Add variable seqlen and sparsity parameters to jagged_sum benchmark #2324
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This pull request was exported from Phabricator. Differential Revision: D58772201 |
Summary:
Modify existing `jagged_sum` operator benchmark to optionally accept any of the following parameters: `B` (dimension 0 of nested tensor), `M` (dimension 2 of nested tensor), `seqlen` (maximum sequence length on ragged dimension), or `sparsity` (average sparsity on ragged dimension). This diff fixes the provided command line parameters and varies all other parameters above, enabling testing of all combinations of multiple parameters in parallel.
The following errors persist with sufficiently large inputs:
- `RuntimeError: numel needs to be smaller than int32_t max; otherwise, please use packed_accessor64` (when running command `buck2 run mode/{opt,inplace} //pytorch/benchmark:triton -- --op jagged_sum --B 1024 --M 1024 --sparsity 0.3`)
- `torch.OutOfMemoryError: CUDA out of memory.`
Reviewed By: davidberard98
Differential Revision: D58772201
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This pull request was exported from Phabricator. Differential Revision: D58772201 |
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This pull request has been merged in 1425f68. |
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Summary:
Modify existing
jagged_sumoperator benchmark to optionally accept any of the following parameters:B(dimension 0 of nested tensor),M(dimension 2 of nested tensor),seqlen(maximum sequence length on ragged dimension), orsparsity(average sparsity on ragged dimension). This diff fixes the provided command line parameters and varies all other parameters above, enabling testing of all combinations of multiple parameters in parallel.The following errors persist with sufficiently large inputs:
RuntimeError: numel needs to be smaller than int32_t max; otherwise, please use packed_accessor64(when running commandbuck2 run @mode/{opt,inplace} //pytorch/benchmark:triton -- --op jagged_sum --B 1024 --M 1024 --sparsity 0.3)torch.OutOfMemoryError: CUDA out of memory.Reviewed By: davidberard98
Differential Revision: D58772201