// TODO(b/329300758): add file check back after the cl is fixed | FileCheck %s
// Check a few basic properties of the import-export,
// including constants retaining their shape
// and the module including the TFLite version.

func.func @main(tensor<3x2xi32>) -> tensor<3x2xi32> {
^bb0(%arg0: tensor<3x2xi32>):
  // CHECK: module attributes

import javax.annotation.Resource;

import org.apache.logging.log4j.LogManager;
import org.apache.logging.log4j.Logger;
import org.codelibs.core.lang.StringUtil;
import org.codelibs.core.net.URLUtil;
import org.codelibs.fess.Constants;
import org.codelibs.fess.app.web.base.FessSearchAction;
import org.codelibs.fess.app.web.error.ErrorAction;
import org.codelibs.fess.crawler.util.CharUtil;
import org.codelibs.fess.es.log.exentity.ClickLog;

      objects->variables[i] = std::move(variable);
    } else if (node.kind_case() == SavedObject::kConstant) {
      std::unique_ptr<Constant> constant;
      TF_RETURN_IF_ERROR(ConstantFromSavedConstant(context, node.constant(),
                                                   node_attr_map, &constant));
      objects->constants[i] = std::move(constant);
    } else if (node.kind_case() == SavedObject::kAsset) {
      std::unique_ptr<Asset> asset;

  // time, a module may have constants that need to be restored.  To restore
  // these constants, they are looked up in the GraphDef's nodes by their name.
  // Since we may need to load many constants, we create a hash map of these
  // names to their corresponding nodes at load time in order to look them up
  // in constant time.
  tensorflow::StatusOr<const tensorflow::NodeDef*> GetGraphDefNode(

	assert(obj.typ == nil)

	// use the correct value of iota and errpos
	defer func(iota constant.Value, errpos syntax.Pos) {
		check.iota = iota
		check.errpos = errpos
	}(check.iota, check.errpos)
	check.iota = obj.val
	check.errpos = nopos

	// provide valid constant value under all circumstances
	obj.val = constant.MakeUnknown()

	// determine type, if any
	if typ != nil {
		t := check.typ(typ)

        then:
        deps.getAccessibleDependentClasses() == ["Bar"] as Set
        deps.getPrivateDependentClasses() == ["BarBar"] as Set
    }

    def "find class constant dependents when constants hash analysis returns empty set"() {
        given:
        def a = analysis(
            [:], [:], empty(), empty(), null,

#include "textflag.h"

// Register definitions
#define Rtable	R0	// Pointer to MD5 constants table
#define Rdata	R1	// Pointer to data to hash
#define Ra	R2	// MD5 accumulator
#define Rb	R3	// MD5 accumulator
#define Rc	R4	// MD5 accumulator
#define Rd	R5	// MD5 accumulator
#define Rc0	R6	// MD5 constant
#define Rc1	R7	// MD5 constant
#define Rc2	R8	// MD5 constant
// r9, r10 are forbidden

  }
};

// Inserts a "quant.qcast" and "quant.dcast" op pair (QDQs) in place of the
// tf.FakeQyantWithMinMax{Vars|VarsPerChannel|Args}Op
// before the op being constant folded. Since the constant
// folding logic will use a "arith.constant" op to replace the
// "tf.FakeQuantWithMinMaxVarsOp", the "quant.qcast" op is used to preserve
// the quantization parameters as a TypeAttr and "quant.dcast" op used to

// language object (Object) it denotes.
// Use Info.{Defs,Uses,Implicits} for the results of name resolution.
//
// Constant folding computes the exact constant value (constant.Value)
// for every expression (syntax.Expr) that is a compile-time constant.
// Use Info.Types[expr].Value for the results of constant folding.
//
// Type inference computes the type (Type) of every expression (syntax.Expr)

  retvals.reserve(num_retvals);
  for (Node* n : graph->nodes()) {
    if (n->type_string() == "_Arg") {
      // Check if this is a guaranteed constant.
      if (is_guaranteed_constant(*n)) {
        return errors::InvalidArgument(
            "Guaranteed constants are not supported (", n->name(), ")");
      }
      args.push_back(n);
    } else if (n->type_string() == "_Retval") {
      retvals.push_back(n);
    }