Get Descriptions of Array Computations via Lazy Evaluation
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. 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 (read how things work, see an example)
Github (get latest source code, file bugs)
Pytato is licensed to you under the MIT/X Consortium license. See the documentation 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.
Release history Release notifications | RSS feed
Download the file for your platform. If you're not sure which to choose, learn more about installing packages.