Add CI scripts to run supported executorch networks through MPS#1
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DenisVieriu97 merged 3 commits intomainfrom Nov 15, 2023
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Add CI scripts to run supported executorch networks through MPS#1DenisVieriu97 merged 3 commits intomainfrom
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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* Fix mps_executor_runner build when using cmake * Add CI scripts to run supported executorch networks through MPS (#1) * Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2 * Don't specialize the executable for the current device (#3) Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com> * Update CI script to run test_mps (#4) * Update CI script to run test_mps * Update cmdline * Add lint for mps * Update lint script * Update lint script * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Add support for conv1D (fixes w2l) * Perf imprv - Map conv2D to depthwiseConv3D * Add support for PyTorch style printing of output tensors * Fix lint * Remove unused headers * Remove unused headers #2 --------- Co-authored-by: Grzegorz George Pawelczak <grzpawelczak@gmail.com>
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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* Fix mps_executor_runner build when using cmake * Add CI scripts to run supported executorch networks through MPS (#1) * Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2 * Don't specialize the executable for the current device (#3) Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com> * Update CI script to run test_mps (#4) * Update CI script to run test_mps * Update cmdline * Add lint for mps * Update lint script * Update lint script * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Add support for conv1D (fixes w2l) * Perf imprv - Map conv2D to depthwiseConv3D * Add support for PyTorch style printing of output tensors * Fix lint * Remove unused headers * Remove unused headers #2 --------- Co-authored-by: Grzegorz George Pawelczak <grzpawelczak@gmail.com>
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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* Fix mps_executor_runner build when using cmake * Add CI scripts to run supported executorch networks through MPS (#1) * Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2 * Don't specialize the executable for the current device (#3) Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com> * Update CI script to run test_mps (#4) * Update CI script to run test_mps * Update cmdline * Add lint for mps * Update lint script * Update lint script * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Add support for conv1D (fixes w2l) * Perf imprv - Map conv2D to depthwiseConv3D * Add support for PyTorch style printing of output tensors * Fix lint * Remove unused headers * Remove unused headers #2 --------- Co-authored-by: Grzegorz George Pawelczak <grzpawelczak@gmail.com>
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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* Fix mps_executor_runner build when using cmake * Add CI scripts to run supported executorch networks through MPS (#1) * Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2 * Don't specialize the executable for the current device (#3) Co-authored-by: Denis Vieriu <104024078+DenisVieriu97@users.noreply.github.com> * Update CI script to run test_mps (#4) * Update CI script to run test_mps * Update cmdline * Add lint for mps * Update lint script * Update lint script * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Fix lint * Add support for conv1D (fixes w2l) * Perf imprv - Map conv2D to depthwiseConv3D * Add support for PyTorch style printing of output tensors * Fix lint * Remove unused headers * Remove unused headers #2 --------- Co-authored-by: Grzegorz George Pawelczak <grzpawelczak@gmail.com>
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* Add CI scripts to run supported executorch networks through MPS * Fix CI * Fix CI #2
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Summary: bypass-github-export-checks Pull Request resolved: pytorch#2348 Before: Each node contains a `UniformParamsBuffer`. After: Each node contains a `std::vector<std::shared_ptr<UniformParamsBuffer>>`. In follow up changes, we will break up parameters to be passed via multiple UniformParamsBuffer, since 1. some are tensor-specific (e.g. image extents) and 2. others are operator-specific (e.g. alpha for binary ops). Hence, we need **`std::vector`**. We are adding the methods for #1 in pytorch#2340. Since #1 and #2 will be owned by different objects, we need **pointers**. Since #1 is owned by `vTensor` which is non-copyable, we can't use unique_ptr so we need **`std::shared_ptr`**. ghstack-source-id: 218195447 exported-using-ghexport Reviewed By: SS-JIA Differential Revision: D54691831 fbshipit-source-id: 84ab9f777e247fd56234290ed7f7343b9701c73f
