NUCGen10a

第10世代の CPU を実装したインテルのミニPC NUC を使う †

　Intel® NUC に OpenVINO™ Toolkit をインストールして「AIエッジコンピューティング」を実践する。第10世代 CPU の速度を試す。
　新版にともない OpenVINO™「2021.2」版とする。　最新版はここ

第10世代の CPU を実装したインテルのミニPC NUC を使う
参考資料

※ 最終更新:2021/05/07　

↑

環境設定 †

↑

準備したもの †

インテル Intel® Core™ i5-10210U プロセッサを搭載した Intel® NUC キット BXNUC10I5FNH
Western Digital SSD 1TB WD Blue SN550 PC M.2-2280 NVMe WDS100T2B0C-EC
Team ノートPC用 SO-DIMM DDR4 2666MHz PC4-21300 32GBx2枚組 64GBkit
電源ケーブル
イメージファイル → 「ubuntu-20.04.1-desktop-amd64.iso」

↑

OS (ubuntu20.04LTS) のインストールと環境設定 †

Ubuntu20.04LTS Desktop 版イメージをUSBメモリーにコピーしてインストール。
USB起動してインストール画面が出てくるまで待つ。(USB 起動できない場合は「F2」キーを押して BIOS 画面を呼び出し設定変更)
日本語関連設定
- デスクトップから「言語サポート」を完了する。
  　Ubuntu 20.04 LTSのインストール直後にやっておきたいことまとめ
  　【デスクトップ】日本語表示・入力の設定 (ibus-mozc)
- 日本語フォント「noto sans cjk jp」をインストールする。
```
$ sudo apt-get update
...
$ sudo apt-get install -y fonts-noto
```

各種ツール類をインストールする。

フォント設定
```
sudo apt install gnome-tweaks
```
SSHサーバー
```
sudo apt install openssh-server
```
ネットワークツール
```
sudo apt install net-tools
```

「vi」エディタの設定

$ vi ~/.vimrc
set nocompatible
set backspace=indent,eol,start
set expandtab
set tabstop=4
set shiftwidth=4
set autoindent

sudo 付きで vi を実行した場合は、root の設定が使用されるので、rootの .vimrcを ~/vimrc のシンボリックリンクにする。

sudo ln -s ~/.vimrc /root/.vimrc
$ sudo ls -la /root
合計 24
drwx------  4 root root 4096  3月 31 19:07 .
drwxr-xr-x 20 root root 4096  3月 31 17:29 ..
-rw-r--r--  1 root root 3106 12月  5  2019 .bashrc
drwx------  2 root root 4096  2月 10 03:51 .cache
-rw-r--r--  1 root root  161 12月  5  2019 .profile
lrwxrwxrwx  1 root root   19  3月 31 19:07 .vimrc -> /home/mizutu/.vimrc
drwxr-xr-x  3 root root 4096  3月 31 17:33 snap

VNC接続
【Ubuntu 20.04/18.04 Desktop】WinやMacパソコンからVNCでリモート接続し画面共有する
```
sudo gsettings set org.gnome.Vino require-encryption false
```
設定できていないので
```
DISPLAY=:0 gsettings set org.gnome.Vino require-encryption false
```
VNCビューアから接続＜IPアドレス＞:5900
各種形式の動画や音声を再生できるようにする
```
sudo apt-get install ubuntu-restricted-extras
```

↑

OpenVINO™ Toolkit のダウンロード †

手順 → OpenVINO™ Toolkit for Linux
2021/03/31現在の最新版は「2021.3」だが、インストールディレクトリの変更やオフィシャルサイトの説明の食い違いなどがあり、これまで通り「2021.2」をインストールすることにする。
「~/ダウンロード」ディレクトリに l_openvino_toolkit_p_2021.2.185.tgz をコピーする。

↑

OpenVINO™ Toolkit のインストール †

ダウンロードされたパッケージを解凍

$ cd ダウンロード
$ ls
l_openvino_toolkit_p_2021.2.185.tgz
$ tar -xvzf l_openvino_toolkit_p_2021.2.185.tgz
l_openvino_toolkit_p_2021.2.185/
l_openvino_toolkit_p_2021.2.185/pset/
l_openvino_toolkit_p_2021.2.185/pset/32e/
l_openvino_toolkit_p_2021.2.185/pset/32e/libz/
l_openvino_toolkit_p_2021.2.185/pset/32e/libz/libz.so
    :
    :
l_openvino_toolkit_p_2021.2.185/PUBLIC_KEY.PUB
l_openvino_toolkit_p_2021.2.185/install.sh
l_openvino_toolkit_p_2021.2.185/install_GUI.sh
l_openvino_toolkit_p_2021.2.185/install_openvino_dependencies.sh
l_openvino_toolkit_p_2021.2.185/silent.cfg
$ ls
l_openvino_toolkit_p_2021.2.185  l_openvino_toolkit_p_2021.2.185.tgz

解凍したパッケージの中にあるインストーラを起動
```
cd l_openvino_toolkit_p_2021.2.185
$ sudo ./install_GUI.sh
```
GUI のインストール手順に従いインストールを進める。

依存関係の外部パッケージをインストール

$ cd /opt/intel/openvino_2021/install_dependencies
$ sudo -E ./install_openvino_dependencies.sh

This script installs the following OpenVINO 3rd-party dependencies:
  1. GTK+, FFmpeg and GStreamer libraries used by OpenCV
  2. libusb library required for Myriad plugin for Inference Engine
  3. build dependencies for OpenVINO samples
  4. build dependencies for GStreamer Plugins

ヒット:1 http://jp.archive.ubuntu.com/ubuntu focal InRelease
取得:2 http://jp.archive.ubuntu.com/ubuntu focal-updates InRelease [114 kB]
取得:3 http://jp.archive.ubuntu.com/ubuntu focal-backports InRelease [101 kB]  
    :
    :

