ASSERT_EQ(errors::OK, s.code()) << s.message();
    ctx.reset(ctx_raw);
  }

  AbstractTensorHandlePtr x;
  {
    AbstractTensorHandle* x_raw = nullptr;
    Status s = TestScalarTensorHandle<float, TF_FLOAT>(ctx.get(), 2.0f, &x_raw);
    ASSERT_EQ(errors::OK, s.code()) << s.message();
    x.reset(x_raw);
  }

  Status s = RunModel(TestScalarShape, ctx.get(),

	if buf.Len() > m {
		t.Log("WARNING: TestEncodeDecodelocalLockMap Msgsize() is inaccurate")
	}

	vn := localLockMap{}
	err := msgp.Decode(&buf, &vn)
	if err != nil {
		t.Error(err)
	}

	buf.Reset()
	msgp.Encode(&buf, &v)
	err = msgp.NewReader(&buf).Skip()
	if err != nil {
		t.Error(err)
	}
}

func BenchmarkEncodelocalLockMap(b *testing.B) {
	v := localLockMap{}
	var buf bytes.Buffer

    Range(&vals, 0, num_dims_out);
    AbstractTensorHandle* sum_dims_raw = nullptr;
    TF_RETURN_IF_ERROR(TestTensorHandleWithDims<int32_t, TF_INT32>(
        ctx, vals.data(), vals_shape, 1, &sum_dims_raw));
    sum_dims.reset(sum_dims_raw);
  }

  // Reduce sum the output on all dimensions.
  TF_RETURN_IF_ERROR(ops::Sum(ctx, model_out.get(), sum_dims.get(), &outputs[0],
                              /*keep_dims=*/false, "sum_output"));

class WorkerCacheInterface;

class ImmediateExecutionDistributedManager {
 public:
  virtual ~ImmediateExecutionDistributedManager() {}

  // Set up distributed execution environment on local and remote tasks.
  // When `reset_context` is true, initialize new cluster context state based
  // on cluster configurations provided in `server_def`; otherwise, update
  // existing context state with the provided `server_def`. Contexts created

	for {
		select {
		case <-ctx.Done():
			return
		case <-licenseUpdateTimer.C:

			if globalSubnetConfig.Registered() {
				performLicenseUpdate(ctx, objAPI)
			}

			// Reset the timer for next cycle.
			licenseUpdateTimer.Reset(licUpdateCycle)
		}
	}
}

func performLicenseUpdate(ctx context.Context, objectAPI ObjectLayer) {
	// the subnet license renewal api renews the license only

	if buf.Len() > m {
		t.Log("WARNING: TestEncodeDecodeBaseOptions Msgsize() is inaccurate")
	}

	vn := BaseOptions{}
	err := msgp.Decode(&buf, &vn)
	if err != nil {
		t.Error(err)
	}

	buf.Reset()
	msgp.Encode(&buf, &v)
	err = msgp.NewReader(&buf).Skip()
	if err != nil {
		t.Error(err)
	}
}

func BenchmarkEncodeBaseOptions(b *testing.B) {
	v := BaseOptions{}
	var buf bytes.Buffer

			if len(healDisks) == 0 {
				// Reset for next interval.
				diskCheckTimer.Reset(defaultMonitorNewDiskInterval)
				continue
			}

			// Reformat disks immediately
			_, err := z.HealFormat(context.Background(), false)
			if err != nil && !errors.Is(err, errNoHealRequired) {
				healingLogIf(ctx, err)
				// Reset for next interval.
				diskCheckTimer.Reset(defaultMonitorNewDiskInterval)
				continue
			}

		t.Errorf("Failed, got error: %v", err)
	}
}

func TestPreparedStmtReset(t *testing.T) {
	tx := DB.Session(&gorm.Session{PrepareStmt: true})

	user := *GetUser("prepared_stmt_reset", Config{})
	tx = tx.Create(&user)

	pdb, ok := tx.ConnPool.(*gorm.PreparedStmtDB)
	if !ok {
		t.Fatalf("should assign PreparedStatement Manager back to database when using PrepareStmt mode")
	}

    ASSERT_EQ(errors::OK, status_.code()) << status_.message();
    x1.reset(x1_raw);
  }

  AbstractTensorHandlePtr x2;
  {
    AbstractTensorHandle* x2_raw = nullptr;
    status_ = TestScalarTensorHandle<float, TF_FLOAT>(
        immediate_execution_ctx_.get(), 1.0f, &x2_raw);
    ASSERT_EQ(errors::OK, status_.code()) << status_.message();
    x2.reset(x2_raw);
  }

	if buf.Len() > m {
		t.Log("WARNING: TestEncodeDecodeDailyAllTierStats Msgsize() is inaccurate")
	}

	vn := DailyAllTierStats{}
	err := msgp.Decode(&buf, &vn)
	if err != nil {
		t.Error(err)
	}

	buf.Reset()
	msgp.Encode(&buf, &v)
	err = msgp.NewReader(&buf).Skip()
	if err != nil {
		t.Error(err)
	}
}

func BenchmarkEncodeDailyAllTierStats(b *testing.B) {
	v := DailyAllTierStats{}
	var buf bytes.Buffer