2.4. Windows Setup

This guide provides Windows-specific instructions for installing and using Tiny ML Tensorlab.

Note

While Tiny ML Tensorlab works on Windows, Linux is the primary development platform. Some features may have better support on Linux.

2.4.1. Option 1: Native Windows Installation

Step 1: Install Python 3.10

Using pyenv-win (Recommended):

# Run PowerShell as Administrator
Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

# Install pyenv-win
Invoke-WebRequest -UseBasicParsing -Uri "https://raw.githubusercontent.com/pyenv-win/pyenv-win/master/pyenv-win/install-pyenv-win.ps1" -OutFile "./install-pyenv-win.ps1"
& "./install-pyenv-win.ps1"

# Restart PowerShell, then:
pyenv install 3.10.14
pyenv global 3.10.14

# Verify
python --version

Step 2: Install Git

Download and install Git from https://git-scm.com/download/win

During installation:

Select “Git from the command line and also from 3rd-party software”
Select “Checkout as-is, commit Unix-style line endings”

Step 3: Clone and Install

# Clone repository
git clone https://github.com/TexasInstruments/tinyml-tensorlab.git
cd tinyml-tensorlab

# Create virtual environment
python -m venv venv
.\venv\Scripts\Activate.ps1

# Install components
cd tinyml-modelmaker
pip install -e .

cd ..\tinyml-tinyverse
pip install -e .

cd ..\tinyml-modeloptimization\torchmodelopt
pip install -e .

cd ..\..\tinyml-modelzoo
pip install -e .

Step 4: Run Example

cd tinyml-modelzoo
run_tinyml_modelzoo.bat examples\generic_timeseries_classification\config.yaml

2.4.2. Option 2: WSL2 (Recommended for Full Compatibility)

Windows Subsystem for Linux provides better compatibility with the toolchain.

Step 1: Enable WSL2

Open PowerShell as Administrator:

wsl --install

Restart your computer when prompted.

Step 2: Install Ubuntu

Open Microsoft Store and install “Ubuntu 22.04 LTS”.

Launch Ubuntu and set up your username/password.

Step 3: Install in Ubuntu

# Update packages
sudo apt update && sudo apt upgrade -y

# Install dependencies
sudo apt install -y build-essential git curl

# Install pyenv
curl https://pyenv.run | bash

# Add to ~/.bashrc
echo 'export PYENV_ROOT="$HOME/.pyenv"' >> ~/.bashrc
echo 'export PATH="$PYENV_ROOT/bin:$PATH"' >> ~/.bashrc
echo 'eval "$(pyenv init -)"' >> ~/.bashrc
source ~/.bashrc

# Install Python 3.10
pyenv install 3.10.14
pyenv global 3.10.14

# Clone and install
git clone https://github.com/TexasInstruments/tinyml-tensorlab.git
cd tinyml-tensorlab/tinyml-modelmaker
./setup_all.sh

Step 4: Run Examples

cd ~/tinyml-tensorlab/tinyml-modelzoo
./run_tinyml_modelzoo.sh examples/generic_timeseries_classification/config.yaml

2.4.3. Path Configuration

Long Path Support (Native Windows)

Enable long path support for deep directory structures:

# Run as Administrator
New-ItemProperty -Path "HKLM:\SYSTEM\CurrentControlSet\Control\FileSystem" -Name "LongPathsEnabled" -Value 1 -PropertyType DWORD -Force

Environment Variables

Set up paths for TI tools (if compiling for devices):

# Add to your profile or set in System Properties
$env:C2000_CG_ROOT = "C:\ti\ccs\tools\compiler\ti-cgt-c2000_22.6.1.LTS"
$env:C2000WARE_ROOT = "C:\ti\c2000\C2000Ware_5_03_00_00"

2.4.4. Common Windows Issues

PowerShell Execution Policy

If you get “running scripts is disabled”:

Set-ExecutionPolicy -ExecutionPolicy RemoteSigned -Scope CurrentUser

Path Too Long Errors

Clone to a short path (e.g., C:\dev\tensorlab) or enable long paths.

Line Ending Issues

Configure Git to handle line endings:

git config --global core.autocrlf true

Virtual Environment Activation

If venv\Scripts\Activate.ps1 fails:

# Alternative activation
.\venv\Scripts\activate.bat

# Or run Python directly
.\venv\Scripts\python.exe -m tinyml_modelmaker ...

2.4.5. GPU Support on Windows

For CUDA support (useful for NAS):

Install NVIDIA drivers from https://www.nvidia.com/drivers
Install CUDA Toolkit from https://developer.nvidia.com/cuda-downloads
Verify with:

python -c "import torch; print(torch.cuda.is_available())"

2.4.6. WSL2 vs Native Windows Comparison

Feature	Native Windows	WSL2
Setup Complexity	Moderate	Higher initially
Shell Scripts	Requires .bat files	Full bash support
Compilation	Full support	Full support
GPU Support	Native CUDA	WSL2 CUDA (newer)
CCS Integration	Direct	Requires file sharing
Recommended For	Quick start	Full development

2.4.7. Next Steps

Environment Variables - Configure TI compiler paths
Quickstart - Train your first model