環境変数の設定
```
$ source /opt/intel/openvino_2021/bin/setupvars.sh
[setupvars.sh] OpenVINO environment initialized
```
シェルを起動時に自動的に環境変数を設定するため「~/.bashrc」ファイルの最後に「source /opt/intel/openvino_2021/bin/setupvars.sh」の1行を追記する。

Model Optimizer の設定

$ cd /opt/intel/openvino_2021/deployment_tools/model_optimizer/install_prerequisites
$ sudo ./install_prerequisites.sh
[sudo] mizutu のパスワード: 
ヒット:1 http://jp.archive.ubuntu.com/ubuntu focal InRelease
取得:2 http://jp.archive.ubuntu.com/ubuntu focal-updates InRelease [114 kB]
取得:3 http://jp.archive.ubuntu.com/ubuntu focal-backports InRelease [101 kB]  
ヒット:4 http://security.ubuntu.com/ubuntu focal-security InRelease            
    :
    :

サンプルデモの実行１ demo_security_barrier_camera.sh

$ cd /opt/intel/openvino_2021/deployment_tools/demo
$ ./demo_security_barrier_camera.sh
    :
    :
Downloading Intel models

target_precision = FP16
Run python3 /opt/intel/openvino_2021/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name vehicle-license-plate-detection-barrier-0106 --output_dir /home/mizutu/openvino_models/ir --cache_dir /home/mizutu/openvino_models/cache

################|| Downloading vehicle-license-plate-detection-barrier-0106 ||################
    :

###################################################

Build Inference Engine demos

-- The C compiler identification is GNU 9.3.0
-- The CXX compiler identification is GNU 9.3.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
    :

[ 92%] Building CXX object security_barrier_camera_demo/CMakeFiles/security_barrier_camera_demo.dir/main.cpp.o
[100%] Linking CXX executable ../intel64/Release/security_barrier_camera_demo
[100%] Built target security_barrier_camera_demo


###################################################

Run Inference Engine security_barrier_camera demo

Run ./security_barrier_camera_demo -d CPU -d_va CPU -d_lpr CPU -i /opt/intel/openvino_2021/deployment_tools/demo/car_1.bmp -m /home/mizutu/openvino_models/ir/intel/vehicle-license-plate-detection-barrier-0106/FP16/vehicle-license-plate-detection-barrier-0106.xml -m_lpr /home/mizutu/openvino_models/ir/intel/license-plate-recognition-barrier-0001/FP16/license-plate-recognition-barrier-0001.xml -m_va /home/mizutu/openvino_models/ir/intel/vehicle-attributes-recognition-barrier-0039/FP16/vehicle-attributes-recognition-barrier-0039.xml

[ INFO ] InferenceEngine:   API version ......... 2.1
    Build ........... 2021.2.0-1877-176bdf51370-releases/2021/2
[ INFO ] Files were added: 1
[ INFO ]     /opt/intel/openvino_2021/deployment_tools/demo/car_1.bmp
[ INFO ] Loading device CPU
[ INFO ]    CPU
    MKLDNNPlugin version ......... 2.1
    Build ........... 2021.2.0-1877-176bdf51370-releases/2021/2

[ INFO ] Loading detection model to the CPU plugin
[ INFO ] Loading Vehicle Attribs model to the CPU plugin
[ INFO ] Loading Licence Plate Recognition (LPR) model to the CPU plugin
[ INFO ] Number of InferRequests: 1 (detection), 3 (classification), 3 (recognition)
[ INFO ] 4 streams for CPU
[ INFO ] Display resolution: 1920x1080
[ INFO ] Number of allocated frames: 3
[ INFO ] Resizable input with support of ROI crop and auto resize is disabled
0.1FPS for (2 / 1) frames
Detection InferRequests usage: 0.0%

[ INFO ] Execution successful


###################################################

Demo completed successfully.

サンプルデモの実行２ demo_squeezenet_download_convert_run.sh

$ cd /opt/intel/openvino_2021/deployment_tools/demo
$ ./demo_squeezenet_download_convert_run.sh
target_precision = FP16
[setupvars.sh] OpenVINO environment initialized

Run python3 /opt/intel/openvino_2021/deployment_tools/open_model_zoo/tools/downloader/downloader.py --name squeezenet1.1 --output_dir /home/mizutu/openvino_models/models --cache_dir /home/mizutu/openvino_models/cache

################|| Downloading squeezenet1.1 ||################
    :

###################################################

Run Inference Engine classification sample

Run ./classification_sample_async -d CPU -i /opt/intel/openvino_2021/deployment_tools/demo/car.png -m /home/mizutu/openvino_models/ir/public/squeezenet1.1/FP16/squeezenet1.1.xml

[ INFO ] InferenceEngine: 
    API version ............ 2.1
    Build .................. 2021.2.0-1877-176bdf51370-releases/2021/2
    Description ....... API
[ INFO ] Parsing input parameters
[ INFO ] Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ]     /opt/intel/openvino_2021/deployment_tools/demo/car.png
[ INFO ] Creating Inference Engine
    CPU
    MKLDNNPlugin version ......... 2.1
    Build ........... 2021.2.0-1877-176bdf51370-releases/2021/2

[ INFO ] Loading network files
[ INFO ] Preparing input blobs
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[ INFO ] Batch size is 1
[ INFO ] Loading model to the device
[ INFO ] Create infer request
[ INFO ] Start inference (10 asynchronous executions)
[ INFO ] Completed 1 async request execution
[ INFO ] Completed 2 async request execution
[ INFO ] Completed 3 async request execution
[ INFO ] Completed 4 async request execution
[ INFO ] Completed 5 async request execution
[ INFO ] Completed 6 async request execution
[ INFO ] Completed 7 async request execution
[ INFO ] Completed 8 async request execution
[ INFO ] Completed 9 async request execution
[ INFO ] Completed 10 async request execution
[ INFO ] Processing output blobs

Top 10 results:

Image /opt/intel/openvino_2021/deployment_tools/demo/car.png

classid probability label
------- ----------- -----
817     0.6853030   sports car, sport car
479     0.1835197   car wheel
511     0.0917197   convertible
436     0.0200694   beach wagon, station wagon, wagon, estate car, beach waggon, station waggon, waggon
751     0.0069604   racer, race car, racing car
656     0.0044177   minivan
717     0.0024739   pickup, pickup truck
581     0.0017788   grille, radiator grille
468     0.0013083   cab, hack, taxi, taxicab
661     0.0007443   Model T

[ INFO ] Execution successful

[ INFO ] This sample is an API example, for any performance measurements please use the dedicated benchmark_app tool


###################################################

Demo completed successfully.

