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;

// CHECK:         [[CONSTANT:%.*]] = s32[0]{0} constant({})
// CHECK:         ROOT %tuple.{{[0-9]+}} = (s32[0]{0}, s32[0]{0}) tuple(s32[0]{0} [[CONSTANT]], s32[0]{0} [[CONSTANT]])
// CHECK:       }

// NO_TUPLES-LABEL: HloModule main
// NO_TUPLES:       ENTRY %main.{{[0-9+]}} () -> (s32[0], s32[0]) {
// NO_TUPLES:         [[CONSTANT:%.*]] = s32[0]{0} constant({})

      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(

		fmt.Println("Error running featuresgen on file: ", pwd, "/", input)
		panic(err)
	}

	constants := readVal(m, make([]string, 0))
	// The parsing of the yaml file doesn't seem to happen in a consistent order. To avoid a different file every time 'make gen' is run, we sort the list.
	sort.Strings(constants)
	return strings.Join(constants, "\n")
}

func check(err error) {
	if err != nil {
		panic(err)
	}
}

	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,

// CHECK-NEXT:      shape: [ 5 ],
// CHECK-NEXT:      buffer: 3,
// CHECK-NEXT:      name: "arith.constant",
// CHECK-NEXT:      quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:      },
// CHECK-NEXT:      has_rank: true
// CHECK-NEXT:    }, {
// CHECK-NEXT:      shape: [ 5, 3 ],
// CHECK-NEXT:      buffer: 4,
// CHECK-NEXT:      name: "arith.constant1",
// CHECK-NEXT:      quantization: {
// CHECK-EMPTY:
// CHECK-NEXT:      },

#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