deploy-dia

Deploy Dia TTS on reComputer Jetson

Dia is an expressive neural speech generation model that produces natural multi-speaker audio from text. This skill deploys it on Jetson with a Gradio web interface.

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Execution model

Run one phase at a time. After each phase:

• Relay all output to the user.
• If output contains [STOP] → stop immediately, consult the failure decision tree.
• If output ends with [OK] → tell the user "Phase N complete" and proceed to the next phase.

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Prerequisites

Requirement	Detail
Jetson device	8GB+ RAM (e.g. reComputer J4012 with Orin NX 16GB)
JetPack	6.1 or later
Python	3.10 with pip
Network	Internet access for downloading wheels and cloning repo

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Phase 1 — Download and install aarch64 PyTorch wheels (~5–10 min)

Download the following wheels from the Seeed shared drive:

• torch-2.7.0-cp310-cp310-linux_aarch64.whl
• torchaudio-2.7.0-cp310-cp310-linux_aarch64.whl
• triton-3.3.0-cp310-cp310-linux_aarch64.whl

Install them:

pip install torch-2.7.0-cp310-cp310-linux_aarch64.whl
pip install torchaudio-2.7.0-cp310-cp310-linux_aarch64.whl
pip install triton-3.3.0-cp310-cp310-linux_aarch64.whl

Verify:

python3 -c "import torch; print(torch.__version__); print('CUDA:', torch.cuda.is_available())"

[OK] when torch imports and CUDA is available. [STOP] if wheel install fails.

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Phase 2 — Clone Dia and patch dependencies (~2 min)

git clone https://github.com/nari-labs/dia.git
cd dia

Edit pyproject.toml to comment out the torch, torchaudio, and triton dependency lines (lines 19–22) since we installed custom Jetson wheels:

sed -i 's/^\(\s*"torch.*\)/#\1/' pyproject.toml
sed -i 's/^\(\s*"torchaudio.*\)/#\1/' pyproject.toml
sed -i 's/^\(\s*"triton.*\)/#\1/' pyproject.toml

Install Dia and fix numpy:

pip install -e .
pip install numpy==1.26.4

[OK] when pip install -e . completes without error. [STOP] if dependency resolution fails.