return false;
                    }

                    // Only compile nodes that are marked for compilation by the
                    // compilation-marking pass (via 'attr_name').
                    return IsXlaCompiledKernel(*n);
                  });

  bool lazy_compilation_enabled =
      enable_lazy_compilation_
          ? *enable_lazy_compilation_

  auto check = [&](mlir::Value val, std::string attr_name) -> LogicalResult {
    ElementsAttr attr;
    if (matchPattern(val, m_Constant(&attr))) {
      if (attr.getShapedType().getRank() != 1) {
        return op.emitOpError()
               << "expects the rank of " << attr_name << "to be 1, got "
               << attr.getShapedType().getRank();
      }

//
// Analogous to TF_SetAttrValueProto for building graph operations.
TF_CAPI_EXPORT extern void TFE_OpSetAttrValueProto(const TFE_Op* op,
                                                   const char* attr_name,
                                                   const void* proto,
                                                   size_t proto_len,
                                                   TF_Status* status);

// That will require setting up the tensorflow build with gmock.
#define EXPECT_TF_META(attr_name, expected_list_size, expected_type, \
                       expected_total_size)                          \
  do {                                                               \
    auto m = TF_OperationGetAttrMetadata(oper, attr_name, s_);       \
    EXPECT_EQ(TF_OK, TF_GetCode(s_)) << TF_Message(s_);              \

  }
  return result;
}

// Helper method that return list of string for all the StringAttr in the
// Attribute identified by 'attr_name'.
std::vector<std::string> GetStringsFromDictionaryAttr(
    const llvm::SmallVector<mlir::DictionaryAttr, 4>& dict_attrs,
    const StringRef attr_name) {
  std::vector<std::string> result;
  for (const auto& arg_attr : dict_attrs) {
    if (!arg_attr) continue;

	26:  _Attr_name[121:130],
	27:  _Attr_name[130:137],
	28:  _Attr_name[137:147],
	29:  _Attr_name[147:161],
	30:  _Attr_name[161:173],
	32:  _Attr_name[173:179],
	33:  _Attr_name[179:189],
	34:  _Attr_name[189:199],
	37:  _Attr_name[199:207],
	39:  _Attr_name[207:217],
	42:  _Attr_name[217:227],
	44:  _Attr_name[227:237],
	46:  _Attr_name[237:247],
	47:  _Attr_name[247:257],

      %out_c, %out_tensor = "tfd.delegate_kernel"(
        %in_c, %in1_tensor, %in2_tensor) {
        _name = "MatMul",
        attr1_name = "transpose_a", attr1_value = "bool$false",
        attr2_name = "transpose_b", attr2_value = "bool$false"
      } : (!tfrt.chain, !tfd.tf_tensor, !tfd.tf_tensor) -> (
        !tfrt.chain, !tfd.tf_tensor)
  }];

        String tag = "tag", id = "id", css = "css", attrName = "attrName", attrValue = "attrValue";
        PrunedTag prunedtag = new PrunedTag(tag);
        prunedtag.setAttr(attrName, attrValue);
        prunedtag.setId(id);
        prunedtag.setCss(css);
        assertEquals("PrunedTag [tag=" + tag + ", id=" + id + ", css=" + css + ", attrName=" + attrName + ", attrValue=" + attrValue + "]",
                prunedtag.toString());

			err:   errorf(ErrBadHTML, nil, 0, "expected space, attr name, or end of tag, but got %q", s[i:]),
		}, len(s)
	}

	attrName := strings.ToLower(string(s[i:j]))
	if c.element == elementScript && attrName == "type" {
		attr = attrScriptType
	} else {
		switch attrType(attrName) {
		case contentTypeURL:
			attr = attrURL
		case contentTypeCSS:
			attr = attrStyle
		case contentTypeJS:
			attr = attrScript

    private String css;
    private String attrName;
    private String attrValue;

    public PrunedTag(final String tag) {
        this.tag = tag;
    }

    public boolean matches(final Node node) {
        if (tag.equalsIgnoreCase(node.getNodeName())) {
            if (attrName != null) {
                final Node attr = node.getAttributes().getNamedItem(attrName);