サンプルデモの実行３ demo_benchmark_app.sh

$cd /opt/intel/openvino_2021/deployment_tools/demo
$ ./demo_benchmark_app.sh
target_precision = FP16
[setupvars.sh] OpenVINO environment initialized
    :
###################################################

Run Inference Engine benchmark app

Run ./benchmark_app -d CPU -i /opt/intel/openvino_2021/deployment_tools/demo/car.png -m /home/mizutu/openvino_models/ir/public/squeezenet1.1/FP16/squeezenet1.1.xml -pc -niter 1000

[Step 1/11] Parsing and validating input arguments
[ INFO ] Parsing input parameters
[ INFO ] Files were added: 1
[ INFO ]     /opt/intel/openvino_2021/deployment_tools/demo/car.png
[Step 2/11] Loading Inference Engine
[ INFO ] InferenceEngine: 
    API version ............ 2.1
    Build .................. 2021.2.0-1877-176bdf51370-releases/2021/2
    Description ....... API
[ INFO ] Device info: 
    CPU
    MKLDNNPlugin version ......... 2.1
    Build ........... 2021.2.0-1877-176bdf51370-releases/2021/2

[Step 3/11] Setting device configuration
[ WARNING ] -nstreams default value is determined automatically for CPU device. Although the automatic selection usually provides a reasonable performance,but it still may be non-optimal for some cases, for more information look at README.
[Step 4/11] Reading network files
[ INFO ] Loading network files
[ INFO ] Read network took 8.75 ms
[Step 5/11] Resizing network to match image sizes and given batch
[ INFO ] Network batch size: 1
[Step 6/11] Configuring input of the model
[Step 7/11] Loading the model to the device
[ INFO ] Load network took 123.16 ms
[Step 8/11] Setting optimal runtime parameters
[Step 9/11] Creating infer requests and filling input blobs with images
[ INFO ] Network input 'data' precision U8, dimensions (NCHW): 1 3 227 227 
[ WARNING ] Some image input files will be duplicated: 4 files are required but only 1 are provided
[ INFO ] Infer Request 0 filling
[ INFO ] Prepare image /opt/intel/openvino_2021/deployment_tools/demo/car.png
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[ INFO ] Infer Request 1 filling
[ INFO ] Prepare image /opt/intel/openvino_2021/deployment_tools/demo/car.png
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[ INFO ] Infer Request 2 filling
[ INFO ] Prepare image /opt/intel/openvino_2021/deployment_tools/demo/car.png
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[ INFO ] Infer Request 3 filling
[ INFO ] Prepare image /opt/intel/openvino_2021/deployment_tools/demo/car.png
[ WARNING ] Image is resized from (787, 259) to (227, 227)
[Step 10/11] Measuring performance (Start inference asynchronously, 4 inference requests using 4 streams for CPU, limits: 1000 iterations)
[ INFO ] First inference took 4.71 ms

[Step 11/11] Dumping statistics report
[ INFO ] Pefrormance counts for 0-th infer request:
data/mean_value_const_biases  NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value_const_weights NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value               EXECUTED       layerType: ScaleShift         realTime: 65        cpu: 65              execType: jit_avx2_I8
conv1                         EXECUTED       layerType: Convolution        realTime: 522       cpu: 522             execType: jit_avx2_FP32
relu_conv1                    NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool1                         EXECUTED       layerType: Pooling            realTime: 315       cpu: 315             execType: jit_avx_FP32
fire2/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 83        cpu: 83              execType: jit_avx2_1x1_FP32
fire2/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand1x1               EXECUTED       layerType: Convolution        realTime: 81        cpu: 81              execType: jit_avx2_1x1_FP32
fire2/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand3x3               EXECUTED       layerType: Convolution        realTime: 537       cpu: 537             execType: jit_avx2_FP32
fire2/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/concat                  EXECUTED       layerType: Concat             realTime: 3         cpu: 3               execType: unknown_FP32
fire3/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 171       cpu: 171             execType: jit_avx2_1x1_FP32
fire3/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand1x1               EXECUTED       layerType: Convolution        realTime: 78        cpu: 78              execType: jit_avx2_1x1_FP32
fire3/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand3x3               EXECUTED       layerType: Convolution        realTime: 540       cpu: 540             execType: jit_avx2_FP32
fire3/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool3                         EXECUTED       layerType: Pooling            realTime: 142       cpu: 142             execType: jit_avx_FP32
fire4/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 78        cpu: 78              execType: jit_avx2_1x1_FP32
fire4/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand1x1               EXECUTED       layerType: Convolution        realTime: 72        cpu: 72              execType: jit_avx2_1x1_FP32
fire4/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand3x3               EXECUTED       layerType: Convolution        realTime: 565       cpu: 565             execType: jit_avx2_FP32
fire4/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
fire5/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 157       cpu: 157             execType: jit_avx2_1x1_FP32
fire5/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand1x1               EXECUTED       layerType: Convolution        realTime: 70        cpu: 70              execType: jit_avx2_1x1_FP32
fire5/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand3x3               EXECUTED       layerType: Convolution        realTime: 554       cpu: 554             execType: jit_avx2_FP32
fire5/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool5                         EXECUTED       layerType: Pooling            realTime: 63        cpu: 63              execType: jit_avx_FP32
fire6/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 52        cpu: 52              execType: jit_avx2_1x1_FP32
fire6/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand1x1               EXECUTED       layerType: Convolution        realTime: 39        cpu: 39              execType: jit_avx2_1x1_FP32
fire6/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand3x3               EXECUTED       layerType: Convolution        realTime: 325       cpu: 325             execType: jit_avx2_FP32
fire6/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire7/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 78        cpu: 78              execType: jit_avx2_1x1_FP32
fire7/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand1x1               EXECUTED       layerType: Convolution        realTime: 38        cpu: 38              execType: jit_avx2_1x1_FP32
fire7/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand3x3               EXECUTED       layerType: Convolution        realTime: 321       cpu: 321             execType: jit_avx2_FP32
fire7/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire8/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 101       cpu: 101             execType: jit_avx2_1x1_FP32
fire8/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand1x1               EXECUTED       layerType: Convolution        realTime: 68        cpu: 68              execType: jit_avx2_1x1_FP32
fire8/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand3x3               EXECUTED       layerType: Convolution        realTime: 565       cpu: 565             execType: jit_avx2_FP32
fire8/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire9/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 135       cpu: 135             execType: jit_avx2_1x1_FP32
fire9/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand1x1               EXECUTED       layerType: Convolution        realTime: 67        cpu: 67              execType: jit_avx2_1x1_FP32
fire9/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand3x3               EXECUTED       layerType: Convolution        realTime: 578       cpu: 578             execType: jit_avx2_FP32
fire9/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
conv10                        EXECUTED       layerType: Convolution        realTime: 1942      cpu: 1942            execType: jit_avx2_1x1_FP32
relu_conv10                   NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool10/reduce                 EXECUTED       layerType: Pooling            realTime: 49        cpu: 49              execType: jit_avx_FP32
prob                          EXECUTED       layerType: SoftMax            realTime: 3         cpu: 3               execType: jit_avx2_FP32
prob_nChw8c_nchw_out_prob     EXECUTED       layerType: Reorder            realTime: 6         cpu: 6               execType: jit_uni_FP32
out_prob                      NOT_RUN        layerType: Output             realTime: 0         cpu: 0               execType: unknown_FP32
Total time: 8474     microseconds

