This reverts commit efc8f767c8.
This commit is contained in:
Brian
GitHub
parent
5e31828d3e
commit
1265c670fd
14 changed files with 49 additions and 145 deletions
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@ -7,6 +7,8 @@ android {
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namespace = "com.example.llama"
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compileSdk = 34
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ndkVersion = "26.1.10909125"
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defaultConfig {
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applicationId = "com.example.llama"
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minSdk = 33
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@ -18,6 +20,17 @@ android {
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vectorDrawables {
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useSupportLibrary = true
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}
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ndk {
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// Add NDK properties if wanted, e.g.
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// abiFilters += listOf("arm64-v8a")
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}
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externalNativeBuild {
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cmake {
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arguments += "-DCMAKE_BUILD_TYPE=Release"
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cppFlags += listOf()
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arguments += listOf()
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}
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}
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}
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buildTypes {
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@ -42,6 +55,17 @@ android {
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composeOptions {
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kotlinCompilerExtensionVersion = "1.5.1"
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}
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packaging {
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resources {
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excludes += "/META-INF/{AL2.0,LGPL2.1}"
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}
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}
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externalNativeBuild {
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cmake {
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path = file("src/main/cpp/CMakeLists.txt")
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version = "3.22.1"
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}
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}
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}
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dependencies {
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@ -54,7 +78,6 @@ dependencies {
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implementation("androidx.compose.ui:ui-graphics")
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implementation("androidx.compose.ui:ui-tooling-preview")
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implementation("androidx.compose.material3:material3")
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implementation(project(":llama"))
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testImplementation("junit:junit:4.13.2")
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androidTestImplementation("androidx.test.ext:junit:1.1.5")
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androidTestImplementation("androidx.test.espresso:espresso-core:3.5.1")
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50
examples/llama.android/app/src/main/cpp/CMakeLists.txt
Normal file
50
examples/llama.android/app/src/main/cpp/CMakeLists.txt
Normal file
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@ -0,0 +1,50 @@
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# For more information about using CMake with Android Studio, read the
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# documentation: https://d.android.com/studio/projects/add-native-code.html.
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# For more examples on how to use CMake, see https://github.com/android/ndk-samples.
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# Sets the minimum CMake version required for this project.
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cmake_minimum_required(VERSION 3.22.1)
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# Declares the project name. The project name can be accessed via ${ PROJECT_NAME},
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# Since this is the top level CMakeLists.txt, the project name is also accessible
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# with ${CMAKE_PROJECT_NAME} (both CMake variables are in-sync within the top level
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# build script scope).
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project("llama-android")
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include(FetchContent)
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FetchContent_Declare(
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llama
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GIT_REPOSITORY https://github.com/ggerganov/llama.cpp
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GIT_TAG master
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)
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# Also provides "common"
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FetchContent_MakeAvailable(llama)
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# Creates and names a library, sets it as either STATIC
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# or SHARED, and provides the relative paths to its source code.
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# You can define multiple libraries, and CMake builds them for you.
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# Gradle automatically packages shared libraries with your APK.
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#
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# In this top level CMakeLists.txt, ${CMAKE_PROJECT_NAME} is used to define
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# the target library name; in the sub-module's CMakeLists.txt, ${PROJECT_NAME}
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# is preferred for the same purpose.
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#
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# In order to load a library into your app from Java/Kotlin, you must call
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# System.loadLibrary() and pass the name of the library defined here;
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# for GameActivity/NativeActivity derived applications, the same library name must be
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# used in the AndroidManifest.xml file.
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add_library(${CMAKE_PROJECT_NAME} SHARED
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# List C/C++ source files with relative paths to this CMakeLists.txt.
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llama-android.cpp)
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# Specifies libraries CMake should link to your target library. You
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# can link libraries from various origins, such as libraries defined in this
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# build script, prebuilt third-party libraries, or Android system libraries.
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target_link_libraries(${CMAKE_PROJECT_NAME}
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# List libraries link to the target library
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llama
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common
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android
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log)
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443
examples/llama.android/app/src/main/cpp/llama-android.cpp
Normal file
443
examples/llama.android/app/src/main/cpp/llama-android.cpp
Normal file
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@ -0,0 +1,443 @@
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#include <android/log.h>
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#include <jni.h>
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#include <iomanip>
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#include <math.h>
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#include <string>
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#include <unistd.h>
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#include "llama.h"
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#include "common/common.h"
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// Write C++ code here.
