Hi all,
I’m using the NCS2 on Raspberry. The network is Caffe based and Model Optimizer was executed with --data_type=FP16. When looking into the generated XML all the layer elements have the precision=FP16 attribute.
When running inferences on the Raspberry (C++ / OpenVINO) all works good when using F32 input buffers; the output of the inference are as expected.
However, when attempting to use FP16 the data returned is _always_ a buffer full of 0.0.
I’m building with g++ flag -mfp16-format=ieee. When attempting FP16 each element in the input given to the input->data() element is of type __fp16.
I create the input blobs with:
auto input = make_shared_blob<PrecisionTrait<Precision::FP32>::value_type>(inputInfoItem.second->getTensorDesc());
resp:
auto input = make_shared_blob<PrecisionTrait<Precision::FP16>::value_type>(inputInfoItem.second->getTensorDesc());
Prior to creating the blobs I’ve called:
inputInfoItem.second->setPrecision(Precision::FP32);
Resp:
inputInfoItem.second->setPrecision(Precision::FP16);
Any ideas of why I’m getting all zeroes as output?
Does openVINO require the output format to also be FP16 in this case or shout the input/output precision be independent?
