cuda export supported #14478
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cuda export supported #14478
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Gasoonjia
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/14478
Note: Links to docs will display an error until the docs builds have been completed. ❌ 7 New Failures, 5 Pending, 1 Unrelated FailureAs of commit 3779980 with merge base b3f3111 ( NEW FAILURES - The following jobs have failed:
BROKEN TRUNK - The following job failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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| return PreprocessResult( | ||
| processed_bytes=b"", | ||
| debug_handle_map={}, | ||
| data_store_output=named_data_store.get_named_data_store_output(), |
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Why are you putting this in the named_data_store since the .so is not actually shareable? Just legacy from when we were going to share with nativeRT?
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we just want to make sure in et we are using the correct pipeline.
in the future we need to find the way to load .so directly from ptd file which benefits both et loading efficiency and other partners like nativeRT.
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
Gasoonjia
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
Gasoonjia
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Sep 25, 2025
Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Reviewed By: angelayi, larryliu0820 Differential Revision: D82987410
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Summary: Pull Request resolved: pytorch#14478 this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Differential Revision: D82987410 Reviewed By: angelayi, larryliu0820
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Summary: Pull Request resolved: pytorch#14478 this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Differential Revision: D82987410 Reviewed By: angelayi, larryliu0820
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Summary: Pull Request resolved: pytorch#14478 this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime. Differential Revision: D82987410 Reviewed By: angelayi, larryliu0820
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Summary: this diff introuce the cuda backend that compiles the partitioned model graph to run on CUDA devices. It uses the AOTInductor compiler to generate optimized CUDA kernels for the model's operators with libtorch-free. The compiled model can be executed on CUDA devices using the Executorch runtime.
Differential Revision: D82987410