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//
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// Do not forget to dynamically load the C++ library into your application.
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//
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// For instance,
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//
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// In MainActivity.java:
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// static {
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// System.loadLibrary("llama-android");
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// }
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//
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// Or, in MainActivity.kt:
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// companion object {
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// init {
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// System.loadLibrary("llama-android")
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// }
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// }
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#define TAG "llama-android.cpp"
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#define LOGi(...) __android_log_print(ANDROID_LOG_INFO, TAG, __VA_ARGS__)
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#define LOGe(...) __android_log_print(ANDROID_LOG_ERROR, TAG, __VA_ARGS__)
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jclass la_int_var;
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jmethodID la_int_var_value;
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jmethodID la_int_var_inc;
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std::string cached_token_chars;
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bool is_valid_utf8(const char * string) {
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if (!string) {
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return true;
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}
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const unsigned char * bytes = (const unsigned char *)string;
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int num;
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while (*bytes != 0x00) {
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if ((*bytes & 0x80) == 0x00) {
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// U+0000 to U+007F
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num = 1;
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} else if ((*bytes & 0xE0) == 0xC0) {
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// U+0080 to U+07FF
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num = 2;
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} else if ((*bytes & 0xF0) == 0xE0) {
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// U+0800 to U+FFFF
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num = 3;
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} else if ((*bytes & 0xF8) == 0xF0) {
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// U+10000 to U+10FFFF
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num = 4;
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} else {
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return false;
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}
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bytes += 1;
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for (int i = 1; i < num; ++i) {
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if ((*bytes & 0xC0) != 0x80) {
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return false;
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}
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bytes += 1;
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}
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}
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return true;
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}
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static void log_callback(ggml_log_level level, const char * fmt, void * data) {
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if (level == GGML_LOG_LEVEL_ERROR) __android_log_print(ANDROID_LOG_ERROR, TAG, fmt, data);
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else if (level == GGML_LOG_LEVEL_INFO) __android_log_print(ANDROID_LOG_INFO, TAG, fmt, data);
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else if (level == GGML_LOG_LEVEL_WARN) __android_log_print(ANDROID_LOG_WARN, TAG, fmt, data);
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else __android_log_print(ANDROID_LOG_DEFAULT, TAG, fmt, data);
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}
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extern "C"
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JNIEXPORT jlong JNICALL
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Java_com_example_llama_Llm_load_1model(JNIEnv *env, jobject, jstring filename) {
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llama_model_params model_params = llama_model_default_params();
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auto path_to_model = env->GetStringUTFChars(filename, 0);
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LOGi("Loading model from %s", path_to_model);
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auto model = llama_load_model_from_file(path_to_model, model_params);
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env->ReleaseStringUTFChars(filename, path_to_model);
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if (!model) {
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LOGe("load_model() failed");
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env->ThrowNew(env->FindClass("java/lang/IllegalStateException"), "load_model() failed");
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return 0;
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}
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return reinterpret_cast<jlong>(model);
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_free_1model(JNIEnv *, jobject, jlong model) {
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llama_free_model(reinterpret_cast<llama_model *>(model));
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}
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extern "C"
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JNIEXPORT jlong JNICALL
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Java_com_example_llama_Llm_new_1context(JNIEnv *env, jobject, jlong jmodel) {
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auto model = reinterpret_cast<llama_model *>(jmodel);
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if (!model) {
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LOGe("new_context(): model cannot be null");
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env->ThrowNew(env->FindClass("java/lang/IllegalArgumentException"), "Model cannot be null");
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return 0;
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}
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int n_threads = std::max(1, std::min(8, (int) sysconf(_SC_NPROCESSORS_ONLN) - 2));
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LOGi("Using %d threads", n_threads);
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llama_context_params ctx_params = llama_context_default_params();
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ctx_params.seed = 1234;
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ctx_params.n_ctx = 2048;
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ctx_params.n_threads = n_threads;
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ctx_params.n_threads_batch = n_threads;
