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[demo] Reuse input tensor buffer #6

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Oct 5, 2019
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[demo] Reuse input tensor buffer #6

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23 changes: 16 additions & 7 deletions PyTorchDemoApp/app/src/main/java/org/pytorch/demo/vision/ImageClassificationActivity.java
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Original file line number Diff line number Diff line change
Expand Up @@ -19,6 +19,7 @@
import org.pytorch.torchvision.TensorImageUtils;

import java.io.File;
import java.nio.FloatBuffer;
import java.util.Locale;

import androidx.annotation.Nullable;
Expand Down Expand Up @@ -59,6 +60,8 @@ public AnalysisResult(String[] topNClassNames, float[] topNScores,
private TextView mMsText;
private Module mModule;
private String mModuleAssetName;
private FloatBuffer mInputTensorBuffer;
private Tensor mInputTensor;

@Override
protected int getContentViewLayoutId() {
Expand Down Expand Up @@ -136,18 +139,24 @@ protected AnalysisResult analyzeImage(ImageProxy image, int rotationDegrees) {
final String moduleFileAbsoluteFilePath = new File(
Utils.assetFilePath(this, getModuleAssetName())).getAbsolutePath();
mModule = Module.load(moduleFileAbsoluteFilePath);

mInputTensorBuffer =
Tensor.allocateFloatBuffer(3 * INPUT_TENSOR_WIDTH * INPUT_TENSOR_HEIGHT);
mInputTensor = Tensor.newFloat32Tensor(
new long[]{1, 3, INPUT_TENSOR_HEIGHT, INPUT_TENSOR_WIDTH},
mInputTensorBuffer);
}

final long startTime = SystemClock.elapsedRealtime();
final Tensor inputTensor =
TensorImageUtils.imageYUV420CenterCropToFloat32Tensor(
image.getImage(), rotationDegrees,
INPUT_TENSOR_WIDTH, INPUT_TENSOR_HEIGHT,
TensorImageUtils.TORCHVISION_NORM_MEAN_RGB,
TensorImageUtils.TORCHVISION_NORM_STD_RGB);
TensorImageUtils.imageYUV420CenterCropToFloatBuffer(
image.getImage(), rotationDegrees,
INPUT_TENSOR_WIDTH, INPUT_TENSOR_HEIGHT,
TensorImageUtils.TORCHVISION_NORM_MEAN_RGB,
TensorImageUtils.TORCHVISION_NORM_STD_RGB,
mInputTensorBuffer, 0);

final long moduleForwardStartTime = SystemClock.elapsedRealtime();
final Tensor outputTensor = mModule.forward(IValue.tensor(inputTensor)).getTensor();
final Tensor outputTensor = mModule.forward(IValue.tensor(mInputTensor)).getTensor();
final long moduleForwardDuration = SystemClock.elapsedRealtime() - moduleForwardStartTime;

final float[] scores = outputTensor.getDataAsFloatArray();
Expand Down