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Add xnnpack to llama runner mac & linux CI job #2677
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🔗 Helpful Links🧪 See artifacts and rendered test results at hud.pytorch.org/pr/pytorch/executorch/2677
Note: Links to docs will display an error until the docs builds have been completed. ❌ 1 New Failure, 2 Unrelated FailuresAs of commit 0b1e68c with merge base 08b644f ( NEW FAILURE - The following job has failed:
BROKEN TRUNK - The following jobs failed but were present on the merge base:👉 Rebase onto the `viable/strict` branch to avoid these failures
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@@ -90,6 +90,7 @@ jobs: | |||
matrix: | |||
dtype: [fp32] | |||
build-tool: [buck2, cmake] | |||
mode: [portable, xnnpack] |
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can we select quant mode rather than portable/xnnpack? Right now this is choosing xnnpack but its actually quantizing the model. Instead I think we should have quant mode be what's selected, and XNNPACK will be the quantized backend which runs it.
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Let's update in follow on, as we also want the pt2e quant path.
$<TARGET_FILE:optimized_native_cpu_ops_lib> \ | ||
LINKER:--no-whole-archive") | ||
list(APPEND link_libraries optimized_native_cpu_ops_lib optimized_kernels | ||
portable_kernels) |
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portable kernels is linked regardless of optimized? Can we move this outside of the if?
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Hmn, optimized_native_cpu_ops_lib
contains portable and optimized kernel registrations. If we don't have an optimized version of an op that's used by the model, we take the portable one.
"SHELL:LINKER:--whole-archive \ | ||
$<TARGET_FILE:portable_ops_lib> \ | ||
LINKER:--no-whole-archive") | ||
target_link_options_shared_lib(portable_ops_lib) | ||
endif() | ||
|
||
target_link_libraries(llama_main PUBLIC gflags llama_runner) |
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can we add executorch here as well? This lib dep contains prim ops which need to be registered via target_link_options_shared_lib
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thanks - good catch
Summary: Remake of D55290786, which is ghstack poisoned Reviewed By: kimishpatel, digantdesai Differential Revision: D55349949
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This pull request was exported from Phabricator. Differential Revision: D55349949 |
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Summary: Remake of D55290786, which is ghstack poisoned Reviewed By: kimishpatel, digantdesai Differential Revision: D55349949
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This pull request was exported from Phabricator. Differential Revision: D55349949 |
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Summary: Remake of D55290786, which is ghstack poisoned bypass-github-export-checks Reviewed By: kimishpatel, digantdesai Differential Revision: D55349949
Summary: Remake of D55290786, which is ghstack poisoned bypass-github-export-checks Reviewed By: kimishpatel, digantdesai Differential Revision: D55349949
This pull request has been merged in 66c5fc8. |
Summary: Remake of D55290786, which is ghstack poisoned
Differential Revision: D55349949