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@@ -172,7 +172,7 @@ To deploy the OpenVINO Runtime components from the development machine to the ta
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3. On a target Linux system, to run inference install additional dependencies by running the ``install_openvino_dependencies.sh`` script:
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.. code-block: sh
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.. code-block:: sh
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cd <destination_dir>/openvino/install_dependencies
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sudo -E ./install_openvino_dependencies.sh
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@@ -165,7 +165,7 @@ You can use performance data (in sample applications, it is the option ``-pc``)
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Here is an example of the output for Googlenet v1 running on HDDL (device no longer supported) with fallback to CPU:
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.. code-block: sh
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.. code-block:: sh
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subgraph1: 1. input preprocessing (mean data/HDDL):EXECUTED layerType: realTime: 129 cpu: 129 execType:
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subgraph1: 2. input transfer to DDR:EXECUTED layerType: realTime: 201 cpu: 0 execType:
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@@ -183,7 +183,7 @@ Sample Usage
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OpenVINO™ sample programs can use the Heterogeneous execution used with the ``-d`` option:
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.. code-block: sh
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.. code-block:: sh
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./hello_classification <path_to_model>/squeezenet1.1.xml <path_to_pictures>/picture.jpg HETERO:GPU,CPU
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@@ -118,7 +118,7 @@ Step 2: Configure the Environment
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You must update several environment variables before you can compile and run OpenVINO™ applications. Open the Command Prompt, and run the ``setupvars.bat`` batch file to temporarily set your environment variables. If your ``<INSTALL_DIR>`` is not ``C:\Program Files (x86)\Intel\openvino_2023``, use the correct directory instead.
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.. code-block: sh
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.. code-block:: sh
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"C:\Program Files (x86)\Intel\openvino_2023\setupvars.bat"
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@@ -35,7 +35,7 @@
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**Example**
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.. code-block: cpp
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.. code-block:: cpp
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<layer ... type="Mish">
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<input>
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@@ -75,7 +75,7 @@ Select quantization parameters
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Default Quantization algorithm has mandatory and optional parameters which are defined as a dictionary:
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.. code-block: python
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.. code-block:: python
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{
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"name": "DefaultQuantization",
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