Full device name: Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz

[ INFO ] Pefrormance counts for 1-th infer request:
data/mean_value_const_biases  NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value_const_weights NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value               EXECUTED       layerType: ScaleShift         realTime: 65        cpu: 65              execType: jit_avx2_I8
conv1                         EXECUTED       layerType: Convolution        realTime: 519       cpu: 519             execType: jit_avx2_FP32
relu_conv1                    NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool1                         EXECUTED       layerType: Pooling            realTime: 323       cpu: 323             execType: jit_avx_FP32
fire2/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 84        cpu: 84              execType: jit_avx2_1x1_FP32
fire2/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand1x1               EXECUTED       layerType: Convolution        realTime: 78        cpu: 78              execType: jit_avx2_1x1_FP32
fire2/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand3x3               EXECUTED       layerType: Convolution        realTime: 515       cpu: 515             execType: jit_avx2_FP32
fire2/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/concat                  EXECUTED       layerType: Concat             realTime: 3         cpu: 3               execType: unknown_FP32
fire3/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 167       cpu: 167             execType: jit_avx2_1x1_FP32
fire3/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand1x1               EXECUTED       layerType: Convolution        realTime: 73        cpu: 73              execType: jit_avx2_1x1_FP32
fire3/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand3x3               EXECUTED       layerType: Convolution        realTime: 514       cpu: 514             execType: jit_avx2_FP32
fire3/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool3                         EXECUTED       layerType: Pooling            realTime: 142       cpu: 142             execType: jit_avx_FP32
fire4/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 71        cpu: 71              execType: jit_avx2_1x1_FP32
fire4/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand1x1               EXECUTED       layerType: Convolution        realTime: 67        cpu: 67              execType: jit_avx2_1x1_FP32
fire4/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand3x3               EXECUTED       layerType: Convolution        realTime: 539       cpu: 539             execType: jit_avx2_FP32
fire4/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
fire5/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 149       cpu: 149             execType: jit_avx2_1x1_FP32
fire5/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand1x1               EXECUTED       layerType: Convolution        realTime: 67        cpu: 67              execType: jit_avx2_1x1_FP32
fire5/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand3x3               EXECUTED       layerType: Convolution        realTime: 535       cpu: 535             execType: jit_avx2_FP32
fire5/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool5                         EXECUTED       layerType: Pooling            realTime: 62        cpu: 62              execType: jit_avx_FP32
fire6/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 52        cpu: 52              execType: jit_avx2_1x1_FP32
fire6/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand1x1               EXECUTED       layerType: Convolution        realTime: 38        cpu: 38              execType: jit_avx2_1x1_FP32
fire6/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand3x3               EXECUTED       layerType: Convolution        realTime: 305       cpu: 305             execType: jit_avx2_FP32
fire6/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire7/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 76        cpu: 76              execType: jit_avx2_1x1_FP32
fire7/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand1x1               EXECUTED       layerType: Convolution        realTime: 37        cpu: 37              execType: jit_avx2_1x1_FP32
fire7/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand3x3               EXECUTED       layerType: Convolution        realTime: 305       cpu: 305             execType: jit_avx2_FP32
fire7/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire8/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 96        cpu: 96              execType: jit_avx2_1x1_FP32
fire8/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand1x1               EXECUTED       layerType: Convolution        realTime: 65        cpu: 65              execType: jit_avx2_1x1_FP32
fire8/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand3x3               EXECUTED       layerType: Convolution        realTime: 540       cpu: 540             execType: jit_avx2_FP32
fire8/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
fire9/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 132       cpu: 132             execType: jit_avx2_1x1_FP32
fire9/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand1x1               EXECUTED       layerType: Convolution        realTime: 65        cpu: 65              execType: jit_avx2_1x1_FP32
fire9/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand3x3               EXECUTED       layerType: Convolution        realTime: 552       cpu: 552             execType: jit_avx2_FP32
fire9/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
conv10                        EXECUTED       layerType: Convolution        realTime: 1888      cpu: 1888            execType: jit_avx2_1x1_FP32
relu_conv10                   NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool10/reduce                 EXECUTED       layerType: Pooling            realTime: 45        cpu: 45              execType: jit_avx_FP32
prob                          EXECUTED       layerType: SoftMax            realTime: 3         cpu: 3               execType: jit_avx2_FP32
prob_nChw8c_nchw_out_prob     EXECUTED       layerType: Reorder            realTime: 6         cpu: 6               execType: jit_uni_FP32
out_prob                      NOT_RUN        layerType: Output             realTime: 0         cpu: 0               execType: unknown_FP32
Total time: 8190     microseconds