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llama_context * context = llama_new_context_with_model(model, ctx_params);
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if (!context) {
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LOGe("llama_new_context_with_model() returned null)");
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env->ThrowNew(env->FindClass("java/lang/IllegalStateException"),
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"llama_new_context_with_model() returned null)");
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return 0;
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}
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return reinterpret_cast<jlong>(context);
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_free_1context(JNIEnv *, jobject, jlong context) {
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llama_free(reinterpret_cast<llama_context *>(context));
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_backend_1free(JNIEnv *, jobject) {
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llama_backend_free();
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_log_1to_1android(JNIEnv *, jobject) {
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llama_log_set(log_callback, NULL);
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}
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extern "C"
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JNIEXPORT jstring JNICALL
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Java_com_example_llama_Llm_bench_1model(
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JNIEnv *env,
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jobject,
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jlong context_pointer,
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jlong model_pointer,
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jlong batch_pointer,
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jint pp,
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jint tg,
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jint pl,
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jint nr
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) {
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auto pp_avg = 0.0;
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auto tg_avg = 0.0;
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auto pp_std = 0.0;
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auto tg_std = 0.0;
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const auto context = reinterpret_cast<llama_context *>(context_pointer);
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const auto model = reinterpret_cast<llama_model *>(model_pointer);
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const auto batch = reinterpret_cast<llama_batch *>(batch_pointer);
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const int n_ctx = llama_n_ctx(context);
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LOGi("n_ctx = %d", n_ctx);
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int i, j;
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int nri;
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for (nri = 0; nri < nr; nri++) {
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LOGi("Benchmark prompt processing (pp)");
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llama_batch_clear(*batch);
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const int n_tokens = pp;
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for (i = 0; i < n_tokens; i++) {
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llama_batch_add(*batch, 0, i, { 0 }, false);
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}
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batch->logits[batch->n_tokens - 1] = true;
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llama_kv_cache_clear(context);
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const auto t_pp_start = ggml_time_us();
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if (llama_decode(context, *batch) != 0) {
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LOGi("llama_decode() failed during prompt processing");
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}
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const auto t_pp_end = ggml_time_us();
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// bench text generation
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LOGi("Benchmark text generation (tg)");
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llama_kv_cache_clear(context);
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const auto t_tg_start = ggml_time_us();
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for (i = 0; i < tg; i++) {
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llama_batch_clear(*batch);
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for (j = 0; j < pl; j++) {
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llama_batch_add(*batch, 0, i, { j }, true);
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}
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LOGi("llama_decode() text generation: %d", i);
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if (llama_decode(context, *batch) != 0) {
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LOGi("llama_decode() failed during text generation");
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}
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}
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const auto t_tg_end = ggml_time_us();
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llama_kv_cache_clear(context);
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const auto t_pp = double(t_pp_end - t_pp_start) / 1000000.0;
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const auto t_tg = double(t_tg_end - t_tg_start) / 1000000.0;
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const auto speed_pp = double(pp) / t_pp;
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const auto speed_tg = double(pl * tg) / t_tg;
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pp_avg += speed_pp;
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tg_avg += speed_tg;
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pp_std += speed_pp * speed_pp;
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tg_std += speed_tg * speed_tg;
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LOGi("pp %f t/s, tg %f t/s", speed_pp, speed_tg);
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}
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pp_avg /= double(nr);
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tg_avg /= double(nr);
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if (nr > 1) {
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pp_std = sqrt(pp_std / double(nr - 1) - pp_avg * pp_avg * double(nr) / double(nr - 1));
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tg_std = sqrt(tg_std / double(nr - 1) - tg_avg * tg_avg * double(nr) / double(nr - 1));
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} else {
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pp_std = 0;
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tg_std = 0;
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}
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char model_desc[128];
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llama_model_desc(model, model_desc, sizeof(model_desc));
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const auto model_size = double(llama_model_size(model)) / 1024.0 / 1024.0 / 1024.0;
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const auto model_n_params = double(llama_model_n_params(model)) / 1e9;
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const auto backend = "(Android)"; // TODO: What should this be?
