Sparse tensors to decrease training time
I've learning about PyTorch sparse tensors : https://pytorch.org/docs/stable/sparse.html
From the docs (https://pytorch.org/docs/stable/sparse.html) : "Torch supports sparse tensors in COO(rdinate) format, which can efficiently store and process tensors for which the majority of elements are zeros."
Is one of the intended use of sparse tensors instead of regular PyTorch tensors to decrease training time ?
python machine-learning deep-learning pytorch
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
add a comment |
I've learning about PyTorch sparse tensors : https://pytorch.org/docs/stable/sparse.html
From the docs (https://pytorch.org/docs/stable/sparse.html) : "Torch supports sparse tensors in COO(rdinate) format, which can efficiently store and process tensors for which the majority of elements are zeros."
Is one of the intended use of sparse tensors instead of regular PyTorch tensors to decrease training time ?
python machine-learning deep-learning pytorch
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
add a comment |
I've learning about PyTorch sparse tensors : https://pytorch.org/docs/stable/sparse.html
From the docs (https://pytorch.org/docs/stable/sparse.html) : "Torch supports sparse tensors in COO(rdinate) format, which can efficiently store and process tensors for which the majority of elements are zeros."
Is one of the intended use of sparse tensors instead of regular PyTorch tensors to decrease training time ?
python machine-learning deep-learning pytorch
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
I've learning about PyTorch sparse tensors : https://pytorch.org/docs/stable/sparse.html
From the docs (https://pytorch.org/docs/stable/sparse.html) : "Torch supports sparse tensors in COO(rdinate) format, which can efficiently store and process tensors for which the majority of elements are zeros."
Is one of the intended use of sparse tensors instead of regular PyTorch tensors to decrease training time ?
python machine-learning deep-learning pytorch
python machine-learning deep-learning pytorch
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
asked Nov 24 '18 at 23:08
blue-skyblue-sky
17.5k84274504
17.5k84274504
add a comment |
add a comment |
1 Answer
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Yes but indirectly.
sparse tensors can reduce the complexity of computations and hence training/inference time. Complexity of matrix multiplication depends on number of elements in matrix whereas complexity of sparse matrix multiplication would depend on the number of non-zero elements which are less (due to sparsity)
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
add a comment |
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1 Answer
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1 Answer
1
active
oldest
votes
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oldest
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active
oldest
votes
Yes but indirectly.
sparse tensors can reduce the complexity of computations and hence training/inference time. Complexity of matrix multiplication depends on number of elements in matrix whereas complexity of sparse matrix multiplication would depend on the number of non-zero elements which are less (due to sparsity)
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
add a comment |
Yes but indirectly.
sparse tensors can reduce the complexity of computations and hence training/inference time. Complexity of matrix multiplication depends on number of elements in matrix whereas complexity of sparse matrix multiplication would depend on the number of non-zero elements which are less (due to sparsity)
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
add a comment |
Yes but indirectly.
sparse tensors can reduce the complexity of computations and hence training/inference time. Complexity of matrix multiplication depends on number of elements in matrix whereas complexity of sparse matrix multiplication would depend on the number of non-zero elements which are less (due to sparsity)
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
Yes but indirectly.
sparse tensors can reduce the complexity of computations and hence training/inference time. Complexity of matrix multiplication depends on number of elements in matrix whereas complexity of sparse matrix multiplication would depend on the number of non-zero elements which are less (due to sparsity)
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
answered Nov 25 '18 at 6:27
Umang GuptaUmang Gupta
3,17511535
3,17511535
add a comment |
add a comment |
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