std::vector<std::string> in_names = parser->GetSubgraphInputTensorNames(0);
for (auto const &name:in_names) {
- inputBindingInfo.push_back(parser->GetNetworkInputBindingInfo(0, name));
+ mInputBindingInfo.push_back(parser->GetNetworkInputBindingInfo(0, name));
}
std::vector<std::string> out_names = parser->GetSubgraphOutputTensorNames(0);
for (auto const &name:out_names) {
- outputBindingInfo.push_back(parser->GetNetworkOutputBindingInfo(0, name));
+ mOutputBindingInfo.push_back(parser->GetNetworkOutputBindingInfo(0, name));
}
- LOGI("Input Tensor count = %d", (int)inputBindingInfo.size());
- LOGI("Output Tensor count = %d", (int) outputBindingInfo.size());
+ LOGI("Input Tensor count = %d", (int)mInputBindingInfo.size());
+ LOGI("Output Tensor count = %d", (int)mOutputBindingInfo.size());
LOGI("LEAVE");
// TODO. Need to check if model file loading is done.
std::vector<armnn::BindingPointInfo>::iterator iter;
- for (iter = inputBindingInfo.begin(); iter != inputBindingInfo.end(); iter++) {
+ for (iter = mInputBindingInfo.begin(); iter != mInputBindingInfo.end(); iter++) {
inference_engine_tensor_info out_info;
armnn::BindingPointInfo bindingInfo = *iter;
armnn::TensorInfo tensorInfo = bindingInfo.second;
// TODO. Need to check if model file loading is done.
std::vector<armnn::BindingPointInfo>::iterator iter;
- for (iter = outputBindingInfo.begin(); iter != outputBindingInfo.end(); iter++) {
+ for (iter = mOutputBindingInfo.begin(); iter != mOutputBindingInfo.end(); iter++) {
inference_engine_tensor_info out_info;
armnn::BindingPointInfo bindingInfo = *iter;
armnn::TensorInfo tensorInfo = bindingInfo.second;
{
LOGI("ENTER");
- armnn::BindingPointInfo outBindingInfo = outputBindingInfo.front();
+ armnn::BindingPointInfo outBindingInfo = mOutputBindingInfo.front();
armnn::TensorInfo outputTensorInfo = outBindingInfo.second;
armnn::TensorShape shape = outputTensorInfo.GetShape();
// input
- armnn::BindingPointInfo inBindingInfo = inputBindingInfo.front();
+ armnn::BindingPointInfo inBindingInfo = mInputBindingInfo.front();
armnn::TensorInfo inputTensorInfo = inBindingInfo.second;
int tensor_size = 1;
armnn::InputTensors input_tensors;
armnn::OutputTensors output_tensors;
- input_tensors.push_back({inputBindingInfo[0].first, InputTensors.front()});
- output_tensors.push_back({outputBindingInfo[0].first, mOutputTensor.front()});
+ input_tensors.push_back({mInputBindingInfo[0].first, InputTensors.front()});
+ output_tensors.push_back({mOutputBindingInfo[0].first, mOutputTensor.front()});
armnn::Status ret = mRuntime->EnqueueWorkload(mNetworkIdentifier,
input_tensors, output_tensors);