Install Mayaku

Requirements

Python 3.10, 3.11 or 3.12.
Linux or macOS.
PyTorch 2.4 or newer and torchvision 0.19 or newer. They install with Mayaku if you don't already have them.

Install

Bash

pip install mayaku

This installs everything needed to train, predict, evaluate and download models: torch, torchvision, numpy, opencv-python-headless, pydantic, pyyaml, typer and pycocotools. It also installs the mayaku command.

GPU builds of PyTorch

pip install mayaku installs whichever PyTorch build pip picks by default. On an NVIDIA machine, make sure that build has CUDA support. If it doesn't, install the CUDA build of PyTorch first by following the selector at https://pytorch.org/get-started/locally/, then install Mayaku:

Bash

# example: CUDA 12.8 wheels; pick the index URL that pytorch.org gives you
pip install torch torchvision --index-url https://download.pytorch.org/whl/cu128
pip install mayaku

On Apple Silicon the default macOS wheels already include MPS support.

Optional packages for export

Each export target is an optional extra. Install only the ones you deploy to:

Target	Install	Notes
ONNX	`pip install "mayaku[onnx]" onnxruntime`	See the onnxruntime note below.
Core ML	`pip install "mayaku[coreml]"`	The `.mlpackage` can be written on any OS, but it is only checked and run on macOS.
OpenVINO	`pip install "mayaku[openvino]"`	Intel CPUs, integrated GPUs and NPUs.
TensorRT	`pip install "mayaku[tensorrt]"`	Linux with an NVIDIA GPU. Installs `tensorrt` and `nvidia-modelopt[onnx]`.

onnxruntime is not in any extra. CPU and GPU machines need different packages, so install the one for your machine yourself:

Bash

pip install onnxruntime        # CPU, Apple Silicon
pip install onnxruntime-gpu    # NVIDIA GPU (CUDA)

You need onnxruntime to export to ONNX as well as to run an ONNX model. After writing the file, mayaku export onnx runs it once with onnxruntime to check its outputs against the PyTorch model.

Check the installation

Bash

python -c "import mayaku; print(mayaku.__version__)"
mayaku --help

You can also run the command line as a module. It is the same program:

Bash

python -m mayaku.cli --help

Devices

Every command and function that runs a model takes a device argument (--device on the command line):

Value	Meaning
`auto` (default)	CUDA if available, else MPS (Apple Silicon), else CPU.
`cuda`	The first NVIDIA GPU. `cuda:1` and so on select another GPU.
`mps`	Apple Silicon GPU.
`cpu`	CPU only.

Training on more than one GPU is covered in Training. It needs CUDA. MPS supports a single device only.

On Apple Silicon, Mayaku sets the environment variable PYTORCH_ENABLE_MPS_FALLBACK=1 when it is imported. Any PyTorch operation without an MPS kernel then runs on the CPU instead of raising an error. If you set the variable yourself before importing Mayaku, including to 0, your value is kept.

Install from source

Bash

git clone https://github.com/datamarkin/mayaku.git
cd mayaku
pip install -e .

Add extras the same way, for example pip install -e ".[onnx,openvino]".

If the mayaku command fails with ImportError: cannot import name 'app' from 'mayaku.cli.__main__' after you update a source checkout, the installed command script is out of date. Run pip install -e . again to regenerate it.