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Imagine TensorFlow, but aimed at HPC. Produces a data flow graph, where the
edges carry arrays and the nodes are (give or take) static-control programs
that compute array outputs from inputs, possibly (but not necessarily)
expressed in Loopy <https://github.com/inducer/loopy>__. A core assumption is
that the graph represents a computation that's being repeated often enough that
it is worthwhile to do expensive processing on it (code generation, fusion,
OpenCL compilation, etc).
Documentation <https://documen.tician.de/pytato>__ (read how things work, see an example)Github <https://github.com/inducer/pytato>__ (get latest source code, file bugs)Pytato is licensed to you under the MIT/X Consortium license. See
the documentation <https://documen.tician.de/pytato/misc.html>__
for further details.
Pytato is written to pose no particular restrictions on the version of numpy used for execution. To use mypy-based type checking on Pytato itself or packages using Pytato, numpy 1.20 or newer is required, due to the typing-based changes to numpy in that release.
Furthermore, pytato now uses type promotion rules based on those in
numpy <https://numpy.org/devdocs/numpy_2_0_migration_guide.html#changes-to-numpy-data-type-promotion>__ that should result in the same
data types as the currently installed version of numpy.