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This PR is to show some init time related log at runtime.

  1. This is all init time on the QnnBackend.
    [Time consuming during init in QnnBackend] Init Time: 219 milliseconds
  2. It is generated from qnn profiling.
    QNN (load binary) time includes RPC (load binary) time.
    RPC (load binary) time includes QNN accelerator (load binary) time.
    QNN accelerator (load binary) time includes Accelerator (load binary) time.
[INFO] [Qnn ExecuTorch]: Type: 1002, Init Event Name: RPC (load binary) time, Event Data: 16303 us
[INFO] [Qnn ExecuTorch]: Type: 1003, Init Event Name: QNN accelerator (load binary) time, Event Data: 15899 us
[INFO] [Qnn ExecuTorch]: Type: 1004, Init Event Name: Accelerator (load binary) time, Event Data: 15709 us
[INFO] [Qnn ExecuTorch]: Type: 100, Init Event Name: QNN (load binary) time, Event Data: 53819 us

image
(refer to qnn docs)
3. This is overall loading time in main.cpp

I 00:00:00.386326 executorch:main.cpp:358] [Time consuming during load() function] init took 383 ms

@shewu-quic shewu-quic marked this pull request as draft October 7, 2024 09:33
cccclai pushed a commit that referenced this pull request 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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