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17 October 2024
| 11:39 | X-LINUX-RT expansion package - v5.1.0 diffhist +40 Registered User | ||||
| N 10:54 | X-LINUX-RT expansion package diffhist +608 Registered User (Created page with "<noinclude>{{ApplicableFor |MPUs list=STM32MP13x, STM32MP15x, STM32MP25x |MPUs checklist=STM32MP13x,STM32MP15x, STM32MP25x }}</noinclude> {{:X-LINUX-RT_expansion_package_-_v5.1.0}} ==Archives 25px|link=== {| class="st-table" ! X-LINUX-RT release !! Release note |- | X-LINUX-RT v5.0.0 ||{{EcosystemFlow/Archives | custom=Basic | flow=v5 | page=X-LINUX-RT_expansion_package_-_v5.0.0}} |} <br> ==References== <noinclude> {{PublicationRequestId | 26...") | ||||
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N 10:44 | X-LINUX-RT expansion package - v5.0.0 3 changes history +9,882 [Registered User (3×)] | |||
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10:44 (cur | prev) −10,138 Registered User Tag: 2017 source edit | ||||
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10:39 (cur | prev) +1 Registered User (Page created from X-LINUX-RT_expansion_package) Tag: 2017 source edit | ||||
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10:37 (cur | prev) +20,019 Registered User (Created page with "<noinclude>{{ApplicableFor |MPUs list=STM32MP13x, STM32MP15x, STM32MP25x |MPUs checklist=STM32MP13x,STM32MP15x, STM32MP25x }}</noinclude> ==Article purpose== Purpose of this article is to: * introduce the X-LINUX-RT expansion package * define the hardware & software deliverables to use the X-LINUX-RT package, * describe all steps to integrate the X-LINUX-RT package and associated expected results * give some use case examples enabled by the X-LINUX-RT package <div clas...") | |||
27 September 2024
| 14:12 | System build troubleshooting grid diffhist +25 Registered User | ||||
25 September 2024
| 17:19 | Example of directory structure for Packages diffhist +25 Registered User | ||||
23 September 2024
| N 10:44 | How to retrain a NN model using ONNXRuntime on STM32MP2x diffhist +678 Registered User (Created page with "{{ApplicableFor |MPUs list=STM32MP13x, STM32MP15x, STM32MP25x |MPUs checklist=STM32MP13x, STM32MP15x, STM32MP25x }} <noinclude></noinclude> == Article purpose == This article describes how to run a simple training session on the STM32MP2x using the ONNXRuntime™ training package. It is an example based on an image classification application which aims to retrain a {{Highlight|mobilenetV2}} model in floating point format on the Cortex-A of the STM32MP2x. {{Information...") | ||||