Exception: Remote functions cannot be called directly.

[lunasdejavu]

System information

• OS Platform and Distribution (e.g., Linux Ubuntu 16.04):ubuntu16.04
• Ray installed from (source or binary): pip install
• Ray version:0.7.5
• Python version:3.6
• Exact command to reproduce:

Describe the problem

I am trying to do reading a dictionary by a for loop every loop will call a function which there are three functions to be run by ray but I met the error

 File "lp_analysis.py", line 267, in evaluation
    eval_ids.append(eval_lpd(real_name_list, sorted_lpr_names, sorted_boxes, img_path).remote())
  File "/usr/local/lib/python3.6/dist-packages/ray/remote_function.py", line 92, in __call__
    self._function_name, self._function_name))
Exception: Remote functions cannot be called directly. Instead of running '__main__.eval_lpd()', try '__main__.eval_lpd.remote()'

Source code / logs

@ray.remote
def eval_lpd(lps_gt,lps_prd_sort, boxes, path):
    global Result
    flag = 0
    for i  in range(len(lps_prd_sort)):
        if lps_prd_sort[i] == '' or i >= len(lps_gt):
            Result['detection']['fp'] += 1
            Result['detection']['fp path'].append(path)
            Result['detection']['fp box'].append(boxes[i])
            flag = 1
        else:
            Result['detection']['tp'] += 1
        Result['detection']['total'] += 1
    return flag
@ray.remote
def eval_lpr(lps_prd, lps_gt, boxes, path):
    # print(lps_gt, lps_prd, boxes, path)
    global Result
    flag = 0 # if all license plates are correct flag = 0
    for i in range(len(lps_gt)):
        if lps_prd[i] != '':
            flag2 = 0 # if one of license plate correct flag2 = 1
            result = list(difflib.Differ().compare(lps_prd[i], lps_gt[i]))
            for act in result:
                # print(act)
                if act[0] == '-':
                    Result['recognition']['fp'][CLASSES_RECOGNITION.index(act[2])] += 1
                    Result['recognition']['fp path'][CLASSES_RECOGNITION.index(act[2])].append(path)
                    Result['recognition']['fp box'][CLASSES_RECOGNITION.index(act[2])].append(boxes)
                    flag2 = 1
                    flag = 1
                elif act[0] == '+':
                    Result['recognition']['fn'][CLASSES_RECOGNITION.index(act[2])] += 1
                    Result['recognition']['fn path'][CLASSES_RECOGNITION.index(act[2])].append(path)
                    Result['recognition']['fn box'][CLASSES_RECOGNITION.index(act[2])].append(boxes)
                    flag2 = 1
                    flag = 1
                elif act[0] == ' ':
                    Result['recognition']['tp'][CLASSES_RECOGNITION.index(act[2])] += 1
                else:
                    print("error:", act)
                Result['recognition']['total'][CLASSES_RECOGNITION.index(act[2])] += 1
        else :
            flag2 = 1
            flag = 1
        if flag2 == 0:
            Result['recognition']['correct'] += 1

    return flag
@ray.remote
def eval_lpf(fmts, real_fmts, boxes, path):
    global Result
    flag = 0 # if all license plates are correct flag = 0
    for i in range(len(real_fmts)):
 # if one of license plate correct flag2 = 1
        if fmts[i] == real_fmts[i]:
            Result['classification']['tp'][fmts[i]] += 1
        elif real_fmts[i] != 7:
            flag = 1
            Result['classification']['fp'][fmts[i]] += 1
            Result['classification']['fp path'][fmts[i]].append(path)
            Result['classification']['fp box'][fmts[i]].append(boxes)
            Result['classification']['fn'][real_fmts[i]] += 1
            Result['classification']['fn path'][real_fmts[i]].append(path)
            Result['classification']['fn box'][real_fmts[i]].append(boxes)
        if real_fmts[i] == 7 or fmts[i] == 7:
            Result['broke'] += 1
            Result['broke path'].append(path)
            Result['broke loc'].append(i)
        Result['classification']['total'][real_fmts[i]] += 1
    return flag

def evaluation(lpr_names, fmts, img_path, boxes):
    print ("eval input:", lpr_names, fmts, img_path, boxes)
    #generate ground_truth
    real_name_list, real_name_list_no_dash, real_fmts = get_real_names(img_path)
    # print("real", real_name_list, real_name_list_no_dash, real_fmts)
    #sort the results of lpr & lpf to compare with ground trouth
    sorted_lpr_names, sorted_fmts, sorted_boxes = sort_lvst(real_name_list_no_dash, lpr_names, fmts, boxes)
    # print("sort", sorted_lpr_names, sorted_fmts, sorted_boxes)

    eval_ids =[]
    #evaluation for lpd
    eval_ids.append(eval_lpd(real_name_list, sorted_lpr_names, sorted_boxes, img_path).remote())
    #evaluation for lpr
    eval_ids.append(eval_lpr(sorted_lpr_names, real_name_list_no_dash, sorted_boxes, img_path).remote())
    #evaluation for lpf
    eval_ids.append(eval_lpf(sorted_fmts, real_fmts, sorted_boxes, img_path).remote())
    evals = ray.get(eval_ids)
    if (eval_ids[0] or eval_ids[1] or eval_ids[2]) == 1:
        return 0
    else:   
        return 1

    for data in inference_result:
        # lpd didn't find any license plate under the threshold
        if not data['Boxes']:
            Result['detection']['fn'] += 1
            Result['detection']['fn path'].append(path)
            continue
        if evaluation(data['Names'], data['Fmts'], data['Image path'], data['Boxes']) == 1 :
            Result['failed images'] += 1
            Result['failed path'].append(img_path)

[fyrestone]

try eval_ids.append(eval_lpd.remote(real_name_list, sorted_lpr_names, sorted_boxes, img_path))

[lunasdejavu]

try eval_ids.append(eval_lpd.remote(real_name_list, sorted_lpr_names, sorted_boxes, img_path))

thanks! it works!