =
            paddings.getValues<APInt>()[{i, 0}].getSExtValue() +

            op->getOperand(qi).getDefiningOp());
        if (!const_op) {
          continue;
        }

        DenseFPElementsAttr attr;
        if (!matchPattern(const_op->getResult(0), m_Constant(&attr))) {
          continue;
        }

        if (mlir::dyn_cast<DenseFPElementsAttr>(attr).size() >=
            quant_specs_.minimum_elements_for_weights) {

                            SmallVectorImpl<int64_t>& s0_shape,
                            SmallVectorImpl<int64_t>& s1_shape) {
  if (!matchPattern(op.getS0(), m_Constant(&s0))) return false;
  if (!matchPattern(op.getS1(), m_Constant(&s1))) return false;

  for (auto s : s0.getValues<APInt>()) s0_shape.push_back(s.getSExtValue());

    DenseIntElementsAttr strides_elem_attr;

    if (!begin_attr_type ||
        !matchPattern(begin_attr, m_Constant(&begin_elem_attr))) {
      return failure();
    }
    if (!end_attr_type || !matchPattern(end_attr, m_Constant(&end_elem_attr))) {
      return failure();
    }
    if (!strides_attr_type ||
        !matchPattern(strides_attr, m_Constant(&strides_elem_attr))) {
      return failure();
    }