p.expect('.')
		isVariadic = true
	}
	typ := p.parseType(pkg)
	if isVariadic {
		typ = types.NewSlice(typ)
	}
	param = types.NewParam(token.NoPos, pkg, name, typ)
	return
}

// Var = Name Type .
func (p *parser) parseVar(pkg *types.Package) *types.Var {
	name := p.parseName()
	v := types.NewVar(token.NoPos, pkg, name, p.parseType(pkg))
	if name[0] == '.' || name[0] == '<' {

		return errMalformedXML(err)
	}

	parsedType := CompressionType(strings.ToUpper(s))
	if s == "" || parsedType == "NONE" {
		parsedType = noneType
	}

	switch parsedType {
	case noneType, gzipType, bzip2Type, snappyType, s2Type, zstdType, lz4Type:
	default:
		return errInvalidCompressionFormat(fmt.Errorf("invalid compression format '%v'", s))
	}

	*c = parsedType
	return nil
}

  for (auto &hook : GetAdditionalOperationHooks()) {
    hook.second(*this);
  }
}

TensorFlowDialect::~TensorFlowDialect() {
  delete fallback_effect_op_interface_;
}

Type TensorFlowDialect::parseType(DialectAsmParser &parser) const {
  StringRef spec = parser.getFullSymbolSpec();
  llvm::SMLoc loc = parser.getCurrentLocation();
  parser.emitError(
      loc, "tf dialect has no types, potentially meant !tf_type." + spec);

//                 | `tensor<` (string-literal | string_list)  '>'
//   tensor_list_type ::= `tensor_list`
//                      | `tensor_list<` (string-literal | string_list)  '>'
//   attr_type ::= `attr`
Type TFRDialect::parseType(DialectAsmParser &parser) const {
  Location loc = parser.getEncodedSourceLoc(parser.getNameLoc());
  MLIRContext *ctx = loc.getContext();

  StringRef typeNameSpelling;

      >();

  addInterfaces<TensorFlowExecutorInlinerInterface,
                TensorFlowExecutorDialectFoldInterface>();

  addTypes<ControlType, TokenType>();
}

Type TensorFlowExecutorDialect::parseType(DialectAsmParser &parser) const {
  StringRef data_type;
  if (parser.parseKeyword(&data_type)) return Type();

  if (data_type == "control") return ControlType::get(getContext());