Result for 02804724FA472A048C2CAC0EF05D0CF408092499

Query result

Key Value
FileName./usr/lib/python3.6/site-packages/opt_einsum/__pycache__/blas.cpython-36.pyc
FileSize4833
MD571EF1FF44503C80E34442B1F78F13BD3
SHA-102804724FA472A048C2CAC0EF05D0CF408092499
SHA-256E6FE98BAA8A243FFF9FCE6EB2A8EDAEBFBA8DEFD0B22CBA41AE729828E8E98C6
SSDEEP96:s1+wJQmqd5/VJZ/P8rWkrBGlq366NkMh51Jpu2/jqQDuViKYt2r4rOWrD2qY7YcT:ZwJNqDJxEvGG3h1227D4hYcEPD2Kcz3
TLSHT147A1A4C1BDC87738D1A3D2F2E2CE0227CA11A66F23164411B0ADD0656F769B1237EA8C
hashlookup:parent-total3
hashlookup:trust65

Network graph view

Parents (Total: 3)

The searched file hash is included in 3 parent files which include package known and seen by metalookup. A sample is included below:

Key Value
MD530382EA6D23E491CABFA137DCC614248
PackageArchnoarch
PackageDescriptionOptimized 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**](http://optimized-einsum.readthedocs.io) for more information.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-opt-einsum
PackageReleasebp154.1.30
PackageVersion3.1.0
SHA-1F11107B7B8DDCF52997FD1E19E5CA3E5E283C2D8
SHA-256C2B0456597FCFF34FC69BF9AACE209201A6465C80827F18BBD324FBE13829E85
Key Value
MD59F574855320F1F4A3D50C36BEE820112
PackageArchnoarch
PackageDescriptionOptimized 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**](http://optimized-einsum.readthedocs.io) for more information.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-opt-einsum
PackageReleasebp155.2.12
PackageVersion3.1.0
SHA-17E0F1B26A59F60BE3965A196F4563E54D4D22429
SHA-2563BAFE13C483B8175BBB7717D24B3F64AA1AE10ED4F76BD4E8E6A9269B6D0F997
Key Value
MD5AD770C20739AF27B97EAF5A2E21535E7
PackageArchnoarch
PackageDescriptionOptimized 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**](http://optimized-einsum.readthedocs.io) for more information.
PackageMaintainerhttps://bugs.opensuse.org
PackageNamepython3-opt-einsum
PackageReleasebp156.3.1
PackageVersion3.1.0
SHA-143ACB56E4B3F308B70E5183F3F3C2AA80BD8A580
SHA-256B634C108E1FE48D0B8D3EF0353476A80DB8CBC0DFA12F8F315B04B16FC8D6038