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pytorch/benchmarks/sparse
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Aaron Gokaslan 8fce9a09cd [BE]: pyupgrade Python to 3.8 - imports and object inheritance only (#94308) 
Apply parts of pyupgrade to torch (starting with the safest changes).
This PR only does two things: removes the need to inherit from object and removes unused future imports.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/94308
Approved by: https://github.com/ezyang, https://github.com/albanD
2023-02-07 21:10:56 +00:00
..
dlmc
__init__.py Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
README.md Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
spmm.py Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
spmv.py Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
test_csr.sh Add CSR (compressed sparse row) layout for sparse tensors (#50937) 2021-04-12 10:09:12 -07:00
utils.py [BE]: pyupgrade Python to 3.8 - imports and object inheritance only (#94308) 2023-02-07 21:10:56 +00:00

README.md

#Sparse benchmarks

These sets of benchmarks are for the sparse matrix functionality. They exist for comparing the performance of sparse matrix routines such as SpMV between various sparse matrix formats and with other frameworks such as TensorFlow.