Full device name: Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz

[ INFO ] Pefrormance counts for 2-th infer request:
data/mean_value_const_biases  NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value_const_weights NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value               EXECUTED       layerType: ScaleShift         realTime: 62        cpu: 62              execType: jit_avx2_I8
conv1                         EXECUTED       layerType: Convolution        realTime: 514       cpu: 514             execType: jit_avx2_FP32
relu_conv1                    NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool1                         EXECUTED       layerType: Pooling            realTime: 347       cpu: 347             execType: jit_avx_FP32
fire2/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 82        cpu: 82              execType: jit_avx2_1x1_FP32
fire2/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand1x1               EXECUTED       layerType: Convolution        realTime: 79        cpu: 79              execType: jit_avx2_1x1_FP32
fire2/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand3x3               EXECUTED       layerType: Convolution        realTime: 504       cpu: 504             execType: jit_avx2_FP32
fire2/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/concat                  EXECUTED       layerType: Concat             realTime: 4         cpu: 4               execType: unknown_FP32
fire3/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 175       cpu: 175             execType: jit_avx2_1x1_FP32
fire3/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand1x1               EXECUTED       layerType: Convolution        realTime: 74        cpu: 74              execType: jit_avx2_1x1_FP32
fire3/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand3x3               EXECUTED       layerType: Convolution        realTime: 503       cpu: 503             execType: jit_avx2_FP32
fire3/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool3                         EXECUTED       layerType: Pooling            realTime: 155       cpu: 155             execType: jit_avx_FP32
fire4/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 73        cpu: 73              execType: jit_avx2_1x1_FP32
fire4/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand1x1               EXECUTED       layerType: Convolution        realTime: 67        cpu: 67              execType: jit_avx2_1x1_FP32
fire4/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand3x3               EXECUTED       layerType: Convolution        realTime: 539       cpu: 539             execType: jit_avx2_FP32
fire4/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
fire5/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 150       cpu: 150             execType: jit_avx2_1x1_FP32
fire5/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand1x1               EXECUTED       layerType: Convolution        realTime: 66        cpu: 66              execType: jit_avx2_1x1_FP32
fire5/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand3x3               EXECUTED       layerType: Convolution        realTime: 530       cpu: 530             execType: jit_avx2_FP32
fire5/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool5                         EXECUTED       layerType: Pooling            realTime: 62        cpu: 62              execType: jit_avx_FP32
fire6/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 50        cpu: 50              execType: jit_avx2_1x1_FP32
fire6/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand1x1               EXECUTED       layerType: Convolution        realTime: 38        cpu: 38              execType: jit_avx2_1x1_FP32
fire6/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand3x3               EXECUTED       layerType: Convolution        realTime: 302       cpu: 302             execType: jit_avx2_FP32
fire6/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire7/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 80        cpu: 80              execType: jit_avx2_1x1_FP32
fire7/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand1x1               EXECUTED       layerType: Convolution        realTime: 37        cpu: 37              execType: jit_avx2_1x1_FP32
fire7/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand3x3               EXECUTED       layerType: Convolution        realTime: 303       cpu: 303             execType: jit_avx2_FP32
fire7/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire8/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 94        cpu: 94              execType: jit_avx2_1x1_FP32
fire8/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand1x1               EXECUTED       layerType: Convolution        realTime: 63        cpu: 63              execType: jit_avx2_1x1_FP32
fire8/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand3x3               EXECUTED       layerType: Convolution        realTime: 530       cpu: 530             execType: jit_avx2_FP32
fire8/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire9/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 127       cpu: 127             execType: jit_avx2_1x1_FP32
fire9/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand1x1               EXECUTED       layerType: Convolution        realTime: 64        cpu: 64              execType: jit_avx2_1x1_FP32
fire9/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand3x3               EXECUTED       layerType: Convolution        realTime: 533       cpu: 533             execType: jit_avx2_FP32
fire9/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
conv10                        EXECUTED       layerType: Convolution        realTime: 1892      cpu: 1892            execType: jit_avx2_1x1_FP32
relu_conv10                   NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool10/reduce                 EXECUTED       layerType: Pooling            realTime: 42        cpu: 42              execType: jit_avx_FP32
prob                          EXECUTED       layerType: SoftMax            realTime: 3         cpu: 3               execType: jit_avx2_FP32
prob_nChw8c_nchw_out_prob     EXECUTED       layerType: Reorder            realTime: 6         cpu: 6               execType: jit_uni_FP32
out_prob                      NOT_RUN        layerType: Output             realTime: 0         cpu: 0               execType: unknown_FP32
Total time: 8160     microseconds

