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/*
* Copyright (C) 2021 The Proton AOSP Project
*
* Licensed under the Apache License, Version 2.0 (the "License");
* you may not use this file except in compliance with the License.
* You may obtain a copy of the License at
*
* http://www.apache.org/licenses/LICENSE-2.0
*
* Unless required by applicable law or agreed to in writing, software
* distributed under the License is distributed on an "AS IS" BASIS,
* WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
* See the License for the specific language governing permissions and
* limitations under the License.
*/
package org.protonaosp.systemui
import android.content.res.AssetManager
import com.android.systemui.navigationbar.gestural.BackGestureTfClassifierProvider
import org.tensorflow.lite.Interpreter
import java.nio.ByteBuffer
import java.nio.ByteOrder
class CustomBackGestureTfClassifierProvider(
am: AssetManager,
private val modelName: String
) : BackGestureTfClassifierProvider() {
// Don't bother to set up a MappedByteBuffer for 512 KiB of data
private val interpreter = am.open("$modelName.tflite").use {
val data = it.readBytes()
Interpreter(ByteBuffer.allocateDirect(data.size).apply {
order(ByteOrder.nativeOrder())
put(data)
})
}
override fun loadVocab(am: AssetManager) = am.open("$modelName.vocab").use { ins ->
String(ins.readBytes()).lines().asSequence()
.withIndex()
.map { it.value to it.index }
.toMap()
}
override fun predict(featuresVector: Array<Any>): Float {
val confidenceTensor = floatArrayOf(0f)
val tensors = mutableMapOf(0 to arrayOf(confidenceTensor))
interpreter.runForMultipleInputsOutputs(featuresVector, tensors as Map<Int, Any>)
return confidenceTensor[0]
}
override fun release() = interpreter.close()
override fun isActive() = true
}
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