cyrusbehr opened a new issue #19821:
URL: https://github.com/apache/incubator-mxnet/issues/19821
Building mxnet release 1.7.0 `64f737cdd59fe88d2c5b479f25d011c5156b6a8a` from
source on Ubuntu 18.04 using the following CMake arguments:
```
cmake -DUSE_CPP_PACKAGE=1 -DBUILD_CPP_EXAMPLES=OFF -DUSE_CUDA=0
-DUSE_MKL_IF_AVAILABLE=1 -DUSE_BLAS=mkl -DUSE_OPENCV=0 -DUSE_LAPACK=0
-DMKL_INCLUDE_DIR=/opt/intel/compilers_and_libraries/linux/mkl/include
-DMKL_RT_LIBRARY=/opt/intel/compilers_and_libraries/linux/mkl/lib/intel64/libmkl_rt.so
-DCMAKE_BUILD_TYPE=Release ..
```
I am trying to run inference with a quantized model. Here is my code:
```
#include <iostream>
#include <iostream>
#include <fstream>
#include <sstream>
#include <opencv2/opencv.hpp>
#include "mxnet-cpp/MxNetCpp.h"
using namespace mxnet::cpp;
float dotProduct(const std::vector<float> &v1, const std::vector<float> &v2)
{
float res = 0.f;
for (int i = 0; i < v1.size(); ++i) {
res += v1[i] * v2[i];
}
return res;
}
inline NDArray AsData(cv::Mat rgb_image, Context ctx = Context::cpu()) {
std::vector<float> data_buffer;
// hwc to chw conversion
for (int c = 0; c < 3; ++c) {
for (int i = 0; i < rgb_image.rows; ++i) {
for (int j = 0; j < rgb_image.cols; ++j) {
data_buffer.push_back(static_cast<float>(rgb_image.data[(i *
rgb_image.cols + j) * 3 + c]));
}
}
}
// construct NDArray from data buffer
return NDArray(data_buffer, Shape(1, 3, rgb_image.rows, rgb_image.cols),
ctx);
}
int main() {
std::string jsonFilepath = "../tfv4_quantized-symbol.json";
std::string paramsFilepath = "../tfv4_quantized-0000.params";
// std::string jsonFilepath = "../tfv4.json";
// std::string paramsFilepath = "../tfv4.params";
// Read a face chip:
auto imgBGR =
cv::imread("/home/nchafni/Cyrus/data/10kx10/data/Joseph-Abram-Cook-mugshot-36942062.jpg");
cv::Mat imgRGB;
cv::cvtColor(imgBGR, imgRGB, cv::COLOR_BGR2RGB);
mxnet::cpp::Context ctx(Context::cpu());
mxnet::cpp::Symbol net;
mxnet::cpp::Executor *exec;
std::map<std::string, mxnet::cpp::NDArray> args;
std::map<std::string, mxnet::cpp::NDArray> auxs;
net = Symbol::Load(jsonFilepath);
std::map<std::string, NDArray> params =
NDArray::LoadToMap(paramsFilepath);
for (auto iter : params) {
std::string type = iter.first.substr(0, 4);
std::string name = iter.first.substr(4);
if (type == "arg:")
args[name] = iter.second.Copy(ctx);
else if (type == "aux:")
auxs[name] = iter.second.Copy(ctx);
else
continue;
}
NDArray::WaitAll();
args["data"] = NDArray(Shape(1, 3, 112, 112), ctx, false);
exec = net.SimpleBind(
ctx, args, std::map<std::string, NDArray>(),
std::map<std::string, OpReqType>(), auxs);
auto data = AsData(imgRGB, ctx);
data.CopyTo(&(exec->arg_dict()["data"]));
exec->Forward(false);
auto embedding = exec->outputs[0].Copy(Context(kCPU, 0));
embedding.WaitToRead();
std::vector<float> featureVector;
int num = embedding.GetShape()[1];
featureVector.resize(num);
for (int i=0; i<num; i++) {
featureVector[i] = embedding.At(0, i);
}
float magnitude = sqrt(dotProduct(featureVector, featureVector));
for (size_t j = 0; j < featureVector.size(); j++) {
featureVector[j] = featureVector[j] / magnitude;
}
auto simScore = dotProduct(featureVector, featureVector);
std::cout << simScore << std::endl;
delete exec;
return 0;
}
```
I can compile the program fine. When I try to run it, I get the following
error message:
```
[09:52:28]
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/src/executor/graph_executor.cc:2061:
Subgraph backend MKLDNN is activated.
terminate called after throwing an instance of 'dmlc::Error'
what(): [09:52:28]
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/packaged/usr/local/include/mxnet-cpp/ndarray.hpp:237:
Check failed: MXNDArrayWaitToRead(blob_ptr_->handle_) == 0 (-1 vs. 0) :
MXNetError: Check failed: (in_data[0].dtype()) == (mshadow: :kUint8)
mkldnn_quantized_conv op only supports uint8 as input type
Stack trace:
File
"/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/src/operator/quantization/mkldnn/mkldnn_quantized_conv.cc",
line 41
[bt] (0)
./quanitzed_mxnet_mkldnn(dmlc::LogMessageFatal::~LogMessageFatal()+0x4d)
[0x558c0c32cf01]
[bt] (1)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(+0x3268973)
[0x7fd3467bd973]
[bt] (2)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(mxnet::exec::FComputeExExecutor::Run(mxnet::RunContext,
bool)+0x23b) [0x7fd34411ea8b]
[bt] (3)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(+0xbda5fd)
[0x7fd34412f5fd]
[bt] (4)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(+0xbda6bf)
[0x7fd34412f6bf]
[bt] (5)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(mxnet::engine::ThreadedEngine::ExecuteOprBlock(mxnet::RunContext,
mxnet::engine::OprBlock*)+0x121) [0x7fd344109cf1]
[bt] (6)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(std::_Function_handler<void
(std::shared_ptr<dmlc::ManualEvent>),
mxnet::engine::ThreadedEnginePerDevice::PushToExecute(mxnet::engine::OprBlock*,
bool)::{lambda()#1}::operator()()
const::{lambda(std::shared_ptr<dmlc::ManualEvent>)#1}>::_M_invoke(std::_Any_data
const&, std::shared_ptr<dmlc::ManualEvent>&&)+0x147) [0x7fd34410a637]
[bt] (7)
/home/nchafni/Cyrus/prototype/quanitzed_mxnet_mkldnn/incubator-mxnet/build/libmxnet.so(std::thread::_State_impl<std::thread::_Invoker<std::tuple<std::function<void
(std::shared_ptr<dmlc::ManualEvent>)>, std::shared_ptr<dmlc::ManualEvent> > >
>::_M_run()+0x4a) [0x7fd344108cba]
[bt] (8) /usr/lib/x86_64-linux-gnu/libstdc++.so.6(+0xd0870)
[0x7fd33fec7870]
Stack trace:
[bt] (0)
./quanitzed_mxnet_mkldnn(dmlc::LogMessageFatal::~LogMessageFatal()+0x4d)
[0x558c0c32cf01]
[bt] (1) ./quanitzed_mxnet_mkldnn(+0x10527) [0x558c0c332527]
[bt] (2) ./quanitzed_mxnet_mkldnn(+0x908e) [0x558c0c32b08e]
[bt] (3) /lib/x86_64-linux-gnu/libc.so.6(__libc_start_main+0xe7)
[0x7fd33f471bf7]
[bt] (4) ./quanitzed_mxnet_mkldnn(+0x81da) [0x558c0c32a1da]
```
How can I resolve this issue?
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