Full device name: Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz

[ INFO ] Pefrormance counts for 3-th infer request:
data/mean_value_const_biases  NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value_const_weights NOT_RUN        layerType: Const              realTime: 0         cpu: 0               execType: unknown_FP32
data/mean_value               EXECUTED       layerType: ScaleShift         realTime: 66        cpu: 66              execType: jit_avx2_I8
conv1                         EXECUTED       layerType: Convolution        realTime: 517       cpu: 517             execType: jit_avx2_FP32
relu_conv1                    NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool1                         EXECUTED       layerType: Pooling            realTime: 305       cpu: 305             execType: jit_avx_FP32
fire2/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 75        cpu: 75              execType: jit_avx2_1x1_FP32
fire2/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand1x1               EXECUTED       layerType: Convolution        realTime: 76        cpu: 76              execType: jit_avx2_1x1_FP32
fire2/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/expand3x3               EXECUTED       layerType: Convolution        realTime: 514       cpu: 514             execType: jit_avx2_FP32
fire2/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire2/concat                  EXECUTED       layerType: Concat             realTime: 3         cpu: 3               execType: unknown_FP32
fire3/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 158       cpu: 158             execType: jit_avx2_1x1_FP32
fire3/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand1x1               EXECUTED       layerType: Convolution        realTime: 72        cpu: 72              execType: jit_avx2_1x1_FP32
fire3/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/expand3x3               EXECUTED       layerType: Convolution        realTime: 519       cpu: 519             execType: jit_avx2_FP32
fire3/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire3/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
pool3                         EXECUTED       layerType: Pooling            realTime: 137       cpu: 137             execType: jit_avx_FP32
fire4/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 71        cpu: 71              execType: jit_avx2_1x1_FP32
fire4/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand1x1               EXECUTED       layerType: Convolution        realTime: 67        cpu: 67              execType: jit_avx2_1x1_FP32
fire4/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/expand3x3               EXECUTED       layerType: Convolution        realTime: 538       cpu: 538             execType: jit_avx2_FP32
fire4/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire4/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
fire5/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 146       cpu: 146             execType: jit_avx2_1x1_FP32
fire5/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand1x1               EXECUTED       layerType: Convolution        realTime: 66        cpu: 66              execType: jit_avx2_1x1_FP32
fire5/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/expand3x3               EXECUTED       layerType: Convolution        realTime: 530       cpu: 530             execType: jit_avx2_FP32
fire5/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire5/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
pool5                         EXECUTED       layerType: Pooling            realTime: 59        cpu: 59              execType: jit_avx_FP32
fire6/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 49        cpu: 49              execType: jit_avx2_1x1_FP32
fire6/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand1x1               EXECUTED       layerType: Convolution        realTime: 38        cpu: 38              execType: jit_avx2_1x1_FP32
fire6/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/expand3x3               EXECUTED       layerType: Convolution        realTime: 304       cpu: 304             execType: jit_avx2_FP32
fire6/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire6/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire7/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 72        cpu: 72              execType: jit_avx2_1x1_FP32
fire7/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand1x1               EXECUTED       layerType: Convolution        realTime: 36        cpu: 36              execType: jit_avx2_1x1_FP32
fire7/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/expand3x3               EXECUTED       layerType: Convolution        realTime: 304       cpu: 304             execType: jit_avx2_FP32
fire7/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire7/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire8/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 95        cpu: 95              execType: jit_avx2_1x1_FP32
fire8/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand1x1               EXECUTED       layerType: Convolution        realTime: 64        cpu: 64              execType: jit_avx2_1x1_FP32
fire8/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/expand3x3               EXECUTED       layerType: Convolution        realTime: 530       cpu: 530             execType: jit_avx2_FP32
fire8/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire8/concat                  EXECUTED       layerType: Concat             realTime: 1         cpu: 1               execType: unknown_FP32
fire9/squeeze1x1              EXECUTED       layerType: Convolution        realTime: 130       cpu: 130             execType: jit_avx2_1x1_FP32
fire9/relu_squeeze1x1         NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand1x1               EXECUTED       layerType: Convolution        realTime: 65        cpu: 65              execType: jit_avx2_1x1_FP32
fire9/relu_expand1x1          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/expand3x3               EXECUTED       layerType: Convolution        realTime: 551       cpu: 551             execType: jit_avx2_FP32
fire9/relu_expand3x3          NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
fire9/concat                  EXECUTED       layerType: Concat             realTime: 2         cpu: 2               execType: unknown_FP32
conv10                        EXECUTED       layerType: Convolution        realTime: 1898      cpu: 1898            execType: jit_avx2_1x1_FP32
relu_conv10                   NOT_RUN        layerType: ReLU               realTime: 0         cpu: 0               execType: undef
pool10/reduce                 EXECUTED       layerType: Pooling            realTime: 47        cpu: 47              execType: jit_avx_FP32
prob                          EXECUTED       layerType: SoftMax            realTime: 3         cpu: 3               execType: jit_avx2_FP32
prob_nChw8c_nchw_out_prob     EXECUTED       layerType: Reorder            realTime: 6         cpu: 6               execType: jit_uni_FP32
out_prob                      NOT_RUN        layerType: Output             realTime: 0         cpu: 0               execType: unknown_FP32
Total time: 8121     microseconds

Full device name: Intel(R) Core(TM) i5-10210U CPU @ 1.60GHz

Count:      1000 iterations
Duration:   2089.63 ms
Latency:    8.22 ms
Throughput: 478.55 FPS


###################################################

Inference Engine benchmark app completed successfully.

Pytorch をインストールする。

オフィシャルサイト PyTorch FROM RESEARCH TO PRODUCTION にアクセスして、インストールパラメータを取得する

pip install torch==1.8.1+cpu torchvision==0.9.1+cpu torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html

