Difference between revisions of "ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 6"

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== History ==
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= History =
 
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==Introduction==
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=Introduction=
 
This Technical Note (TN for short) belongs to the series introduced [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1|here]]. The configuration here described is similar to the one used for [[ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 3|this article]] of the same series. With respect to that TN, the main differences are:
 
This Technical Note (TN for short) belongs to the series introduced [[ML-TN-001_-_AI_at_the_edge:_comparison_of_different_embedded_platforms_-_Part_1|here]]. The configuration here described is similar to the one used for [[ML-TN-001 - AI at the edge: comparison of different embedded platforms - Part 3|this article]] of the same series. With respect to that TN, the main differences are:
 
* PyTorch framework was used instead of TensorFlow
 
* PyTorch framework was used instead of TensorFlow
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These changes allowed to increase performance as detailed in the rest of the document.
 
These changes allowed to increase performance as detailed in the rest of the document.
  
==PyTorch-based development flow==
+
=PyTorch-based development flow=
  
 
TBD
 
TBD
  
==Results==
+
=Results=
 
TBD
 
TBD

Latest revision as of 13:13, 24 September 2021

Info Box
NeuralNetwork.png Applies to Machine Learning


History[edit | edit source]

Version Date Notes
1.0.0 October 2021 First public release

Introduction[edit | edit source]

This Technical Note (TN for short) belongs to the series introduced here. The configuration here described is similar to the one used for this article of the same series. With respect to that TN, the main differences are:

  • PyTorch framework was used instead of TensorFlow
  • Vitis AI was upgraded to version 1.3.2.

Also, two significant improvements were implemented:

  • Structural pruning of the model
  • Model review resulting in the removal of the fully connected layer.

These changes allowed to increase performance as detailed in the rest of the document.

PyTorch-based development flow[edit | edit source]

TBD

Results[edit | edit source]

TBD