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[android] Use torch::from_blob instead of shareExternalPointer, nits #25973

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[android] Use torch::from_blob instead of shareExternalPointer, nits #25973

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58 changes: 28 additions & 30 deletions android/pytorch_android/src/main/cpp/pytorch_jni.cpp
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Original file line number Diff line number Diff line change
Expand Up @@ -41,53 +41,51 @@ struct JHashMap
};

static at::Tensor newAtTensor(
facebook::jni::alias_ref<facebook::jni::JBuffer> inputData,
facebook::jni::alias_ref<jlongArray> inputDims,
facebook::jni::alias_ref<facebook::jni::JBuffer> jbuffer,
facebook::jni::alias_ref<jlongArray> jdims,
jint typeCode) {
const auto inputDimsRank = inputDims->size();
const auto inputDimsArr = inputDims->getRegion(0, inputDimsRank);
std::vector<int64_t> inputDimsVec;
auto inputNumel = 1;
for (auto i = 0; i < inputDimsRank; ++i) {
inputDimsVec.push_back(inputDimsArr[i]);
inputNumel *= inputDimsArr[i];
const auto rank = jdims->size();
const auto dimsArr = jdims->getRegion(0, rank);
std::vector<int64_t> dimsVec{};
dimsVec.reserve(rank);
auto numel = 1;
for (auto i = 0; i < rank; ++i) {
dimsVec.push_back(dimsArr[i]);
numel *= dimsArr[i];
}
JNIEnv* jni = facebook::jni::Environment::current();
caffe2::TypeMeta inputTypeMeta{};
int inputDataElementSizeBytes = 0;
caffe2::TypeMeta typeMeta{};
int dataElementSizeBytes = 0;
if (kTensorTypeCodeFloat32 == typeCode) {
inputDataElementSizeBytes = 4;
inputTypeMeta = caffe2::TypeMeta::Make<float>();
dataElementSizeBytes = 4;
typeMeta = caffe2::TypeMeta::Make<float>();
} else if (kTensorTypeCodeInt32 == typeCode) {
inputDataElementSizeBytes = 4;
inputTypeMeta = caffe2::TypeMeta::Make<int>();
dataElementSizeBytes = 4;
typeMeta = caffe2::TypeMeta::Make<int>();
} else if (kTensorTypeCodeByte == typeCode) {
inputDataElementSizeBytes = 1;
inputTypeMeta = caffe2::TypeMeta::Make<uint8_t>();
dataElementSizeBytes = 1;
typeMeta = caffe2::TypeMeta::Make<uint8_t>();
} else {
facebook::jni::throwNewJavaException(
facebook::jni::gJavaLangIllegalArgumentException,
"Unknown Tensor typeCode %d",
typeCode);
}
const auto inputDataCapacity = jni->GetDirectBufferCapacity(inputData.get());
if (inputDataCapacity != inputNumel) {
const auto dataCapacity = jni->GetDirectBufferCapacity(jbuffer.get());
if (dataCapacity != numel) {
facebook::jni::throwNewJavaException(
facebook::jni::gJavaLangIllegalArgumentException,
"Tensor dimensions(elements number:%d, element byte size:%d, total "
"bytes:%d) inconsistent with buffer capacity(%d)",
inputNumel,
inputDataElementSizeBytes,
inputNumel * inputDataElementSizeBytes,
inputDataCapacity);
numel,
dataElementSizeBytes,
numel * dataElementSizeBytes,
dataCapacity);
}

at::Tensor inputTensor = torch::empty(torch::IntArrayRef(inputDimsVec));
inputTensor.unsafeGetTensorImpl()->ShareExternalPointer(
{jni->GetDirectBufferAddress(inputData.get()), at::DeviceType::CPU},
inputTypeMeta,
inputDataCapacity);
return inputTensor;
return torch::from_blob(
jni->GetDirectBufferAddress(jbuffer.get()),
torch::IntArrayRef(dimsVec),
at::TensorOptions(typeMeta));
}

class JTensor : public facebook::jni::JavaClass<JTensor> {
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