Parents (Total: 11)

The searched file hash is included in 11 parent files which include package known and seen by metalookup. A sample is included below:

Key	Value
MD5	DB2888E8C6102C33F72D02542E94F6BB
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp152.3.3
PackageVersion	3.3.0
SHA-1	968E2D1B6E6047FA92E783961230B8D0799B601E
SHA-256	621DAC40686185DAE07412943BEBE5F395FE7128E7B79121122E24EDDC5EED05

Key	Value
MD5	AAB54F380CD5EE8F2EA26C39526CA733
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	3.3
PackageVersion	3.3.0
SHA-1	3CD839CA4110BE1E4B97B02F439E5B6922444BD0
SHA-256	6DA87A1CEE32EA705D8A9832CDD29DFF4222909FA72A4661F97C00982236160B

Key	Value
MD5	4C06D0EC1423F12A83653C6960700939
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	3.3
PackageVersion	3.3.0
SHA-1	69A09408C1EE3D5AF8D329AE4D65DB1902B63BA8
SHA-256	EA5D616940AA453509F7B0DB7D244703D4BB20812B074873720D8E53D687B1ED

Key	Value
MD5	5A94FE8B8A58AA5AA894518F16E457B2
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp154.3.1
PackageVersion	3.3.0
SHA-1	5CB0A2666B896EBEB64EC806CEE033B2749D09F9
SHA-256	F691F4CAE6C347ED867286734660D221F5407DB9A54CF7C117CFFF0C30CB4135

Key	Value
MD5	3CF6F5A7E4C84F7E1523560A061CE5FE
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp153.3.1
PackageVersion	3.3.0
SHA-1	8D77D3B072A863D432264E649AAEC9D7ABBD8559
SHA-256	E1C3AADD19CFBF7CA57722DAD66B42E1DF9A41AABF3E0D5E83A758510F6077CC

Key	Value
MD5	02AC521107A8229E897DC25B0C94C4F0
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp153.3.4
PackageVersion	3.3.0
SHA-1	00DA61D719889443ABF8567D6D4B874EFEA65930
SHA-256	2022490622682BB0726245282C6EF96F4071D6259766D6C7FE0BC5F1ECD237AA

Key	Value
MD5	C5AC5542AEF1749FCE5D1DEB97E3BF25
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp152.3.3
PackageVersion	3.3.0
SHA-1	255228479BF3B8285E848FB28A8CF97BF9FBD6F1
SHA-256	1048CE221CFA61EF786ECD05D9DB0C35A152DBF1166D63194588C8930CD08D0D

Key	Value
MD5	81E6E3B4844B4CA7ECCD6A14126B5257
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	3.3
PackageVersion	3.3.0
SHA-1	8CB7BFE40737544DF10EED03F8B5A25E34DC1D20
SHA-256	700BA131AE3E6B6FF81A3C32FB6DE94831394CF6984B9895CD45092E1A5D42C8

Key	Value
MD5	A2ECAA4EDC83C6DA7E451A053EC0026F
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	lp151.2.1
PackageVersion	3.3.0
SHA-1	B0B2BB5C7B6F1235E91D8ACD115B255877810A40
SHA-256	53B17B02DFCED7F50BF3C15CFA68C09B3E8040F7927B5603CFDA41AA8AF6EB47

Key	Value
MD5	70F635437F076188EDD995A9E481C7AA
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	3.3
PackageVersion	3.3.0
SHA-1	1348D56D21BDB7D8815E546AAB0964FD4533554B
SHA-256	93AFA0A2D2B6A81872552D03ABA6CE886B035A585B3473694A13C0DF66BC997C

Key	Value
MD5	740DF4D5099B8ADCB5769502784A2CEC
PackageArch	noarch
PackageDescription	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**](http://optimized-einsum.readthedocs.io) for more information.
PackageName	python3-opt-einsum
PackageRelease	3.4
PackageVersion	3.3.0
SHA-1	CA5E47039609036C7A6A0A5CB91D83C33D6F6B77
SHA-256	4F50ED0364042BEC2013A85D850BB0C3DBC3E55645ED24DC250E65DCF7E032F1