mirror of
https://github.com/zebrajr/pytorch.git
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5fb1142702
Summary: Implement compressed sparse row format. Derived from the GCS implementation at https://github.com/pytorch/pytorch/pull/44190 Pull Request resolved: https://github.com/pytorch/pytorch/pull/50937 Reviewed By: mrshenli Differential Revision: D27439865 Pulled By: ezyang fbshipit-source-id: 3ba3dcb9679505b980ff6a5f513e913bbae2fb1d
42 lines
1.1 KiB
Bash
42 lines
1.1 KiB
Bash
OUTFILE=spmm-no-mkl-test.txt
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PYTORCH_HOME=$1
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cd $PYTORCH_HOME
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echo "" >> $OUTFILE
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echo "----- USE_MKL=1 -----" >> $OUTFILE
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rm -rf build
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export USE_MKL=1
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export CMAKE_PREFIX_PATH=${CONDA_PREFIX:-"$(dirname $(which conda))/../"}
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python setup.py build --cmake-only
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ccmake build # or cmake-gui build
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python setup.py install
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cd benchmarks
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echo "!! SPARSE SPMM TIME BENCHMARK!! " >> $OUTFILE
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for dim0 in 1000 5000 10000; do
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for nnzr in 0.01 0.05 0.1 0.3; do
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python -m sparse.spmm --format csr --m $dim0 --n $dim0 --k $dim0 --nnz_ratio $nnzr --outfile $OUTFILE
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# python -m sparse.spmm --format coo --m $dim0 --n $dim0 --k $dim0 --nnz_ratio $nnzr --outfile $OUTFILE
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done
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done
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echo "----------------------" >> $OUTFILE
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cd $PYTORCH_HOME
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echo "----- USE_MKL=0 ------" >> $OUTFILE
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rm -rf build
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export USE_MKL=0
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python setup.py install
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cd benchmarks
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for dim0 in 1000 5000 10000; do
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for nnzr in 0.01 0.05 0.1 0.3; do
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python -m sparse.spmv --format csr --m $dim0 --nnz_ratio $nnzr --outfile $OUTFILE
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python -m sparse.spmv --format coo --m $dim0 --nnz_ratio $nnzr --outfile $OUTFILE
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done
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done
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echo "----------------------" >> $OUTFILE
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