41 lines
1.8 KiB
Diff
41 lines
1.8 KiB
Diff
diff --git a/backends/qualcomm/CMakeLists.txt b/backends/qualcomm/CMakeLists.txt
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index e93731e..4951e1d 100644
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--- a/backends/qualcomm/CMakeLists.txt
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+++ b/backends/qualcomm/CMakeLists.txt
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@@ -308,8 +308,8 @@ if(${CMAKE_SYSTEM_PROCESSOR} MATCHES Hexagon)
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)
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endif()
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-# QNN pybind
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-if(${CMAKE_SYSTEM_PROCESSOR} MATCHES "x86_64")
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+# QNN pybind — host Python bindings, not for Android cross-compile
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+if(${CMAKE_SYSTEM_PROCESSOR} MATCHES "x86_64" AND NOT ANDROID)
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add_subdirectory(
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${EXECUTORCH_SOURCE_DIR}/third-party/pybind11
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${CMAKE_CURRENT_BINARY_DIR}/pybind11
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diff --git a/extension/android/jni/jni_layer_llama.cpp b/extension/android/jni/jni_layer_llama.cpp
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index 45f2414..e1c2a8f 100644
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--- a/extension/android/jni/jni_layer_llama.cpp
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+++ b/extension/android/jni/jni_layer_llama.cpp
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@@ -171,14 +171,17 @@ class ExecuTorchLlmJni : public facebook::jni::HybridClass<ExecuTorchLlmJni> {
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model_path->toStdString().c_str(),
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data_files_vector,
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executorch::extension::Module::LoadMode::MmapUseMlockIgnoreErrors);
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- std::string decoder_model = "llama3"; // use llama3 for now
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+ std::string decoder_model = "qwen3"; // Kazeia: our .pte was exported with --decoder_model qwen3-4b
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runner_ = std::make_unique<example::Runner<uint16_t>>( // QNN runner
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std::move(module),
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decoder_model.c_str(),
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model_path->toStdString().c_str(),
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tokenizer_path->toStdString().c_str(),
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- "",
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- "");
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+ /* performance_output_path */ "",
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+ /* dump_logits_path */ "",
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+ /* temperature */ 0.7f,
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+ /* eval_mode */ 0, // EvalMode::kKVCached (our .pte has only kv_forward, no prefill_forward)
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+ /* shared_buffer */ true);
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model_type_category_ = MODEL_TYPE_CATEGORY_LLM;
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#endif
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#if defined(EXECUTORCH_BUILD_MEDIATEK)
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