fixed layer norm quantization annotation #3
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This looks good, should we file a PR on the main branch? |
I created the PR to fix it. |
cccclai
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Feb 25, 2025
) In preparation for replacing the checked-in files in shim/ with https://github.com/facebook/buck2-shims-meta as a submodule. The portions of this diff that are not a pure move are: creation of shim_et/BUCK symlink shim/tools to shim_et/tools so that fbsource//tools movement of Android toolchains from shim/BUCK to shim_et/BUCK because they are not present in buck2-shims-meta edits to .buckconfig edit to Utils.cmake to point at shim_et// instead of shim// edit to shim_et/README.md (note that shim/README.md will come back when shim/ is a submodule pointing to buck2-shims-meta)
cccclai
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May 29, 2025
Differential Revision: D75104487 Pull Request resolved: pytorch#11021
cccclai
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Jun 10, 2025
Differential Revision: D75718888 Pull Request resolved: pytorch#11444
cccclai
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Jun 13, 2025
Differential Revision: D76157744 Pull Request resolved: pytorch#11501
cccclai
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Aug 4, 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 pytorch#5: 0x000000019091821c libsystem_malloc.dylib`___BUG_IN_CLIENT_OF_LIBMALLOC_POINTER_BEING_FREED_WAS_NOT_ALLOCATED + 32 frame pytorch#6: 0x000000019d2f4084 libBNNS.dylib`___lldb_unnamed_symbol1620 + 564 frame pytorch#7: 0x000000019d2f5bac libBNNS.dylib`___lldb_unnamed_symbol1628 + 680 frame pytorch#8: 0x000000019d69ce48 libBNNS.dylib`BNNSCopy + 616 frame pytorch#9: 0x000000030c74d950 _portable_lib.cpython-310-darwin.so`(anonymous namespace)::copy_using_bnns(executorchcoreml::MultiArray const&, executorchcoreml::MultiArray&) + 188 frame pytorch#10: 0x000000030c74cfdc _portable_lib.cpython-310-darwin.so`(anonymous namespace)::copy(executorchcoreml::MultiArray const&, executorchcoreml::MultiArray&, executorchcoreml::MultiArray::CopyOptions) + 72 frame pytorch#11: 0x000000030c74ceec _portable_lib.cpython-310-darwin.so`executorchcoreml::MultiArray::copy(executorchcoreml::MultiArray&, executorchcoreml::MultiArray::CopyOptions) const + 148 frame pytorch#12: 0x000000030c7488d4 _portable_lib.cpython-310-darwin.so`invocation function for block in (anonymous namespace)::copy(MLMultiArray*, executorchcoreml::MultiArray&) + 376 frame pytorch#13: 0x000000030c748ac8 _portable_lib.cpython-310-darwin.so`invocation function for block in (anonymous namespace)::copy(MLMultiArray*, executorchcoreml::MultiArray&) + 52 frame pytorch#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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