Is the QNN backend support the model of Llama 3.2 3B instead of XNNPACK？

[tombang]

🐛 Describe the bug

I have run the XNNPACK tutorial and the pte file can run normally. but when I run the tutorial of Llama 3 8B and change the model to Llama 3.2 3B, the model load fail on the Android device of Qualcomm 8Gen 2， the fail code is 1.

QNN:2.26
SDK:r27b

Versions

QNN:2.26
SDK:r27b

cc @cccclai @winskuo-quic @shewu-quic @cbilgin

[kimishpatel]

Few follow ups

1. Issue summary does not say if you are runnign using qnn workflow. can you iupdate with details?
2. Please add your repro

[tombang]

I followed this tutorial （https://github.com/pytorch/executorch/blob/release/0.5/examples/demo-apps/android/LlamaDemo/docs/delegates/qualcomm_README.md） exactly, except that I replaced the model from Llama3 8B to Llama 3.2 3B during execution. The export command I used is as follows:

python -m examples.models.llama.export_llama --checkpoint "${MODEL_DIR}/consolidated.00.pth" -p "${MODEL_DIR}/params.json" -kv --disable_dynamic_shape --qnn --pt2e_quantize qnn_8a8w -d fp32 --num_sharding 4 --metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}' --output_name="test.pte" --soc_model SM8550

This command successfully exports the model, but when running the APK on Android, a model loading error occurs with error code -1.

[kimishpatel]

Ok lets follow up on this.

[cccclai]

Can you try qnn version 2.28?

[tombang]

Hi,

I change the QNN to 2.28, there is an error occured:

[INFO] [Qnn ExecuTorch]: Destroy Qnn backend parameters
[INFO] [Qnn ExecuTorch]: Destroy Qnn context
[INFO] [Qnn ExecuTorch]: Destroy Qnn device
[INFO] [Qnn ExecuTorch]: Destroy Qnn backend
[INFO] [Qnn ExecuTorch]: create QNN Logger with log_level 2
[INFO] [Qnn ExecuTorch]: Initialize Qnn backend parameters for Qnn executorch backend type 2
[INFO] [Qnn ExecuTorch]: Caching: Caching is in RESTORE MODE.
[WARNING] [Qnn ExecuTorch]: Unknown QNN BinaryInfo version 3.
[ERROR] [Qnn ExecuTorch]: Failed to retrieve backend binary info from QNN context binary.
[ERROR] [Qnn ExecuTorch]: Failed to parse QNN Graph Info. The cache might be broken. Please consider to re-generate the cache.
[WARNING] [Qnn ExecuTorch]: QnnDsp Performance Estimates unsupported

[WARNING] [Qnn ExecuTorch]: QnnDsp Arch 68 set by custom config is different from arch associated with SoC 43, will overwrite it to 73

[ERROR] [Qnn ExecuTorch]: QNN context cache is invalid.
Traceback (most recent call last):
File "/usr/lib/python3.10/runpy.py", line 196, in _run_module_as_main
return _run_code(code, main_globals, None,
File "/usr/lib/python3.10/runpy.py", line 86, in _run_code
exec(code, run_globals)
File "/mnt/data/tmp/executorch/examples/models/llama/export_llama.py", line 32, in
main() # pragma: no cover
File "/mnt/data/tmp/executorch/examples/models/llama/export_llama.py", line 28, in main
export_llama(args)
File "/mnt/data/tmp/executorch/examples/models/llama/export_llama_lib.py", line 522, in export_llama
builder = _export_llama(args)
File "/mnt/data/tmp/executorch/examples/models/llama/export_llama_lib.py", line 801, in _export_llama
canonicalize_program(builder.edge_manager.exported_program())
File "/mnt/data/tmp/executorch/backends/qualcomm/utils/utils.py", line 281, in canonicalize_program
update_spill_fill_size(obj)
File "/mnt/data/tmp/executorch/backends/qualcomm/utils/utils.py", line 278, in update_spill_fill_size
update_program(*get_program_info(exported_program))
File "/mnt/data/tmp/executorch/backends/qualcomm/utils/utils.py", line 256, in get_program_info
return dispatchtype(program)
File "/mnt/data/tmp/executorch/backends/qualcomm/utils/utils.py", line 233, in process_exported_program
assert qnn_mgr.Init().value == 0, "failed to load context binary"
AssertionError: failed to load context binary
[INFO] [Qnn ExecuTorch]: Destroy Qnn device
[INFO] [Qnn ExecuTorch]: Destroy Qnn backend

The command of export is below:

python -m examples.models.llama.export_llama
-c "/home/ai/tb/LLM-Research/Llama-3___2-3B/original/consolidated.00.pth"
-p "/home/ai/tb/LLM-Research/Llama-3___2-3B/original/params.json"
-t /home/ai/tb/LLM-Research/Llama-3___2-3B/original/tokenizer.model
-kv --disable_dynamic_shape --qnn
--num_sharding 8
--pt2e_quantize qnn_16a4w
-d fp32
--metadata '{"get_bos_id":128000, "get_eos_ids":[128009, 128001]}'
--output_name="test.pte"
--soc_model SM8550
--calibration_tasks wikitext
--calibration_limit 1
--calibration_seq_length 128
--calibration_data "<|begin_of_text|><|start_header_id|>system<|end_header_id|> You are an helpful assistant. <|eot_id|><|start_header_id|>user<|end_header_id|> Name all the prime ministers of India. <|eot_id|><|start_header_id|>assistant<|end_header_id|>"

[james-p-xu]

I am hitting the same issue as @tombang, with QNN version 2.29 and on release/0.5 branch.

Unknown QNN BinaryInfo version 3.
Failed to retrieve backend binary info from QNN context binary.
Failed to parse QNN Graph Info. The cache might be broken. Please consider to re-generate the cache.
QNN context cache is invalid.
Fail to configure Qnn context
Fail to initialize Qnn Manager
Init failed for backend QnnBackend: 0x1

java.lang.Exception: Execution of method forward failed with status 0x1

I saw someone mention on a different thread that they got the Llama example working with 2.31 so unsure what is happening? Would appreciate any pointers here.

[kimishpatel]

@cccclai can you tag someone from qcomm?

[cccclai]

I am hitting the same issue as @tombang, with QNN version 2.29 and on release/0.5 branch.

Unknown QNN BinaryInfo version 3.
Failed to retrieve backend binary info from QNN context binary.
Failed to parse QNN Graph Info. The cache might be broken. Please consider to re-generate the cache.
QNN context cache is invalid.
Fail to configure Qnn context
Fail to initialize Qnn Manager
Init failed for backend QnnBackend: 0x1

java.lang.Exception: Execution of method forward failed with status 0x1
I saw someone mention on a different thread that they got the Llama example working with 2.31 so unsure what is happening? Would appreciate any pointers here.

It seems like a different issue, as the reported issue happens during export (ahead of time), and the issue from your side is runtime error (I assume you generate the .pte file already?)

[cccclai]

@tombang Thank you for trying out the qnn + executorch solution. I've never tried 3b model with the executorch + qnn, but we have stories model set up in CI and it has been running fine

executorch/.github/workflows/pull.yml

Line 587 in 0342bab

PYTHON_EXECUTABLE=python bash .ci/scripts/test_qnn_static_llama.sh

. The CI is using qnn v2.28. ndk is likely r27b based on the the docker setup for the CI

executorch/.ci/docker/build.sh

Line 51 in 0342bab

ANDROID_NDK_VERSION=r27b

While we're trying to improve the out-of-the-box experience, do you mind trying out a simpler model to make sure the setup is correct?