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pytorch/benchmarks/sparse
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Pearu Peterson cf6041e942 Use weakref in storing tensors as keys (follow-up to #111470) (#112076) 
This PR addresses the discussion items in https://github.com/pytorch/pytorch/pull/111470#discussion_r1369008167, that is,
- use weakref when storing tensors as keys,
- add `storage_offset` to the key data,
- and revise the description of the `TensorAsKey` utility.

Pull Request resolved: https://github.com/pytorch/pytorch/pull/112076
Approved by: https://github.com/cpuhrsch
ghstack dependencies: #112154
2023-10-30 19:16:05 +00:00
..
dlmc Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
__init__.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
benchmark_semi_structured_sparsity.py [sparse] Add padding for dense matrices in semi-structured sparse (#110583) 2023-10-13 20:04:23 +00:00
README.md
spmm.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
spmv.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +00:00
test_csr.sh [BE] Prefer dash over underscore in command-line options (#94505) 2023-02-09 20:16:49 +00:00
triton_ops.py Use weakref in storing tensors as keys (follow-up to #111470) (#112076) 2023-10-30 19:16:05 +00:00
utils.py Apply UFMT to all files in benchmarks/ (#105928) 2023-07-26 01:18:48 +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.