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std::stringstream result;
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result << std::setprecision(2);
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result << "| model | size | params | backend | test | t/s |\n";
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result << "| --- | --- | --- | --- | --- | --- |\n";
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result << "| " << model_desc << " | " << model_size << "GiB | " << model_n_params << "B | " << backend << " | pp " << pp << " | " << pp_avg << " ± " << pp_std << " |\n";
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result << "| " << model_desc << " | " << model_size << "GiB | " << model_n_params << "B | " << backend << " | tg " << tg << " | " << tg_avg << " ± " << tg_std << " |\n";
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return env->NewStringUTF(result.str().c_str());
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_free_1batch(JNIEnv *, jobject, jlong batch_pointer) {
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llama_batch_free(*reinterpret_cast<llama_batch *>(batch_pointer));
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}
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extern "C"
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JNIEXPORT jlong JNICALL
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Java_com_example_llama_Llm_new_1batch(JNIEnv *, jobject, jint n_tokens, jint embd, jint n_seq_max) {
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// Source: Copy of llama.cpp:llama_batch_init but heap-allocated.
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llama_batch *batch = new llama_batch {
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0,
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nullptr,
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nullptr,
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nullptr,
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nullptr,
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nullptr,
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nullptr,
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0,
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0,
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0,
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};
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if (embd) {
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batch->embd = (float *) malloc(sizeof(float) * n_tokens * embd);
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} else {
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batch->token = (llama_token *) malloc(sizeof(llama_token) * n_tokens);
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}
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batch->pos = (llama_pos *) malloc(sizeof(llama_pos) * n_tokens);
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batch->n_seq_id = (int32_t *) malloc(sizeof(int32_t) * n_tokens);
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batch->seq_id = (llama_seq_id **) malloc(sizeof(llama_seq_id *) * n_tokens);
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for (int i = 0; i < n_tokens; ++i) {
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batch->seq_id[i] = (llama_seq_id *) malloc(sizeof(llama_seq_id) * n_seq_max);
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}
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batch->logits = (int8_t *) malloc(sizeof(int8_t) * n_tokens);
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return reinterpret_cast<jlong>(batch);
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}
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extern "C"
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JNIEXPORT void JNICALL
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Java_com_example_llama_Llm_backend_1init(JNIEnv *, jobject) {
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llama_backend_init();
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}
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extern "C"
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JNIEXPORT jstring JNICALL
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Java_com_example_llama_Llm_system_1info(JNIEnv *env, jobject) {
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return env->NewStringUTF(llama_print_system_info());
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}
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extern "C"
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JNIEXPORT jint JNICALL
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Java_com_example_llama_Llm_completion_1init(
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JNIEnv *env,
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jobject,
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jlong context_pointer,
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jlong batch_pointer,
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jstring jtext,
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jint n_len
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) {
