DS4.0 TX2 yolov3 maxpool parsing error

Hello,
I’m using DS4.0 to run slimyolov3.

But there is error, I found the maxpool will diminished input layer dimensions(w,h) when maxpool size greater than 2.

for example:
1.[maxpool]
stride=1
size=5

2.input–>12 x 19 x 19

3.output diminished -->12 x 15 x 15

How solve this problem? I want to keep output dimensions(w,h) no changed.

(76)  conv-bn-leaky   864 x  19 x  19      11 x  19 x  19    10909193
(77)  conv-bn-leaky    11 x  19 x  19      33 x  19 x  19    10912592
(78)  conv-bn-leaky    33 x  19 x  19      12 x  19 x  19    10913036
(79)  maxpool          12 x  19 x  19      12 x  15 x  15    10913036
(80)  route                  -             12 x  19 x  19    10913036
(81)  maxpool          12 x  19 x  19      12 x  11 x  11    10913036
(82)  route                  -             12 x  19 x  19    10913036
(83)  maxpool          12 x  19 x  19      12 x   7 x   7    10913036
0:00:03.133510912  8139   0x558c324260 ERROR                nvinfer gstnvinfer.cpp:511:gst_nvinfer_logger:<primary_gie_classifier> NvDsInferContext[UID 1]:log(): route_83: all concat input tensors must have the same dimensions except on the concatenation axis

Hello,
I have added "m_TinyMaxpoolPaddingFormula->addSamePaddingLayer(“maxpool_” + std::to_string(i)) in yolo.cpp to fix this issue ,is it right?

I’m also have a new error of “Number of unused weights left : 13824”,how to solve this issue?

(125) conv-linear      63 x  76 x  76      45 x  76 x  76    11100680
(126) yolo             45 x  76 x  76      45 x  76 x  76    11100680
Number of unused weights left : 13824
deepstream-app: yolo.cpp:361: nvinfer1::INetworkDefinition* Yolo::createYoloNetwork(std::vector<float>&, std::vector<nvinfer1::Weights>&): Assertion `0' failed.
Aborted

Duplicated with https://devtalk.nvidia.com/default/topic/1063023/deepstream-sdk/ds4-0-tx2-yolov3-number-of-unused-weights-left-13824/?offset=4#5383374