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Summary: bypass-github-export-checks Pull Request resolved: pytorch#2404 In pytorch#2271, we already added - IntList - DoubleList - BoolList - ValueList to the schema and the runtime's Value class. Their serialization was incomplete missing two components: 1. Receiving a list in `torch.fx.Node.args`. 2. Receiving a non-tensor in `torch.fx.Node`. This change completes #1. Also, this change fixes a bug where values type `bool` matches both types `bool` and `int` and hence were being added twice. If our type support grows more complex, we can consider using our own types similar to the core Executorch runtime: https://github.com/pytorch/executorch/blob/689796499024fc4a133318d707f4c10db73da967/exir/emit/_emitter.py#L158-L166 ghstack-source-id: 218539049 exported-using-ghexport Reviewed By: SS-JIA Differential Revision: D54708353 fbshipit-source-id: 8641647b515e201ea63db67115c01c1532ad6566
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Summary: Pull Request resolved: pytorch#3763 Reviewed By: itamaro, tarun292 Differential Revision: D51566750 fbshipit-source-id: 654c426d479833867e93083e9b55786abfc24a32
manuelcandales
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Aug 27, 2025
BNNS copy crashes the process when the dtypes differ (pytorch#11714). With the example in this PR (pytorch#11714), we crash the process on main. Here is the stack trace from LLDB: ``` Process 19234 stopped * thread #1, queue = 'com.apple.main-thread', stop reason = signal SIGABRT frame #0: 0x0000000190ac9388 libsystem_kernel.dylib`__pthread_kill + 8 libsystem_kernel.dylib`__pthread_kill: -> 0x190ac9388 <+8>: b.lo 0x190ac93a8 ; <+40> 0x190ac938c <+12>: pacibsp 0x190ac9390 <+16>: stp x29, x30, [sp, #-0x10]! 0x190ac9394 <+20>: mov x29, sp (lldb) bt * thread #1, queue = 'com.apple.main-thread', stop reason = signal SIGABRT * frame #0: 0x0000000190ac9388 libsystem_kernel.dylib`__pthread_kill + 8 frame #1: 0x0000000190b0288c libsystem_pthread.dylib`pthread_kill + 296 frame #2: 0x0000000190a0bc60 libsystem_c.dylib`abort + 124 frame #3: 0x0000000190910174 libsystem_malloc.dylib`malloc_vreport + 892 frame #4: 0x0000000190913c90 libsystem_malloc.dylib`malloc_report + 64 frame #5: 0x000000019091821c libsystem_malloc.dylib`___BUG_IN_CLIENT_OF_LIBMALLOC_POINTER_BEING_FREED_WAS_NOT_ALLOCATED + 32 frame #6: 0x000000019d2f4084 libBNNS.dylib`___lldb_unnamed_symbol1620 + 564 frame #7: 0x000000019d2f5bac libBNNS.dylib`___lldb_unnamed_symbol1628 + 680 frame #8: 0x000000019d69ce48 libBNNS.dylib`BNNSCopy + 616 frame #9: 0x000000030c74d950 _portable_lib.cpython-310-darwin.so`(anonymous namespace)::copy_using_bnns(executorchcoreml::MultiArray const&, executorchcoreml::MultiArray&) + 188 frame #10: 0x000000030c74cfdc _portable_lib.cpython-310-darwin.so`(anonymous namespace)::copy(executorchcoreml::MultiArray const&, executorchcoreml::MultiArray&, executorchcoreml::MultiArray::CopyOptions) + 72 frame #11: 0x000000030c74ceec _portable_lib.cpython-310-darwin.so`executorchcoreml::MultiArray::copy(executorchcoreml::MultiArray&, executorchcoreml::MultiArray::CopyOptions) const + 148 frame #12: 0x000000030c7488d4 _portable_lib.cpython-310-darwin.so`invocation function for block in (anonymous namespace)::copy(MLMultiArray*, executorchcoreml::MultiArray&) + 376 frame #13: 0x000000030c748ac8 _portable_lib.cpython-310-darwin.so`invocation function for block in (anonymous namespace)::copy(MLMultiArray*, executorchcoreml::MultiArray&) + 52 frame #14: 0x000000019ad33f4c CoreML`CoreML::MultiArrayBuffer::getBytesWithHandler(void (void const*, unsigned long) block_pointer) const + 340 frame pytorch#15: 0x000000019ad34138 CoreML`-[MLMultiArray(ScopedBufferAccess) getBytesWithHandler:] + 152 frame pytorch#16: 0x000000030c7485ec _portable_lib.cpython-310-darwin.so`(anonymous namespace)::copy(MLMultiArray*, executorchcoreml::MultiArray&) + 296 frame pytorch#17: 0x000000030c744f68 _portable_lib.cpython-310-darwin.so`(anonymous namespace)::set_outputs(std::__1::vector<executorchcoreml::MultiArray, std::__1::allocator<executorchcoreml::MultiArray>>&, NSArray<MLMultiArray*>*) + 180 ``` With this PR, the process succeeds.
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