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cached_token_chars.clear();
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const auto text = env->GetStringUTFChars(jtext, 0);
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const auto context = reinterpret_cast<llama_context *>(context_pointer);
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const auto batch = reinterpret_cast<llama_batch *>(batch_pointer);
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const auto tokens_list = llama_tokenize(context, text, 1);
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auto n_ctx = llama_n_ctx(context);
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auto n_kv_req = tokens_list.size() + (n_len - tokens_list.size());
|
||||
|
||||
LOGi("n_len = %d, n_ctx = %d, n_kv_req = %d", n_len, n_ctx, n_kv_req);
|
||||
|
||||
if (n_kv_req > n_ctx) {
|
||||
LOGe("error: n_kv_req > n_ctx, the required KV cache size is not big enough");
|
||||
}
|
||||
|
||||
for (auto id : tokens_list) {
|
||||
LOGi("%s", llama_token_to_piece(context, id).c_str());
|
||||
}
|
||||
|
||||
llama_batch_clear(*batch);
|
||||
|
||||
// evaluate the initial prompt
|
||||
for (auto i = 0; i < tokens_list.size(); i++) {
|
||||
llama_batch_add(*batch, tokens_list[i], i, { 0 }, false);
|
||||
}
|
||||
|
||||
// llama_decode will output logits only for the last token of the prompt
|
||||
batch->logits[batch->n_tokens - 1] = true;
|
||||
|
||||
if (llama_decode(context, *batch) != 0) {
|
||||
LOGe("llama_decode() failed");
|
||||
}
|
||||
|
||||
env->ReleaseStringUTFChars(jtext, text);
|
||||
|
||||
return batch->n_tokens;
|
||||
}
|
||||
|
||||
extern "C"
|
||||
JNIEXPORT jstring JNICALL
|
||||
Java_com_example_llama_Llm_completion_1loop(
|
||||
JNIEnv * env,
|
||||
jobject,
|
||||
jlong context_pointer,
|
||||
jlong batch_pointer,
|
||||
jint n_len,
|
||||
jobject intvar_ncur
|
||||
) {
|
||||
const auto context = reinterpret_cast<llama_context *>(context_pointer);
|
||||
const auto batch = reinterpret_cast<llama_batch *>(batch_pointer);
|
||||
const auto model = llama_get_model(context);
|
||||
|
||||
if (!la_int_var) la_int_var = env->GetObjectClass(intvar_ncur);
|
||||
if (!la_int_var_value) la_int_var_value = env->GetMethodID(la_int_var, "getValue", "()I");
|
||||
if (!la_int_var_inc) la_int_var_inc = env->GetMethodID(la_int_var, "inc", "()V");
|
||||
|
||||
auto n_vocab = llama_n_vocab(model);
|
||||
auto logits = llama_get_logits_ith(context, batch->n_tokens - 1);
|
||||
|
||||
std::vector<llama_token_data> candidates;
|
||||
candidates.reserve(n_vocab);
|
||||
|
||||
for (llama_token token_id = 0; token_id < n_vocab; token_id++) {
|
||||
candidates.emplace_back(llama_token_data{ token_id, logits[token_id], 0.0f });
|
||||
}
|
||||
|
||||
llama_token_data_array candidates_p = { candidates.data(), candidates.size(), false };
|
||||
|
||||
// sample the most likely token
|
||||
const auto new_token_id = llama_sample_token_greedy(context, &candidates_p);
|
||||
|
||||
const auto n_cur = env->CallIntMethod(intvar_ncur, la_int_var_value);
|
||||
if (llama_token_is_eog(model, new_token_id) || n_cur == n_len) {
|
||||
return env->NewStringUTF("");
|
||||
}
|
||||
|
||||
auto new_token_chars = llama_token_to_piece(context, new_token_id);
|
||||
cached_token_chars += new_token_chars;
|
||||
|
||||
jstring new_token = nullptr;
|
||||
if (is_valid_utf8(cached_token_chars.c_str())) {
|
||||
new_token = env->NewStringUTF(cached_token_chars.c_str());
|
||||
LOGi("cached: %s, new_token_chars: `%s`, id: %d", cached_token_chars.c_str(), new_token_chars.c_str(), new_token_id);
|
||||
cached_token_chars.clear();
|
||||
} else {
|
||||
new_token = env->NewStringUTF("");
|
||||
}
|
||||
|
||||
llama_batch_clear(*batch);
|
||||
llama_batch_add(*batch, new_token_id, n_cur, { 0 }, true);
|
||||
|
||||
env->CallVoidMethod(intvar_ncur, la_int_var_inc);
|
||||
|
||||
if (llama_decode(context, *batch) != 0) {
|
||||
LOGe("llama_decode() returned null");
|
||||
}
|
||||
|
||||
return new_token;
|
||||
}
|
||||
|
||||
extern "C"
|
||||
JNIEXPORT void JNICALL
|
||||
Java_com_example_llama_Llm_kv_1cache_1clear(JNIEnv *, jobject, jlong context) {
|
||||
llama_kv_cache_clear(reinterpret_cast<llama_context *>(context));
|
||||
}
|
||||
|
|
@ -0,0 +1,172 @@
|
|||
package com.example.llama
|
||||
|
||||
import android.util.Log
|
||||
import kotlinx.coroutines.CoroutineDispatcher
|
||||
import kotlinx.coroutines.asCoroutineDispatcher
|
||||
import kotlinx.coroutines.flow.Flow
|
||||
import kotlinx.coroutines.flow.flow
|
||||
import kotlinx.coroutines.flow.flowOn
|
||||
import kotlinx.coroutines.withContext
|
||||
import java.util.concurrent.Executors
|
||||
import kotlin.concurrent.thread
|
||||
|
||||
class Llm {
|
||||
private val tag: String? = this::class.simpleName
|
||||
|
||||
private val threadLocalState: ThreadLocal<State> = ThreadLocal.withInitial { State.Idle }
|
||||
|
||||
private val runLoop: CoroutineDispatcher = Executors.newSingleThreadExecutor {
|
||||
thread(start = false, name = "Llm-RunLoop") {
|
||||
Log.d(tag, "Dedicated thread for native code: ${Thread.currentThread().name}")
|
||||
|
||||
// No-op if called more than once.
