munet-nn 0.1.1

MuNet: lightweight C++ tensor/autograd framework with Python bindings

μNet

μNet is a lightweight C++ tensor + autograd framework with Python bindings. It supports CPU, CUDA and Vulkan backends. The goal of the project is to interop with existing frameworks (torch / onnx) and allow for mixed gpu training & inference.

Setup / Runtime requirements

pip install munet_nn

μNet has provisioning enabled for accelerated support detection, you can install the accelerated backends by specifying the appropriate feature targeting:

vulkan: munet_nn["vk"]

cuda 13: munet_nn["cu13_vk"]

cuda 12: munet_nn["cu12_vk"]

Current repository state

• Core runtime (munet_core) is used by both training and inference surfaces.
• Training APIs (nn, optim, losses, autograd) are available in C++ and Python.
• Inference APIs and serialization flows are available (munet_inference, demos under demos/inference/ and demos/serialization/).
• Backend dispatch which includes:
  • capability-based support checks,
  • fallback reason accounting,
  • accelerator→CPU fallback telemetry counters,
  • optional fail-fast mode for unexpected accelerator fallbacks.

ENV Vars

• MUNET_PROFILE=1 — profiler collection + summary on process exit or manual flush.
• MUNET_DEBUG=1 — debug logging/checks.
• MUNET_LOG_LEVEL=0..3 — log verbosity.
• MUNET_DISPATCH_DECISION_DUMP=1 — emit dispatch decision lines.
• MUNET_FAIL_FAST_ACCELERATOR_CPU_FALLBACK=1 — throw immediately when a CUDA/Vulkan tensor is dispatched to CPU fallback.

Build

Requirements

• CMake 3.10+
• C++17 compiler
• Python 3.10+
• Optional: CUDA Toolkit (nvcc)
• Optional: Vulkan SDK (glslc in PATH)

Python publishing

There are two PyPi streams for μNet. Publishing is done via release tags, dev* tags will push to the test stream and v* tags to production.

Test stream

• https://test.pypi.org/project/munet-nn/

Prod stream

• https://pypi.org/project/munet-nn/

When building a release ensure that the version in pyproject.toml matches the tag.

Tests

make unit-test      # debug gtest (C++)
make py-test        # Python integration test suite
make perf-test      # opt-in perf suite (sets MUNET_RUN_PERF_TESTS=1)

For selective C++ tests:

./build/debug/munet_tests --gtest_filter=*BackendManager*

Docs

• Main docs index: documentation/index.md
• Architecture docs: documentation/architecture/
• Performance/profiling guide: documentation/performance/profiling.md

Serve docs locally:

pip install mkdocs mkdocs-material
mkdocs serve

Demos

See demos/README.md for the full categorized catalog:

• demos/visual/ (object/semantic/instance segmentation categories)
• demos/operators/
• demos/serialization/
• demos/inference/
• demos/multigpu/
• demos/transformers/