python-opt-einsum

Optimizing numpys einsum function

Optimized einsum can significantly reduce the overall execution time of einsum-like expressions (e.g., `np.einsum`,`dask.array.einsum`,`pytorch.einsum`,`tensorflow.einsum`) by optimizing the expression's contraction order and dispatching many operations to canonical BLAS, cuBLAS, or other specialized routines. Optimized einsum is agnostic to the backend and can handle NumPy, Dask, PyTorch, Tensorflow, CuPy, Sparse, Theano, JAX, and Autograd arrays as well as potentially any library which conforms to a standard API. See the [**documentation**](<a href="http://optimized-einsum.readthedocs.io">http://optimized-einsum.readthedocs.io</a> ) for more information.

openSUSE Leap 16.0 हेतु कोई आधिकारिक पैकेज उपलब्ध नहीं है

वितरण

openSUSE Tumbleweed

devel:languages:python:backports अल्पविकसित
3.3.0
science:machinelearning अल्पविकसित
3.3.0

openSUSE Leap 16.0

devel:languages:python:backports अल्पविकसित
3.3.0
science:machinelearning अल्पविकसित
3.3.0

openSUSE Leap 15.6

devel:languages:python:backports अल्पविकसित
3.3.0
science:machinelearning अल्पविकसित
3.3.0

openSUSE Leap 15.5

devel:languages:python:backports अल्पविकसित
3.3.0
science:machinelearning अल्पविकसित
3.3.0

openSUSE Factory RISCV

science:machinelearning अल्पविकसित
3.3.0

SLFO 1.2

openSUSE Backports for SLE 15 SP7

devel:languages:python:backports अल्पविकसित
3.3.0
science:machinelearning अल्पविकसित
3.3.0

openSUSE Backports for SLE 15 SP4

devel:languages:python:backports अल्पविकसित
3.3.0

असमर्थित वितरण

निम्नलिखित वितरण आधिकारिक रूप से समर्थित नहीं हैं। इन पैकेज के उपयोग/प्रभाव का उत्तरदायित्व आप पर है।