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content/learning-paths/microcontrollers/introduction-to-tinyml-on-arm/env-setup-5.md

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@@ -21,13 +21,25 @@ The Ubuntu version should be `20.04 or higher`. The `x86_64` architecture must b
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If you want to use Arm Virtual Hardware the [Arm Virtual Hardware install guide](/install-guides/avh#corstone) provides setup instructions.
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## Setup on Host Machine
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1. Setup if you don't have access to the physical board: We would use the Corstone-300 FVP, it is pre-configured.
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2. Setup if you have access to the board: Skip to "Compilers" Section
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### Corstone-300 FVP {#fvp} Setup for ExecuTorch
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For Arm Virtual Hardware users, the Corstone-300 FVP is pre-installed.
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To install and set up the Corstone-300 FVP and ExecuTorch on your machine, refer to [Building and Running ExecuTorch with ARM Ethos-U Backend](https://pytorch.org/executorch/stable/executorch-arm-delegate-tutorial.html)). Follow this tutorial till "Install the TOSA reference model" Section. It should be the last thing you do from this tutorial.
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Since you already have the compiler installed from the above tutorial, skip to ## Install PyTorch.
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### Compilers
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The examples can be built with [Arm Compiler for Embedded](https://developer.arm.com/Tools%20and%20Software/Arm%20Compiler%20for%20Embedded) or [Arm GNU Toolchain](https://developer.arm.com/Tools%20and%20Software/GNU%20Toolchain).
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Both compilers are pre-installed in Arm Virtual Hardware.
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Alternatively, if you are using Arch Linux or its derivatives, you can use Pacman to install GCC.
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Alternatively, if you use Arch Linux or its derivatives, you can use Pacman to install GCC.
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Use the install guides to install the compilers on your computer:
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- [Arm Compiler for Embedded](/install-guides/armclang/)
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pacman -S aarch64-linux-gnu-gcc
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```
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### Corstone-300 FVP {#fvp}
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To install the Corstone-300 FVP on your computer refer to the [install guide for Arm Ecosystem FVPs](/install-guides/fm_fvp).
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The Corstone-300 FVP is pre-installed in Arm Virtual Hardware.
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## Install PyTorch
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The latest version needs Python 3.8 or later
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1. Follow the [Setting Up ExecuTorch guide](https://pytorch.org/executorch/stable/getting-started-setup.html ) to install it.
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2. Activate the `executorch` virtual environment from the installation guide:
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2. Activate the `executorch` virtual environment from the installation guide to ensure it is ready for use:
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```console
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conda activate executorch
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## Setup on Grove - Vision AI Module V2
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Due to its constrained environment, we'll focus on lightweight, optimized tools and models (will be introcuded in the next learning path).
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**Kindly Note:** Only follow this part of the tutorial if you have the board.
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Due to its constrained environment, we'll focus on lightweight, optimized tools and models (which will be introduced in the next learning path).
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![Hardware Overview #center](Overview.png)
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