TFL_TensorOf<[F32, I8]>:$fw_recurrent_to_output_weights,

    // Forward Cell weights
    TFL_TensorOfOrNone<[F32, I8]>:$fw_cell_to_input_weights,
    // Optional Forward cell weights
    TFL_TensorOfOrNone<[F32, I8]>:$fw_cell_to_forget_weights,
    // Optional Forward cell weights
    TFL_TensorOfOrNone<[F32, I8]>:$fw_cell_to_output_weights,

    // Forward Bias

	}
	return
}

func validateRouteDestinations(weights []*networking.RouteDestination, gatewaySemantics bool) (errs error) {
	var totalWeight int32
	for _, weight := range weights {
		if weight == nil {
			errs = multierror.Append(errs, errors.New("weight may not be nil"))
			continue
		}
		if weight.Destination == nil {

  // expected-error @+1 {{'tfl.unidirectional_sequence_lstm' op failed to verify that either projection weight must be specified or both projection weight and projection bias must not be specified}}

			}

			if tt.expectedLocalityWeightedConfig && c.CommonLbConfig.GetLocalityWeightedLbConfig() == nil {
				t.Errorf("cluster expected to have weighed config, but is nil")
			}
			if tt.expectClusterLoadAssignmenttoBeNil && c.LoadAssignment != nil {
				t.Errorf("cluster expected not to have load assignmentset, but is present")
			}
		})
	}
}

  let constructor = "TFTPU::CreateTPUColocateSplitsPass()";
  let description = [{
    It is beneficial for performance to assign a `Split` op to the same device
    as its predecessor. This is because the weight of cut edges is always
    minimized when the `Split` is with its predecessor. This colocation
    constraint will be used by the placer graph optimization to assign a device
    to the op.