cpp_wrapper: Use runtime dispatched fallbacks for complex ops #143223
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This was referenced Dec 13, 2024
🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/143223
Note: Links to docs will display an error until the docs builds have been completed. ✅ No FailuresAs of commit 218a34c with merge base bb5e439 ( This comment was automatically generated by Dr. CI and updates every 15 minutes. |
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When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic. ghstack-source-id: 60ab533 Pull Request resolved: #143223
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When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic. ghstack-source-id: 4d2e7ef Pull Request resolved: #143223
benjaminglass1
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Dec 14, 2024
When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic. ghstack-source-id: 46b9be7 Pull Request resolved: #143223
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When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic. ghstack-source-id: d8ff9b1 Pull Request resolved: #143223
This was referenced Dec 17, 2024
fightingand
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When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic. ghstack-source-id: 409133d Pull Request resolved: pytorch/pytorch#143223
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This was referenced Jan 3, 2025
pytorchmergebot
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Jan 3, 2025
Removes 4 fallback ops that are currently not possible to codegen, which does not break ABI-compatibility. 1. `_cudnn_rnn_backward` and `_histogramdd_bin_edges` both return `Tensor[]`, which we cannot codegen with the current design. 2. `_sparse_coo_tensor_with_dims_and_tensors` only supplies a Sparse operator, which we don't support. 3. `zeros.names` requires a `Dimname` input, which we can't currently codegen. Removing these ops from the list will improve test performance, since the fallback op generation will use the Python proxy executor instead of calling non-existent C functions. Pull Request resolved: #143421 Approved by: https://github.com/desertfire ghstack dependencies: #141371, #143223
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Since #143223 enabled runtime dispatch for fft_c2c in AOTI mod, for XPU, we can fallback fft_c2c which has no XPU implementation to CPU and pass the case now. Pull Request resolved: #144238 Approved by: https://github.com/jansel
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Stack from ghstack (oldest at bottom):
When calling a fallback op in cpp_wrapper mode, where any of the inputs are complex numbers, utilize the runtime dispatched fallback mode. This properly handles the Conjugate and Negative dispatch keys, if present, in exchange for a performance pessimization in complex arithmetic.
This PR additionally fixes some cascading failure modes exposed in our
aot_inductortests by this change.cc @voznesenskym @penguinwu @EikanWang @jgong5 @Guobing-Chen @XiaobingSuper @zhuhaozhe @blzheng @wenzhe-nrv @jiayisunx @ipiszy @yf225 @chenyang78 @kadeng @muchulee8 @ColinPeppler @amjames @desertfire @chauhang @aakhundov