enqueueV2() for second profile fail

next error after fix error in https://devtalk.nvidia.com/default/topic/1069559/tensorrt/check-allinputdimensionsspecified-for-second-profile-fail/post/5419783/#5419783

error:

[E] [TRT] Parameter check failed at: engine.cpp::enqueueV2::466, condition: bindings[x] != nullptr

My code:

#include "NvInfer.h"
#include <iostream>
#include "NvUtils.h"
#include "NvOnnxParser.h"
using namespace nvinfer1;

#include "common/logger.h"
#include "common/buffers.h"
std::string model_path = "detection_model.onnx";

void convert_dims_to_vect(const nvinfer1::Dims& dims, std::vector<int>& v){
    v.resize(dims.nbDims);
    for (int i=0; i<dims.nbDims; ++i)
        v[i] = dims.d[i];
}
void make_explicit_shapes(IExecutionContext* context,const  std::vector<std::string>& tensorNames, std::vector<std::vector<int>>& explicit_shapes){
	int n = tensorNames.size();
	explicit_shapes.resize(n);
	std::string suffix;
	int profile_index = context->getOptimizationProfile();
	if (profile_index!=0)
		suffix = " [profile "+std::to_string(profile_index)+"]";
	std::vector<int> v;
	for (int i=0; i<n; ++i){
		int index = context->getEngine().getBindingIndex((tensorNames[i]+suffix).c_str());
		convert_dims_to_vect(context->getBindingDimensions(index), v);
		explicit_shapes[i] = v;
	}
}

int main(int argc, char** argv) {
  auto builder = createInferBuilder(gLogger);

  auto config = builder->createBuilderConfig();
  Dims4 dims1(1,10,10,1);
  Dims4 dims2(1,100,100,1);
  Dims4 dims3(1,200,200,1);
  std::string input_name = "fts_input_images:0";
  for (int i=0; i<2; ++i){
    auto profile = builder->createOptimizationProfile();
    profile->setDimensions(input_name.c_str(), OptProfileSelector::kMIN, dims1);
    profile->setDimensions(input_name.c_str(), OptProfileSelector::kOPT, dims2);
    profile->setDimensions(input_name.c_str(), OptProfileSelector::kMAX, dims3);
    config->addOptimizationProfile(profile);
  }

  auto network = builder->createNetworkV2(1U << static_cast<int>(NetworkDefinitionCreationFlag::kEXPLICIT_BATCH));
  auto parser = nvonnxparser::createParser(*network, gLogger);
  parser->parseFromFile(model_path.c_str(), 3);
  auto engine = builder->buildEngineWithConfig(*network,*config);

    std::vector<std::string> tensorNames;
    for (int i=0; i<engine->getNbBindings(); ++i){
        std::string name(engine->getBindingName(i));
        if (name.find("[profile")==-1){
            tensorNames.emplace_back(name);
        }
    }

  std::vector<IExecutionContext*> contexts;
  for (int i=0; i<2; ++i){
    contexts.emplace_back(engine->createExecutionContext());
    auto context = contexts.back();
    context->setOptimizationProfile(i);
    // std::cout<<"allInputDimensionsSpecified: "<<context->allInputDimensionsSpecified()<<"\n";
    int index;
    if (i==0)
        index = engine->getBindingIndex((input_name).c_str());
    else
        index = engine->getBindingIndex((input_name+" [profile "+std::to_string(i)+"]").c_str());
    context->setBindingDimensions(index, dims2);
    // std::cout<<"allInputDimensionsSpecified must equal 1: "<<context->allInputDimensionsSpecified()<<"\n";

    std::vector<std::vector<int>> explicit_shapes;
    make_explicit_shapes(context, tensorNames, explicit_shapes);

    std::vector<samplesCommon::DeviceBuffer> deviceBuffers;
    std::vector<samplesCommon::HostBuffer> hostBuffers;
    for (int i=0; i<tensorNames.size(); ++i){
        size_t allocationSize = std::accumulate(explicit_shapes[i].begin(), explicit_shapes[i].end(), 1, std::multiplies<int>()) * 4;
        hostBuffers.emplace_back(allocationSize);
        // std::cout<<"allocationSize: "<<allocationSize<<"\n";
        deviceBuffers.emplace_back(allocationSize);
    }

    std::vector<void*> mDeviceBindings;
    for (auto& buffer:(deviceBuffers)){
        // std::cout<<buffer.data()<<" buffer\n";
        mDeviceBindings.emplace_back(buffer.data());
    }
    cudaStream_t stream;
    CHECK(cudaStreamCreate(&stream));
    if (!context->enqueueV2(mDeviceBindings.data(), stream, nullptr)){
        std::cout<<"error when run graph TensorRT\n";
    }
    cudaStreamSynchronize(stream);
  }

}

My model: https://1drv.ms/u/s!AhFk3ICqlZI2irgOxoSOSIY80QLWHA?e=5idBBf

How to fix? I use tensorrt7.

Sorry I fixed it by
replace
std::vector<void*> mDeviceBindings;
by
std::vector<void*> mDeviceBindings(i*deviceBuffers.size(), NULL);