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🤗 nlp: datasets and evaluation metrics for Natural Language Processing in NumPy, Pandas, PyTorch and TensorFlowUpdated -
Provides fractional delay filter design and evaluation routines for Numpy arrays
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ScaLAPACK for Python (scalapy) provides a high-level Python interface to distributed dense linear algebra using MPI, BLACS, and ScaLAPACK. It enables efficient computation on large matrices using a block-cyclic distribution, while exposing a NumPy-like API based on the DistributedMatrix abstraction.
This fork modernizes and stabilizes the original scalapy project with: • Support for Python 3.x on modern Linux systems • Clean MPI + ScaLAPACK detection (OpenMPI + Netlib ScaLAPACK) • Reproducible builds using a known-good NumPy / Cython / mpi4py stack • Documentation, examples, and automated tests • High-level wrappers for SVD, QR, LU, Cholesky, eigenproblems, and DMD workflows • Efficient distributed transposes via the new p?lapv2 wrapper
The project makes it possible to write dense parallel linear-algebra pipelines in Python while executing BLAS/PBLAS/ScaLAPACK kernels across an MPI communicator.
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Copy of NumPy open source project for testing purposes.
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Type annotations and runtime checking for shape and dtype of JAX/NumPy/PyTorch/etc. arrays. https://docs.kidger.site/jaxtyping/
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Good starting point for working on data science projects. Contains numpy, pandas, matplotlib, tensorflow and more.
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