Add jagged_sum operator for unpadded nested tensors to TritonBench #2299
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Summary: Add a `jagged_sum` reduction operator for unpadded nested tensors, based on the PyTorch `sum` operator, to TritonBench. This diff implements a basic benchmark for reducing along the ragged dimension for 3-dimensional nested tensors. For a 3-dimensional tensor of shape `(B, *, M)`, where `*` is the ragged dimension, this benchmark uses PyTorch's `sum` operator to reduce `B` `(*, M)` 2-dimensional tensors to a `(B, M)` output tensor. Measure performance of basic benchmark with `gbps` and `latency` metrics and display nested tensor parameters `B` and `M`. Reviewed By: YuqingJ Differential Revision: D58396957
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This pull request was exported from Phabricator. Differential Revision: D58396957 |
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jananisriram
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This pull request has been merged in 576b2b2. |
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Summary:
Add a
jagged_sumreduction operator for unpadded nested tensors, based on the PyTorchsumoperator, to TritonBench. This diff implements a basic benchmark for reducing along the ragged dimension for 3-dimensional nested tensors. For a 3-dimensional tensor of shape(B, *, M), where*is the ragged dimension, this benchmark uses PyTorch'ssumoperator to reduceB(*, M)2-dimensional tensors to a(B, M)output tensor.Measure performance of basic benchmark with
gbpsandlatencymetrics and display nested tensor parametersBandM.Reviewed By: YuqingJ
Differential Revision: D58396957