$ pip3 install torch==1.8.1+cpu torchvision==0.9.1+cpu torchaudio==0.8.1 -f https://download.pytorch.org/whl/torch_stable.html
Defaulting to user installation because normal site-packages is not writeable
Looking in links: https://download.pytorch.org/whl/torch_stable.html
Collecting torch==1.8.1+cpu
  Downloading https://download.pytorch.org/whl/cpu/torch-1.8.1%2Bcpu-cp38-cp38-linux_x86_64.whl (169.1 MB)
     |████████████████████████████████| 169.1 MB 26 kB/s 
Collecting torchvision==0.9.1+cpu
  Downloading https://download.pytorch.org/whl/cpu/torchvision-0.9.1%2Bcpu-cp38-cp38-linux_x86_64.whl (13.3 MB)
     |████████████████████████████████| 13.3 MB 50.1 MB/s 
Collecting torchaudio==0.8.1
  Downloading torchaudio-0.8.1-cp38-cp38-manylinux1_x86_64.whl (1.9 MB)
     |████████████████████████████████| 1.9 MB 1.9 MB/s 
Requirement already satisfied: numpy in /usr/local/lib/python3.8/dist-packages (from torch==1.8.1+cpu) (1.18.5)
Requirement already satisfied: typing-extensions in /usr/local/lib/python3.8/dist-packages (from torch==1.8.1+cpu) (3.7.4.3)
Requirement already satisfied: pillow>=4.1.1 in /usr/lib/python3/dist-packages (from torchvision==0.9.1+cpu) (7.0.0)
Installing collected packages: torch, torchvision, torchaudio
  WARNING: The scripts convert-caffe2-to-onnx and convert-onnx-to-caffe2 are installed in '/home/mizutu/.local/bin' which is not on PATH.
  Consider adding this directory to PATH or, if you prefer to suppress this warning, use --no-warn-script-location.
Successfully installed torch-1.8.1+cpu torchaudio-0.8.1 torchvision-0.9.1+cpu

推論モデルファイルの一括ダウンロード
```
$ cd ~/openvino_models
$ ls
cache  ir  models
$ python3 /opt/intel/openvino_2021/deployment_tools/tools/model_downloader/downloader.py --all
```
ダウンロードには数時間を要する。気長に待つべし。
ダウンロードされたモデルは、カレントディレクトリ直下の ./public ./intel ディレクトリ配下に格納される。

パブリックモデルの一括コンバート

$ python3 /opt/intel/openvino_2021/deployment_tools/tools/model_downloader/converter.py --all
    :

[ SUCCESS ] Generated IR version 10 model.
[ SUCCESS ] XML file: /home/mizutu/openvino_models/public/yolo-v4-tf/FP32/yolo-v4-tf.xml
[ SUCCESS ] BIN file: /home/mizutu/openvino_models/public/yolo-v4-tf/FP32/yolo-v4-tf.bin
[ SUCCESS ] Total execution time: 27.40 seconds. 
[ SUCCESS ] Memory consumed: 1802 MB. 
It's been a while, check for a new version of Intel(R) Distribution of OpenVINO(TM) toolkit here https://software.intel.com/content/www/us/en/develop/tools/openvino-toolkit/choose-download.html?cid=other&source=Prod&campid=ww_2021_bu_IOTG&content=upg_pro&medium=organic_uid_agjj or on the GitHub*

FAILED:
cocosnet
googlenet-v3-pytorch

コンバートできないモデルは２つだけ。

NEURAL COMPUTE STICK2 (NCS2) の使用設定

usersグループにカレントユーザーを加える
```
$ sudo usermod -a -G users "$(whoami)"
```

NCS2用のルールをコピーし、リブートする

$ sudo cp /opt/intel/openvino_2021/inference_engine/external/97-myriad-usbboot.rules /etc/udev/rules.d/
$ sudo udevadm control --reload-rules
$ sudo udevadm trigger
$ sudo ldconfig

確認

$ lsusb
Bus 002 Device 001: ID 1d6b:0003 Linux Foundation 3.0 root hub
Bus 001 Device 004: ID 8087:0aaa Intel Corp. 
Bus 001 Device 003: ID 03f0:334a HP, Inc HP Business Slim Keyboard
Bus 001 Device 002: ID 03f0:134a HP, Inc Optical Mouse
Bus 001 Device 005: ID 03e7:2485 Intel Movidius MyriadX
Bus 001 Device 001: ID 1d6b:0002 Linux Foundation 2.0 root hub

$ id mizutu
uid=1000(mizutu) gid=1000(mizutu) groups=1000(mizutu),4(adm),24(cdrom),27(sudo),30(dip),46(plugdev),100(users),120(lpadmin),131(lxd),132(sambashare)

OpenCV のバージョン「Ubuntu 20.04 LTS版」

開発ツールのバージョン

$ gcc --version
gcc (Ubuntu 9.3.0-17ubuntu1~20.04) 9.3.0
Copyright (C) 2019 Free Software Foundation, Inc.
This is free software; see the source for copying conditions.  There is NO
warranty; not even for MERCHANTABILITY or FITNESS FOR A PARTICULAR PURPOSE.

$ cmake --version
cmake version 3.16.3

CMake suite maintained and supported by Kitware (kitware.com/cmake).

(参考) オフィシャルにサポートされている環境

Build the Demo Applications on Linux*
The officially supported Linux* build environment is the following:

・Ubuntu* 16.04 LTS 64-bit or CentOS* 7.4 64-bit
・GCC* 5.4.0 (for Ubuntu* 16.04) or GCC* 4.8.5 (for CentOS* 7.4)
・CMake* version 2.8 or higher.

OpenVINO™ Toolkit インストールディレクトリ
```
INTEL_OPENVINO_DIR=/opt/intel/openvino_2021
```

↑

OpenVINO™ ツールキットサンプルデモのインストール †

　オフィシャルサイト Open Model Zoo Demos の手順で付属のデモを構築する。

python 拡張モジュールを構築する
- python のバージョン確認
```
mizutu@ubuntu2004dk:~$ python3 --version
python 3.8.5
```
- python3.8-dev のインストール
```
mizutu@ubuntu2004dk:~$ sudo apt install python3.8-dev
```
- 古い ~/omz_demos_build/ があれば削除しておく

新たにデモを python 拡張モジュールも含めてインストールする

$ cd /opt/intel/openvino_2021/deployment_tools/open_model_zoo/demos
$ ./build_demos.sh -DENABLE_PYTHON=ON

