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TensorStudio 2.0.0

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@imattas imattas released this 08 Jul 12:44
v2.0.0
53756be

TensorStudio 2.0.0 is a tested v2 foundation release. It adds concrete roadmap work while keeping unimplemented accelerator and distributed systems honest.

Highlights:

  • Dataset manifests, SHA-256 file checksums, manifest validation, and a small map-style dataset cache wrapper.
  • Compact attention APIs: scaled_dot_product_attention, MultiHeadSelfAttention, and TransformerEncoderBlock.
  • Experimental CSR sparse tensors with dense/COO conversion and CSR sparse-dense matmul.
  • Quantization calibration helpers and quantization error reporting.
  • CPU from_dlpack() import for DLPack-compatible providers through NumPy.
  • ONNX Runtime provider discovery and compatibility diagnostics.
  • Roadmap rewritten to show remaining work only.

Validation:

  • python -m pip install -e .[dev,docs]
  • python test_all.py --quiet
  • python -m ruff check .
  • python -m mypy python\tensorstudio
  • python -m pytest -q
  • python -m mkdocs build --strict
  • python benchmark_all.py --check-thresholds
  • python benchmarks\bench_matmul.py
  • python -m build
  • python -m twine check dist*
  • python tools\verify_artifacts.py --wheel-dir dist --sdist-dir dist

Still not claimed as complete:

  • No CUDA or Metal tensor execution kernels.
  • No production multi-process distributed runtime.
  • No machine-code JIT/compiler.
  • No full TensorFlow/PyTorch compatibility.
  • No broad performance superiority claim.
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