|
||||
System.loadLibrary("llama-android")
|
||||
|
||||
// Set llama log handler to Android
|
||||
log_to_android()
|
||||
backend_init(false)
|
||||
|
||||
Log.d(tag, system_info())
|
||||
|
||||
it.run()
|
||||
}.apply {
|
||||
uncaughtExceptionHandler = Thread.UncaughtExceptionHandler { _, exception: Throwable ->
|
||||
Log.e(tag, "Unhandled exception", exception)
|
||||
}
|
||||
}
|
||||
}.asCoroutineDispatcher()
|
||||
|
||||
private val nlen: Int = 64
|
||||
|
||||
private external fun log_to_android()
|
||||
private external fun load_model(filename: String): Long
|
||||
private external fun free_model(model: Long)
|
||||
private external fun new_context(model: Long): Long
|
||||
private external fun free_context(context: Long)
|
||||
private external fun backend_init(numa: Boolean)
|
||||
private external fun backend_free()
|
||||
private external fun free_batch(batch: Long)
|
||||
private external fun new_batch(nTokens: Int, embd: Int, nSeqMax: Int): Long
|
||||
private external fun bench_model(
|
||||
context: Long,
|
||||
model: Long,
|
||||
batch: Long,
|
||||
pp: Int,
|
||||
tg: Int,
|
||||
pl: Int,
|
||||
nr: Int
|
||||
): String
|
||||
|
||||
private external fun system_info(): String
|
||||
|
||||
private external fun completion_init(
|
||||
context: Long,
|
||||
batch: Long,
|
||||
text: String,
|
||||
nLen: Int
|
||||
): Int
|
||||
|
||||
private external fun completion_loop(
|
||||
context: Long,
|
||||
batch: Long,
|
||||
nLen: Int,
|
||||
ncur: IntVar
|
||||
): String?
|
||||
|
||||
private external fun kv_cache_clear(context: Long)
|
||||
|
||||
suspend fun bench(pp: Int, tg: Int, pl: Int, nr: Int = 1): String {
|
||||
return withContext(runLoop) {
|
||||
when (val state = threadLocalState.get()) {
|
||||
is State.Loaded -> {
|
||||
Log.d(tag, "bench(): $state")
|
||||
bench_model(state.context, state.model, state.batch, pp, tg, pl, nr)
|
||||
}
|
||||
|
||||
else -> throw IllegalStateException("No model loaded")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
suspend fun load(pathToModel: String) {
|
||||
withContext(runLoop) {
|
||||
when (threadLocalState.get()) {
|
||||
is State.Idle -> {
|
||||
val model = load_model(pathToModel)
|
||||
if (model == 0L) throw IllegalStateException("load_model() failed")
|
||||
|
||||
val context = new_context(model)
|
||||
if (context == 0L) throw IllegalStateException("new_context() failed")
|
||||
|
||||
val batch = new_batch(512, 0, 1)
|
||||
if (batch == 0L) throw IllegalStateException("new_batch() failed")
|
||||
|
||||
Log.i(tag, "Loaded model $pathToModel")
|
||||
threadLocalState.set(State.Loaded(model, context, batch))
|
||||
}
|
||||
else -> throw IllegalStateException("Model already loaded")
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
fun send(message: String): Flow<String> = flow {
|
||||
when (val state = threadLocalState.get()) {
|
||||
is State.Loaded -> {
|
||||
val ncur = IntVar(completion_init(state.context, state.batch, message, nlen))
|
||||
while (ncur.value <= nlen) {
|
||||
val str = completion_loop(state.context, state.batch, nlen, ncur)
|
||||
if (str == null) {
|
||||
break
|
||||
}
|
||||
emit(str)
|
||||
}
|
||||
kv_cache_clear(state.context)
|
||||
}
|
||||
else -> {}
|
||||
}
|
||||
}.flowOn(runLoop)
|
||||
|
||||
/**
|
||||
* Unloads the model and frees resources.
