EfficientNMS_TRT plugin compiled by myself can not work

Description

For some reaon, I need to compile the EfficientNMS_TRT plugin by myself, I clone the code from Github, and add the files in "efficientNMSPlugin" and "common" folders to my vs project, compile it success, then I add the plugin I compiled to network, but build engine failed, and tensorRT report below infos:

00000018 4.94450378 [21768] TrtZLog-testYOLOv8(INFO): start to build trt engine...
00000019 6.44722557 [21768] TRT-testYOLOv8(INFO): [MemUsageChange] Init cuBLAS/cuBLASLt: CPU +934, GPU +316, now: CPU 10810, GPU 1662 (MiB)
00000020 6.45917130 [21768] TRT-testYOLOv8(INFO): [MemUsageChange] Init cuDNN: CPU +3, GPU +8, now: CPU 10813, GPU 1670 (MiB)
00000021 6.45966244 [21768] TRT-testYOLOv8(INFO): Local timing cache in use. Profiling results in this builder pass will not be stored.
00000098 389.70767212 [21768] TRT-testYOLOv8(INFO): Some tactics do not have sufficient workspace memory to run. Increasing workspace size will enable more tactics, please check verbose output for requested sizes.
00000099 619.68878174 [21768] TRT-testYOLOv8(WARNING): Skipping tactic 0x0000000000000000 due to exception Assertion status == kSTATUS_SUCCESS failed.
00000100 619.68914795 [21768] TRT-testYOLOv8(WARNING): Skipping tactic 0x0000000000000000 due to exception Assertion status == kSTATUS_SUCCESS failed.
00000101 619.73187256 [21768] TRT-testYOLOv8(ERROR): 4: [optimizer.cpp::nvinfer1::builder::cgraph::LeafCNode::computeCosts::3726] Error Code 4: Internal Error (Could not find any implementation for node (Unnamed Layer 707) [PluginV2DynamicExt] due to insufficient workspace. See verbose log for requested sizes.)
00000102 620.01159668 [21768] TRT-testYOLOv8(ERROR): 2: [builder.cpp::nvinfer1::builder::Builder::buildSerializedNetwork::751] Error Code 2: Internal Error (Assertion engine != nullptr failed. )*

If I use the EfficientNMS plugin shipped with trt sdk, there is no error encounted during engine build, so what's wrong with the plugin I compiled?

Environment

TensorRT Version: 8.5.3.1

NVIDIA GPU: RTX 4070 Super

NVIDIA Driver Version: 551.61

CUDA Version: 11.6.0

CUDNN Version: 8.6.0.163

Operating System: Windows 10 Pro

Python Version (if applicable):

Tensorflow Version (if applicable):

PyTorch Version (if applicable):

Baremetal or Container (if so, version):

Start by reviewing the efficientNMSPlugin and common folders added to the Visual Studio project, then compare the self-compiled plugin setup with the EfficientNMS plugin shipped in the TensorRT SDK. Reproduce the TensorRT 8.5.3.1 engine build using the reported environment and verbose logging. Done means the custom plugin builds the engine without the insufficient-workspace or implementation errors.