// If MaxLen is not 0, make sure MaxLen >= 4.
var MaxLen int

// PrimeRK is the prime base used in Rabin-Karp algorithm.
const PrimeRK = 16777619

// HashStr returns the hash and the appropriate multiplicative
// factor for use in Rabin-Karp algorithm.
func HashStr[T string | []byte](sep T) (uint32, uint32) {
	hash := uint32(0)
	for i := 0; i < len(sep); i++ {
		hash = hash*PrimeRK + uint32(sep[i])
	}

}

// RemoveTarget - removes a remote bucket target for this source bucket.
func (sys *BucketTargetSys) RemoveTarget(ctx context.Context, bucket, arnStr string) error {
	if arnStr == "" {
		return BucketRemoteArnInvalid{Bucket: bucket}
	}

	arn, err := madmin.ParseARN(arnStr)
	if err != nil {
		return BucketRemoteArnInvalid{Bucket: bucket}
	}

	if arn.Type == madmin.ReplicationService {

				netCgo:    true,
			},
			resolv: defaultResolvConf,
			nss:    nssStr(t, "foo: bar"),
			hostTests: []nssHostTest{
				{"foo.local", "myhostname", hostLookupCgo},
				{"google.com", "myhostname", hostLookupCgo},
			},
		},
		{
			name: "netgo_dns_before_files",
			c: &conf{
				netGo: true,
			},
			resolv: defaultResolvConf,
			nss:    nssStr(t, "hosts: dns files"),
			hostTests: []nssHostTest{

}

type goarmFeatures struct {
	Version   int
	SoftFloat bool
}

func (g goarmFeatures) String() string {
	armStr := strconv.Itoa(g.Version)
	if g.SoftFloat {
		armStr += ",softfloat"
	} else {
		armStr += ",hardfloat"
	}
	return armStr
}

func goarm() (g goarmFeatures) {
	const (
		softFloatOpt = ",softfloat"
		hardFloatOpt = ",hardfloat"
	)
	def := defaultGOARM

			}
		})
	}
}

func TestParse(t *testing.T) {
	type args struct {
		arnStr string
	}
	tests := []struct {
		name    string
		args    args
		wantArn ARN
		wantErr bool
	}{
		{
			name: "valid ARN must succeed",
			args: args{
				arnStr: "arn:minio:iam:us-east-1::role/my-role",
			},
			wantArn: ARN{
				Partition:    "minio",
				Service:      "iam",

					val = fmt.Sprintf("%#v", out)
				} else {
					val = fmt.Sprintf("%T(%v)", out, out)
				}
				fmt.Fprintf(&buf, "\t%s, // %s(%s)\n", val, m.Name, argstr)
			} else if p >= len(regressGolden) {
				t.Errorf("r.%s(%s) = %v, missing golden value", m.Name, argstr, out)
			} else {
				want := regressGolden[p]
				if m.Name == "Int" {
					want = int64(int(uint(want.(int64)) << 1 >> 1))
				}
				if m.Name == "Uint" {

        for (Object argument : arguments) {
            String argStr = argument.toString();

            if (argStr.equals("-ea") || argStr.equals("-enableassertions")) {
                assertionsEnabled = true;
            } else if (argStr.equals("-da") || argStr.equals("-disableassertions")) {
                assertionsEnabled = false;
            } else if (argStr.startsWith(XMS_PREFIX)) {

    std::string name = "Conj_Exp_Grad";
    TF_RETURN_IF_ERROR(SafeConj(ctx, exp_.get(), &conj_output, name.c_str()));
    AbstractTensorHandlePtr conj_output_releaser(conj_output);

    name = "Mul_Exp_Grad";
    TF_RETURN_IF_ERROR(
        Mul(ctx, conj_output, grad_outputs[0], &grad_inputs[0], name.c_str()));
    return absl::OkStatus();
  }
  ~ExpGradientFunction() override {}

 private:

    // CHECK: [[exe:%.*]] = tf_executor.island({{.*}}) wraps "tf.TPUExecuteAndUpdateVariables"
    %exe_control = tf_executor.island wraps "tf.TPUExecuteAndUpdateVariables"(%arg0, %arg0, %key) {
        device_var_reads_indices = [0, 1],
        device_var_updates_indices = [0, 1],
        device = "task:0"
    } : (!tf_res, !tf_res, !tf_str) -> ()

	MOVD	res+0(FP), res_ptr
	MOVD	in+8(FP), a_ptr

	MOVD	p256const0<>(SB), const0
	MOVD	p256const1<>(SB), const1

	// Begin point double
	LDP	4*16(a_ptr), (x0, x1)
	LDP	5*16(a_ptr), (x2, x3)
	CALL	p256SqrInternal<>(SB)
	STP	(y0, y1), zsqr(0*8)
	STP	(y2, y3), zsqr(2*8)

	LDP	0*16(a_ptr), (x0, x1)
	LDP	1*16(a_ptr), (x2, x3)
	p256AddInline
	STx(m)

	LDx(z1in)