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recipes_source/recipes/profiler_recipe.py

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"""
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######################################################################
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"""
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This recipe explains how to use PyTorch profiler and measure the time and
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memory consumption of the model's operators.
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#
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# This recipe explains how to use PyTorch profiler and measure the time and
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# memory consumption of the model's operators.
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Introduction
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------------
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PyTorch includes a simple profiler API that is useful when user needs
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to determine the most expensive operators in the model.
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# Introduction
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# ------------
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# PyTorch includes a simple profiler API that is useful when user needs
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# to determine the most expensive operators in the model.
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In this recipe, we will use a simple Resnet model to demonstrate how to
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use profiler to analyze model performance.
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# In this recipe, we will use a simple Resnet model to demonstrate how to
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# use profiler to analyze model performance.
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Prerequisites
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---------------
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- ``torch >= 1.9``
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# Prerequisites
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# ---------------
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# - ``torch >= 1.9``
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Setup
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-----
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To install ``torch`` and ``torchvision`` use the following command:
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# Setup
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# -----
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# To install ``torch`` and ``torchvision`` use the following command:
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.. code-block:: sh
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# .. code-block:: sh
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pip install torch torchvision
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# pip install torch torchvision
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"""
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#
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######################################################################
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# Steps

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