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  <h4>Profiling the memory usage</h4>
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- <p>Using the Pytorch profiler we can understand how memory is allocated througho ut training. We can see that memory utilization is not a static thing but varies a lot during training and during a training step:</p>
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  <aside>Check out <a target="_self" href="#a1%3A_distributed_training_profiling" class="">A1: Distributed Training Profiling</a> for a walkthrough how to profile your model.</aside>
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  <h4>Profiling the memory usage</h4>
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+ <p>Using the Pytorch profiler we can understand how memory is allocated throughout training. We can see that memory utilization is not a static thing but varies a lot during training and during a training step:</p>
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  <aside>Check out <a target="_self" href="#a1%3A_distributed_training_profiling" class="">A1: Distributed Training Profiling</a> for a walkthrough how to profile your model.</aside>
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