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Add benchmark samples (#13388)

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* Add sync_bnehcmark

* Fix Unix comilation

* niter->time

* Explain main loop

* samples: factor out common

* Code style

* clang-format -i

* return 0; -> return EXIT_SUCCESS;, +x

* Update throughput_benchmark

* Add READMEs

* Fix READMEs refs

* Add sync_benchmark.py

* Add niter, infer_new_request, -pc

* from datetime import timedelta

* Fix niter and seconds_to_run

* Add disclaimer about benchmark_app performance

* Update samples/cpp/benchmark/sync_benchmark/README.md

* Add dynamic_shape_bert_benhcmark

* Add dynamic_shape_detection_benchmark

* Adopt for detr-resnet50

* Remove sync_benchmark2, throughput_benchmark2, perf counters

* clang-format -i

* Fix flake8

* Add README.md

* Add links to sample_dynamic_shape_bert_benchmark

* Add softmax

* nameless LatencyMetrics

* parent.parent -> parents[2]

* Add bert_benhcmark sample

* Code style

* Add bert_benhcmark/README.md

* rm -r samples/python/benchmark/dynamic_shape_bert_benhcmark/

* rm -r samples/cpp/benchmark/dynamic_shape_detection_benchmark/

* bert_benhcmark/README.md: remove dynamic shape

* Remove add_subdirectory(dynamic_shape_detection_benchmark)

* flake8

* samples: Add a note about CUMULATIVE_THROUGHPUT, don’t expect get_property() to throw, don’t introduce json dependency for samples/cpp/common

* / namespace

* Add article

* namespace -> static

* Update README, seconds_ro_run 10, niter 10, no inter alinment

* percentile->median

* benchmark samples: use generate(), align logs, update READMEs

* benchmakr samples: remove percentile()

* samples/python/benchmark/bert_benhcmark/bert_benhcmark.py: report average sequence length and processing time

* Python samples: move requirements.txt to every sample

* Remove numpy from requirements.txt

* Remove Building section from Python samples, install only required extras from openvino-dev, set up environment for bert_benhcmark, report duration for bert_benhcmark

* Install openvino-dev for Hello Reshape SSD C++ Sample
This commit is contained in:
Zlobin Vladimir
2022-12-05 15:12:53 +04:00
committed by GitHub
parent a96f2af2f4
commit 67d25d7099
33 changed files with 1102 additions and 103 deletions
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9
samples/cpp/classification_sample_async/README.md
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@@ -67,10 +67,9 @@ Options:
Available target devices: <devices>
```
To run the sample, you need specify a model and image:
- you can use [public](@ref omz_models_group_public) or [Intel's](@ref omz_models_group_intel) pre-trained models from the Open Model Zoo. The models can be downloaded using the [Model Downloader](@ref omz_tools_downloader).
- you can use images from the media files collection available at https://storage.openvinotoolkit.org/data/test_data.
To run the sample, you need to specify a model and image:
- You can use [public](@ref omz_models_group_public) or [Intel's](@ref omz_models_group_intel) pre-trained models from the Open Model Zoo. The models can be downloaded using the [Model Downloader](@ref omz_tools_downloader).
- You can use images from the media files collection available at https://storage.openvinotoolkit.org/data/test_data.
> **NOTES**:
>
@@ -84,7 +83,7 @@ To run the sample, you need specify a model and image:
1. Install the `openvino-dev` Python package to use Open Model Zoo Tools:
```
python -m pip install openvino-dev[caffe,onnx,tensorflow2,pytorch,mxnet]
python -m pip install openvino-dev[caffe]
```
2. Download a pre-trained model using: