//	    __u16 nla_len:      13
//	    __u16 nla_type:     NFACCT_NAME
//	    char data:          dummy-metric\0
//	}
//
//	(padding:)
//	    data:               \0\0\0
//
//	struct nlattr{
//	    __u16 nla_len:      12
//	    __u16 nla_type:     NFACCT_PKTS
//	    __u64: data:        123
//	}
//
//	struct nlattr{
//	    __u16 nla_len:      12
//	    __u16 nla_type:     NFACCT_BYTES

  auto tail_type = mlir::dyn_cast<ShapedType>(type1);
  auto full_type = mlir::dyn_cast<ShapedType>(type2);
  if (!tail_type || !full_type || !tail_type.hasRank() ||
      !full_type.hasRank() || tail_type.getRank() > full_type.getRank())
    return false;
  auto i1 = tail_type.getShape().rbegin(), e1 = tail_type.getShape().rend();
  auto i2 = full_type.getShape().rbegin();
  return std::equal(i1, e1, i2);
}

  // Test that full type information can be accessed.
  auto outs = unwrap(add_outputs);
  auto h = outs->outputs[0];
  ASSERT_NE(h, nullptr);
  ASSERT_EQ(h->FullType().type_id(), TFT_UNSET);
  ASSERT_EQ(unwrap(inputs[0])->FullType().type_id(), TFT_UNSET);

  // Clean up operation and inputs.
  TF_DeleteAbstractOp(add_op);

  TF_AbstractFunction* func =

  }
}

// Output `shard_type`, which is the type of each shard, given `full_type`. If
// the full shape is (num_cores_per_replica * a, b, c), then the shard shape is
// (a, b, c). `context_op` is used for error reporting, in case of errors.
LogicalResult GetShardShapedType(Operation* context_op,
                                 int num_cores_per_replica, Type full_type,
                                 Type& shard_type) {

        is DataType.ConstantType<*> -> ObjectReflection.DefaultValue(type, objectOrigin)
        is DataClass -> reflectData(OperationId(-1L, DefaultOperationGenerationId.preExisting), type, objectOrigin, context)
        is DataType.NullType -> error("Null type can't appear in property types")
        is DataType.UnitType -> error("Unit can't appear in property types")
        else -> { error("Unhandled data type: ${type.javaClass.simpleName}") }
    }
}

					auditAnnotationResult.Action = AuditAnnotationActionExclude
				} else {
					auditAnnotationResult.Action = AuditAnnotationActionPublish
					auditAnnotationResult.Value = value
				}
			case celtypes.NullType:
				auditAnnotationResult.Action = AuditAnnotationActionExclude
			default:
				auditAnnotationResult.Action = AuditAnnotationActionError

}

func (v *fakeAuditAnnotationCondition) GetExpression() string {
	return v.ValueExpression
}

func (v *fakeAuditAnnotationCondition) ReturnTypes() []*celgo.Type {
	return []*celgo.Type{celgo.StringType, celgo.NullType}

  using tensorflow::RecordMutation;
  mutex_lock l(graph->mu);
  FullTypeDef full_type;
  full_type.ParseFromArray(full_type_proto->data, full_type_proto->length);
  *op->node.mutable_def()->mutable_experimental_type() = full_type;
  RecordMutation(graph, *op, "setting fulltype");
}

void TF_SetRequestedDevice(TF_Graph* graph, TF_Operation* op,

		{float64(1.2), types.DoubleType},
		{int64(-42), types.IntType},
		{uint64(63), types.UintType},
		{time.Duration(300), types.DurationType},
		{time.Now().UTC(), types.TimestampType},
		{types.NullValue, types.NullType},
		{NewListValue(), types.ListType},
		{NewMapValue(), types.MapType},
		{[]byte("bytes"), types.BytesType},
		{NewObjectValue(objType), objType},
	}
	for i, tc := range tests {
		idx := i
		tst := tc

		return types.Uint(v), UintType, nil
	case time.Duration:
		return types.Duration{Duration: v}, DurationType, nil
	case time.Time:
		return types.Timestamp{Time: v}, TimestampType, nil
	case types.Null:
		return v, NullType, nil
	case *ListValue:
		return v, ListType, nil
	case *MapValue:
		return v, MapType, nil
	case *ObjectValue:
		return v, v.objectType, nil
	default: