thek0tyara/llama-cpp-turboquant
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Android fixed example

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Signed-off-by: Alejandro Saucedo <axsauze@gmail.com>
This commit is contained in:
Alejandro Saucedo 2022-01-30 13:25:04 +00:00
parent 4fca515d8f
commit d2d9ae6873
6 changed files with 42 additions and 35 deletions
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2
examples/android/android-simple/app/build.gradle
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@ -14,7 +14,7 @@ android {
versionName = "0.0.1"
externalNativeBuild {
cmake {
abiFilters "armeabi-v7a", 'arm64-v8a', 'x86', 'x86_64'
abiFilters "armeabi-v7a", 'arm64-v8a', 'x86'
arguments '-DANDROID_TOOLCHAIN=clang',
'-DANDROID_STL=c++_static',
'-DKOMPUTE_OPT_ANDROID_BUILD=1',

59
examples/android/android-simple/app/src/main/cpp/KomputeModelML.cpp
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@ -23,37 +23,38 @@ void KomputeModelML::train(std::vector<float> yData, std::vector<float> xIData,
{
kp::Manager mgr;
std::shared_ptr<kp::Tensor> xI = mgr.tensor(xIData);
std::shared_ptr<kp::Tensor> xJ = mgr.tensor(xJData);
std::shared_ptr<kp::TensorT<float>> xI = mgr.tensor(xIData);
std::shared_ptr<kp::TensorT<float>> xJ = mgr.tensor(xJData);
std::shared_ptr<kp::Tensor> y = mgr.tensor(yData);
std::shared_ptr<kp::TensorT<float>> y = mgr.tensor(yData);
std::shared_ptr<kp::Tensor> wIn = mgr.tensor({ 0.001, 0.001 });
std::shared_ptr<kp::Tensor> wOutI = mgr.tensor(zerosData);
std::shared_ptr<kp::Tensor> wOutJ = mgr.tensor(zerosData);
std::shared_ptr<kp::TensorT<float>> wIn = mgr.tensor({ 0.001, 0.001 });
std::shared_ptr<kp::TensorT<float>> wOutI = mgr.tensor(zerosData);
std::shared_ptr<kp::TensorT<float>> wOutJ = mgr.tensor(zerosData);
std::shared_ptr<kp::Tensor> bIn = mgr.tensor({ 0 });
std::shared_ptr<kp::Tensor> bOut = mgr.tensor(zerosData);
std::shared_ptr<kp::TensorT<float>> bIn = mgr.tensor({ 0 });
std::shared_ptr<kp::TensorT<float>> bOut = mgr.tensor(zerosData);
std::shared_ptr<kp::Tensor> lOut = mgr.tensor(zerosData);
std::shared_ptr<kp::TensorT<float>> lOut = mgr.tensor(zerosData);
std::vector<std::shared_ptr<kp::Tensor>> params = { xI, xJ, y,
wIn, wOutI, wOutJ,
bIn, bOut, lOut };
std::vector<uint32_t> spirv(
(uint32_t*)kp::shader_data::shaders_glsl_logisticregression_comp_spv,
(uint32_t*)(kp::shader_data::shaders_glsl_logisticregression_comp_spv
+ kp::shader_data::shaders_glsl_logisticregression_comp_spv_len));
std::vector<uint32_t> spirv = std::vector<uint32_t>(
(uint32_t*)kp::shader_data::shaders_glsl_logisticregression_comp_spv,
(uint32_t*)(kp::shader_data::shaders_glsl_logisticregression_comp_spv +
kp::shader_data::shaders_glsl_logisticregression_comp_spv_len));
std::shared_ptr<kp::Algorithm> algo =
mgr.algorithm(params, spirv, kp::Workgroup({ 5 }), std::vector<float>({ 5.0 }));
std::shared_ptr<kp::Algorithm> algorithm = mgr.algorithm(
params, spirv, kp::Workgroup({ 5 }), std::vector<float>({ 5.0 }));
mgr.sequence()->eval<kp::OpTensorSyncDevice>(params);
std::shared_ptr<kp::Sequence> sq = mgr.sequence()
->record<kp::OpTensorSyncDevice>({ wIn, bIn })
->record<kp::OpAlgoDispatch>(algo)
->record<kp::OpAlgoDispatch>(algorithm)
->record<kp::OpTensorSyncLocal>({ wOutI, wOutJ, bOut, lOut });
// Iterate across all expected iterations
@ -73,12 +74,15 @@ void KomputeModelML::train(std::vector<float> yData, std::vector<float> xIData,
KP_LOG_INFO("{}", wIn->data()[1]);
KP_LOG_INFO("{}", bIn->data()[0]);
this->mWeights = wIn;
this->mBias = bIn;
this->mWeights = wIn->vector();
this->mBias = bIn->vector();
}
}
std::vector<float> KomputeModelML::predict(std::vector<float> xI, std::vector<float> xJ) {
KP_LOG_INFO("Running prediction inference");
assert(xI.size() == xJ.size());
std::vector<float> retVector;
@ -89,28 +93,33 @@ std::vector<float> KomputeModelML::predict(std::vector<float> xI, std::vector<fl
for (size_t i = 0; i < xI.size(); i++) {
float xIVal = xI[i];
float xJVal = xJ[i];
float result = (xIVal * this->mWeights->data()[0]
+ xJVal * this->mWeights->data()[1]
+ this->mBias->data()[0]);
float result = (xIVal * this->mWeights[0]
+ xJVal * this->mWeights[1]
+ this->mBias[0]);
// Instead of using sigmoid we'll just return full numbers
float var = result > 0 ? 1 : 0;
retVector.push_back(var);
}
KP_LOG_INFO("Inference finalised");
return retVector;
}
std::vector<float> KomputeModelML::get_params() {
KP_LOG_INFO("Displaying results");
std::vector<float> retVector;
if(this->mWeights->size() + this->mBias->size() == 0) {
if(this->mWeights.size() + this->mBias.size() == 0) {
return retVector;
}
retVector.push_back(this->mWeights->data()[0]);
retVector.push_back(this->mWeights->data()[1]);
retVector.push_back(this->mBias->data()[0]);
retVector.push_back(this->mWeights[0]);
retVector.push_back(this->mWeights[1]);
retVector.push_back(this->mBias[0]);
retVector.push_back(99.0);
return retVector;

4
examples/android/android-simple/app/src/main/cpp/KomputeModelML.hpp
View file

@ -21,8 +21,8 @@ public:
std::vector<float> get_params();
private:
std::shared_ptr<kp::Tensor> mWeights;
std::shared_ptr<kp::Tensor> mBias;
std::vector<float> mWeights;
std::vector<float> mBias;
};

2
examples/android/android-simple/build.gradle
View file

@ -22,4 +22,4 @@ allprojects {
task clean(type: Delete) {
delete rootProject.buildDir
}
}