x86调用转换的MobileNet-SSD的caffemodel模型，调用net_executer时concat层出错。在caffe SSD里面mbox_priorbox的concat层的输入是3维的，在AK里面输入是4维了，concat的参数axis: 2就不对了。这种问题是模型转换有问题吗？

[whongjob]

我用x86调用转换后的MobileNet-SSD模型，在concat层出错。是模型转换哪里出错了吗？
错误信息：
WAN| 16:44:19.00789| 0.078s| AC143780| x86_device.cpp:27] X86 get_info is not implemented
WAN| 16:44:19.00789| 0.078s| AC143780| net.cpp:667] Current used device id : 0
WAN| 16:44:19.00790| 0.079s| AC143780| input.cpp:16] Parsing Input op parameter.
0| 16:44:19.00790| 0.079s| AC143780| input.cpp:19] |-- shape [0]: 1
0| 16:44:19.00790| 0.079s| AC143780| input.cpp:19] |-- shape [1]: 3
0| 16:44:19.00790| 0.079s| AC143780| input.cpp:19] |-- shape [2]: 300
0| 16:44:19.00790| 0.079s| AC143780| input.cpp:19] |-- shape [3]: 300
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00791| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00791| 0.080s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00792| 0.080s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00792| 0.080s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00792| 0.080s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00792| 0.080s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00792| 0.081s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00792| 0.081s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00792| 0.081s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [3]: 1
WAN| 16:44:19.00792| 0.081s| AC143780| permute.cpp:20] !!!!!!!! Parsing Permute op parameter.
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [0]: 0
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [1]: 2
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [2]: 3
0| 16:44:19.00792| 0.081s| AC143780| permute.cpp:24] |-- dims [3]: 1
FTL| 16:44:19.00799| 0.088s| AC143780| concat.h:101] Check failed:shape_out[j] == sh[j] (4332 == 2400) All inputs must have the same shape, except at concat_axis.
*** Check failed:shape_out[j] == sh[j] (4332 == 2400) fatal error stack trace: ***:

[Hub-er]

打印concat层的shape信息。

[whongjob]

出错的层：
layer {
name: "mbox_priorbox"
type: "Concat"
bottom: "conv4_3_norm_mbox_priorbox"
bottom: "fc7_mbox_priorbox"
bottom: "conv6_2_mbox_priorbox"
bottom: "conv7_2_mbox_priorbox"
bottom: "conv8_2_mbox_priorbox"
bottom: "conv9_2_mbox_priorbox"
top: "mbox_priorbox"
concat_param {
axis: 2
}
}
在AK里concat层的shape打印信息：
input_size: 6 param.axis: 2
input 0 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:4332
input 1 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:2400
input 2 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:600
input 3 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:216
input 4 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:96
input 5 dims(): 4
dim[0]:1
dim[1]:1
dim[2]:2
dim[3]:24
我感觉是caffe SSD里面输入是3维的，concat参数是2，到了AK里面输入变成4维了，参数还是2就不对了。这种情况是模型转换不对吗？
请求帮助，感谢！

[MyPandaShaoxiang]

是的，请用最新的master分支进行重新转换