# Bert Benchmark Python* Sample {#openvino_inference_engine_ie_bridges_python_sample_bert_benchmark_README}

@sphinxdirective

This sample demonstrates how to estimate performance of a Bert model using Asynchronous Inference Request API. Unlike :doc:`demos <omz_demos>` this sample doesn't have configurable command line arguments. Feel free to modify sample's source code to try out different options.

The following Python API is used in the application:

+--------------------------------+-------------------------------------------------+----------------------------------------------+
| Feature                        | API                                             | Description                                  |
+================================+=================================================+==============================================+
| OpenVINO Runtime Version       | [openvino.runtime.get_version]                  | Get Openvino API version.                    |
+--------------------------------+-------------------------------------------------+----------------------------------------------+
| Basic Infer Flow               | [openvino.runtime.Core],                        | Common API to do inference: compile a model. |
|                                | [openvino.runtime.Core.compile_model]           |                                              |
+--------------------------------+-------------------------------------------------+----------------------------------------------+
| Asynchronous Infer             | [openvino.runtime.AsyncInferQueue],             | Do asynchronous inference.                   |
|                                | [openvino.runtime.AsyncInferQueue.start_async], |                                              |
|                                | [openvino.runtime.AsyncInferQueue.wait_all]     |                                              |
+--------------------------------+-------------------------------------------------+----------------------------------------------+
| Model Operations               | [openvino.runtime.CompiledModel.inputs]         | Get inputs of a model.                       |
+--------------------------------+-------------------------------------------------+----------------------------------------------+

How It Works
####################

The sample downloads a model and a tokenizer, export the model to onnx, reads the exported model and reshapes it to enforce dynamic input shapes, compiles the resulting model, downloads a dataset and runs benchmarking on the dataset.

You can see the explicit description of
each sample step at :doc:`Integration Steps <openvino_docs_OV_UG_Integrate_OV_with_your_application>` section of "Integrate OpenVINO™ Runtime with Your Application" guide.

Running
####################

Install the ``openvino`` Python package:

.. code-block:: sh

   python -m pip install openvino


Install packages from ``requirements.txt``:

.. code-block:: sh

   python -m pip install -r requirements.txt


Run the sample

.. code-block:: sh

   python bert_benchmark.py


Sample Output
####################

The sample outputs how long it takes to process a dataset.

See Also
####################

* :doc:`Integrate the OpenVINO™ Runtime with Your Application <openvino_docs_OV_UG_Integrate_OV_with_your_application>`
* :doc:`Using OpenVINO Samples <openvino_docs_OV_UG_Samples_Overview>`
* :doc:`Model Downloader <omz_tools_downloader>`
* :doc:`Model Optimizer <openvino_docs_MO_DG_Deep_Learning_Model_Optimizer_DevGuide>`

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