|
||||
*
|
||||
* This is a no-op if there's no model loaded.
|
||||
*/
|
||||
suspend fun unload() {
|
||||
withContext(runLoop) {
|
||||
when (val state = threadLocalState.get()) {
|
||||
is State.Loaded -> {
|
||||
free_context(state.context)
|
||||
free_model(state.model)
|
||||
free_batch(state.batch)
|
||||
|
||||
threadLocalState.set(State.Idle)
|
||||
}
|
||||
else -> {}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
companion object {
|
||||
private class IntVar(value: Int) {
|
||||
@Volatile
|
||||
var value: Int = value
|
||||
private set
|
||||
|
||||
fun inc() {
|
||||
synchronized(this) {
|
||||
value += 1
|
||||
}
|
||||
}
|
||||
}
|
||||
|
||||
private sealed interface State {
|
||||
data object Idle: State
|
||||
data class Loaded(val model: Long, val context: Long, val batch: Long): State
|
||||
}
|
||||
|
||||
// Enforce only one instance of Llm.
|
||||
private val _instance: Llm = Llm()
|
||||
|
||||
fun instance(): Llm = _instance
|
||||
}
|
||||
}
|
||||
|
|
@ -1,6 +1,5 @@
|
|||
package com.example.llama
|
||||
|
||||
import android.llama.cpp.LLamaAndroid
|
||||
import android.util.Log
|
||||
import androidx.compose.runtime.getValue
|
||||
import androidx.compose.runtime.mutableStateOf
|
||||
|
|
@ -10,7 +9,7 @@ import androidx.lifecycle.viewModelScope
|
|||
import kotlinx.coroutines.flow.catch
|
||||
import kotlinx.coroutines.launch
|
||||
|
||||
class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instance()): ViewModel() {
|
||||
class MainViewModel(private val llm: Llm = Llm.instance()): ViewModel() {
|
||||
companion object {
|
||||
@JvmStatic
|
||||
private val NanosPerSecond = 1_000_000_000.0
|
||||
|
|
@ -29,7 +28,7 @@ class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instan
|
|||
|
||||
viewModelScope.launch {
|
||||
try {
|
||||
llamaAndroid.unload()
|
||||
llm.unload()
|
||||
} catch (exc: IllegalStateException) {
|
||||
messages += exc.message!!
|
||||
}
|
||||
|
|
@ -45,7 +44,7 @@ class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instan
|
|||
messages += ""
|
||||
|
||||
viewModelScope.launch {
|
||||
llamaAndroid.send(text)
|
||||
llm.send(text)
|
||||
.catch {
|
||||
Log.e(tag, "send() failed", it)
|
||||
messages += it.message!!
|
||||
|
|
@ -58,7 +57,7 @@ class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instan
|
|||
viewModelScope.launch {
|
||||
try {
|
||||
val start = System.nanoTime()
|
||||
val warmupResult = llamaAndroid.bench(pp, tg, pl, nr)
|
||||
val warmupResult = llm.bench(pp, tg, pl, nr)
|
||||
val end = System.nanoTime()
|
||||
|
||||
messages += warmupResult
|
||||
|
|
@ -71,7 +70,7 @@ class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instan
|
|||
return@launch
|
||||
}
|
||||
|
||||
messages += llamaAndroid.bench(512, 128, 1, 3)
|
||||
messages += llm.bench(512, 128, 1, 3)
|
||||
} catch (exc: IllegalStateException) {
|
||||
Log.e(tag, "bench() failed", exc)
|
||||
messages += exc.message!!
|
||||
|
|
@ -82,7 +81,7 @@ class MainViewModel(private val llamaAndroid: LLamaAndroid = LLamaAndroid.instan
|
|||
fun load(pathToModel: String) {
|
||||
viewModelScope.launch {
|
||||
try {
|
||||
llamaAndroid.load(pathToModel)
|
||||
llm.load(pathToModel)
|
||||
messages += "Loaded $pathToModel"
|
||||
} catch (exc: IllegalStateException) {
|
||||
Log.e(tag, "load() failed", exc)
|
||||
|
|
|
|||
Loading…
Add table
Add a link
Reference in a new issue