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Merge pull request from freedomtan:gpu_delegate_already_allows_quant

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PiperOrigin-RevId: 327630219
Change-Id: I04153386bcf1a80af7356446ee279d29fb04d342
This commit is contained in:
TensorFlower Gardener 2020-08-20 08:31:04 -07:00
commit e7d27d8507
2 changed files with 47 additions and 47 deletions
tensorflow/lite/java/demo/app/src/main/java/com/example/android/tflitecamerademo
Camera2BasicFragment.javaImageClassifier.java

89
tensorflow/lite/java/demo/app/src/main/java/com/example/android/tflitecamerademo/Camera2BasicFragment.java
View File

@ -326,58 +326,55 @@ public class Camera2BasicFragment extends Fragment
final int deviceIndex = deviceView.getCheckedItemPosition();
final int numThreads = np.getValue();
backgroundHandler.post(() -> {
if (modelIndex == currentModel && deviceIndex == currentDevice
backgroundHandler.post(
() -> {
if (modelIndex == currentModel
&& deviceIndex == currentDevice
&& numThreads == currentNumThreads) {
return;
}
currentModel = modelIndex;
currentDevice = deviceIndex;
currentNumThreads = numThreads;
return;
}
currentModel = modelIndex;
currentDevice = deviceIndex;
currentNumThreads = numThreads;
// Disable classifier while updating
if (classifier != null) {
classifier.close();
classifier = null;
}
// Disable classifier while updating
if (classifier != null) {
classifier.close();
classifier = null;
}
// Lookup names of parameters.
String model = modelStrings.get(modelIndex);
String device = deviceStrings.get(deviceIndex);
// Lookup names of parameters.
String model = modelStrings.get(modelIndex);
String device = deviceStrings.get(deviceIndex);
Log.i(TAG, "Changing model to " + model + " device " + device);
Log.i(TAG, "Changing model to " + model + " device " + device);
// Try to load model.
try {
if (model.equals(mobilenetV1Quant)) {
classifier = new ImageClassifierQuantizedMobileNet(getActivity());
} else if (model.equals(mobilenetV1Float)) {
classifier = new ImageClassifierFloatMobileNet(getActivity());
} else {
showToast("Failed to load model");
}
} catch (IOException e) {
Log.d(TAG, "Failed to load", e);
classifier = null;
}
// Try to load model.
try {
if (model.equals(mobilenetV1Quant)) {
classifier = new ImageClassifierQuantizedMobileNet(getActivity());
} else if (model.equals(mobilenetV1Float)) {
classifier = new ImageClassifierFloatMobileNet(getActivity());
} else {
showToast("Failed to load model");
}
} catch (IOException e) {
Log.d(TAG, "Failed to load", e);
classifier = null;
}
// Customize the interpreter to the type of device we want to use.
if (classifier == null) {
return;
}
classifier.setNumThreads(numThreads);
if (device.equals(cpu)) {
} else if (device.equals(gpu)) {
if (model.equals(mobilenetV1Quant)) {
showToast("gpu requires float model.");
classifier = null;
} else {
classifier.useGpu();
}
} else if (device.equals(nnApi)) {
classifier.useNNAPI();
}
});
// Customize the interpreter to the type of device we want to use.
if (classifier == null) {
return;
}
classifier.setNumThreads(numThreads);
if (device.equals(cpu)) {
} else if (device.equals(gpu)) {
classifier.useGpu();
} else if (device.equals(nnApi)) {
classifier.useNNAPI();
}
});
}
/** Connect the buttons to their event handler. */

5
tensorflow/lite/java/demo/app/src/main/java/com/example/android/tflitecamerademo/ImageClassifier.java
View File

@ -172,7 +172,10 @@ public abstract class ImageClassifier {
public void useGpu() {
if (gpuDelegate == null) {
gpuDelegate = new GpuDelegate();
GpuDelegate.Options options = new GpuDelegate.Options();
options.setQuantizedModelsAllowed(true);
gpuDelegate = new GpuDelegate(options);
tfliteOptions.addDelegate(gpuDelegate);
recreateInterpreter();
}