Setting environment variables for building demos...
[setupvars.sh] OpenVINO environment initialized
-- The C compiler identification is GNU 9.3.0
-- The CXX compiler identification is GNU 9.3.0
-- Check for working C compiler: /usr/bin/cc
-- Check for working C compiler: /usr/bin/cc -- works
-- Detecting C compiler ABI info
-- Detecting C compiler ABI info - done
-- Detecting C compile features
-- Detecting C compile features - done
-- Check for working CXX compiler: /usr/bin/c++
-- Check for working CXX compiler: /usr/bin/c++ -- works
-- Detecting CXX compiler ABI info
-- Detecting CXX compiler ABI info - done
-- Detecting CXX compile features
-- Detecting CXX compile features - done
-- Looking for C++ include unistd.h
-- Looking for C++ include unistd.h - found
-- Looking for C++ include stdint.h
-- Looking for C++ include stdint.h - found
-- Looking for C++ include sys/types.h
-- Looking for C++ include sys/types.h - found
-- Looking for C++ include fnmatch.h
-- Looking for C++ include fnmatch.h - found
-- Looking for C++ include stddef.h
-- Looking for C++ include stddef.h - found
-- Check size of uint32_t
-- Check size of uint32_t - done
-- Looking for strtoll
-- Looking for strtoll - found
-- Found InferenceEngine: /opt/intel/openvino_2021/deployment_tools/inference_engine/lib/intel64/libinference_engine.so (Required is at least version "2.0") 
-- Found OpenCV: /opt/intel/openvino_2021.2.185/opencv (found version "4.5.1") found components: core imgcodecs videoio 
-- Found OpenCV: /opt/intel/openvino_2021.2.185/opencv (found version "4.5.1") found components: core imgproc 
-- Looking for pthread.h
-- Looking for pthread.h - found
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD
-- Performing Test CMAKE_HAVE_LIBC_PTHREAD - Failed
-- Looking for pthread_create in pthreads
-- Looking for pthread_create in pthreads - not found
-- Looking for pthread_create in pthread
-- Looking for pthread_create in pthread - found
-- Found Threads: TRUE  
-- Found PythonInterp: /usr/bin/python3 (found suitable version "3.8.5", minimum required is "3.6") 
-- Found PythonLibs: /usr/lib/x86_64-linux-gnu/libpython3.8.so (found suitable exact version "3.8.5") 
-- Found OpenCV: /opt/intel/openvino_2021.2.185/opencv (found suitable version "4.5.1", minimum required is "4") found components: core imgproc 
-- Found OpenCV: /opt/intel/openvino_2021.2.185/opencv (found suitable version "4.5.1", minimum required is "4") found components: core 
-- Configuring done
-- Generating done
-- Build files have been written to: /home/mizutu/omz_demos_build
Scanning dependencies of target gflags_nothreads_static
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In file included from /usr/include/string.h:495,
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In function ‘char* strncpy(char*, const char*, size_t)’,
    inlined from ‘void SWIG_Python_FixMethods(PyMethodDef*, swig_const_info*, swig_type_info**, swig_type_info**)’ at /opt/intel/openvino_2021/deployment_tools/open_model_zoo/demos/python_demos/speech_recognition_demo/ctcdecode-numpy/ctcdecode_numpy/decoders_wrap.cpp:12616:22,
    inlined from ‘PyObject* PyInit__impl()’ at /opt/intel/openvino_2021/deployment_tools/open_model_zoo/demos/python_demos/speech_recognition_demo/ctcdecode-numpy/ctcdecode_numpy/decoders_wrap.cpp:12711:25:
/usr/include/x86_64-linux-gnu/bits/string_fortified.h:106:34: warning: ‘char* __builtin_strncpy(char*, const char*, long unsigned int)’ output truncated before terminating nul copying 10 bytes from a string of the same length [-Wstringop-truncation]
  106 |   return __builtin___strncpy_chk (__dest, __src, __len, __bos (__dest));
      |          ~~~~~~~~~~~~~~~~~~~~~~~~^~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
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[ 89%] Building CXX object multi_channel/human_pose_estimation_demo/CMakeFiles/multi_channel_human_pose_estimation_demo.dir/postprocessor.cpp.o
[ 90%] Building CXX object multi_channel/human_pose_estimation_demo/CMakeFiles/multi_channel_human_pose_estimation_demo.dir/render_human_pose.cpp.o
[ 91%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/align_transform.cpp.o
[ 92%] Linking CXX executable ../../intel64/Release/multi_channel_human_pose_estimation_demo
[ 92%] Built target multi_channel_human_pose_estimation_demo
[ 93%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/cnn.cpp.o
[ 94%] Linking CXX executable ../intel64/Release/object_detection_demo
[ 94%] Built target object_detection_demo
[ 94%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/detector.cpp.o
[ 95%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/logger.cpp.o
[ 96%] Linking CXX executable ../intel64/Release/segmentation_demo_async
[ 96%] Built target segmentation_demo_async
[ 97%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/reid_gallery.cpp.o
[ 97%] Linking CXX executable ../../intel64/Release/multi_channel_object_detection_demo_yolov3
[ 98%] Building CXX object smart_classroom_demo/CMakeFiles/smart_classroom_demo.dir/src/tracker.cpp.o
[ 98%] Built target multi_channel_object_detection_demo_yolov3
[ 99%] Linking CXX executable ../intel64/Release/pedestrian_tracker_demo
[ 99%] Built target pedestrian_tracker_demo
[100%] Linking CXX executable ../intel64/Release/smart_classroom_demo
[100%] Built target smart_classroom_demo
Scanning dependencies of target ie_samples
[100%] Built target ie_samples

Build completed, you can find binaries for all demos in the /home/mizutu/omz_demos_build/intel64/Release subfolder.

デモソフトはカレントディレクトリ下の ~/omz_demos_build/intel64/Release/ に構築される。

ホームディレクトリにデモ実行環境設定のシェルスクリプトを作成する。

omz_demos.sh

#!/bin/sh

echo [OMZ_demos.sh] Open Model Zoo Demos environment initialized

export PYTHONPATH=$PYTHONPATH:/home/mizutu/omz_demos_build/intel64/Release/lib
export PYTHONPATH=$PYTHONPATH:/opt/intel/openvino_2021/deployment_tools/open_model_zoo/demos/python_demos/common

Python デモ実行時にモジュールエラーが発生することがわかり、最後の1行を追加した。(2021/03/31)