Method AddOperation

tensorflow/go/graph.go:280–334

AddOperation adds an operation to g.

(args OpSpec)

// AddOperation adds an operation to g.
func (g *Graph) AddOperation(args OpSpec) (*Operation, error) {
	if args.Name == "" {
		args.Name = args.Type
	}
	cname := C.CString(args.Name)
	ctype := C.CString(args.Type)
	cdesc := C.TF_NewOperation(g.c, ctype, cname)
	C.free(unsafe.Pointer(cname))
	C.free(unsafe.Pointer(ctype))

	for _, in := range args.Input {
		switch in := in.(type) {
		case Output:
			C.TF_AddInput(cdesc, in.c())
		case OutputList:
			size := len(in)
			list := make([]C.TF_Output, size)
			for i, v := range in {
				list[i] = v.c()
			}
			if size > 0 {
				C.TF_AddInputList(cdesc, &list[0], C.int(size))
			} else {
				C.TF_AddInputList(cdesc, nil, 0)
			}
		}
	}
	for _, in := range args.ControlDependencies {
		C.TF_AddControlInput(cdesc, in.c)
	}
	status := newStatus()
	for name, value := range args.Attrs {
		if err := setAttr(cdesc, status, name, value); err != nil {
			// Memory leak here as the TF_OperationDescription
			// object will not be cleaned up. At the time of this
			// writing, this was next to impossible since it
			// required value to be a string tensor with
			// incorrectly encoded strings. Given this rarity, live
			// with the memory leak.  If it becomes a real problem,
			// consider adding a TF_DeleteOperationDescription
			// function to the C API.
			return nil, fmt.Errorf("%v (memory will be leaked)", err)
		}
	}
	if len(args.Device) > 0 {
		cdevice := C.CString(args.Device)
		C.TF_SetDevice(cdesc, cdevice)
		C.free(unsafe.Pointer(cdevice))
	}
	c := C.TF_FinishOperation(cdesc, status.c)
	if err := status.Err(); err != nil {
		return nil, err
	}
	return &Operation{c, g}, nil
}

func setAttr(cdesc *C.TF_OperationDescription, status *status, name string, value interface{}) error {
	cAttrName := C.CString(name)