android-35/android/adservices/ondevicepersonalization/InferenceInputParcel.java - platform/prebuilts/fullsdk/sources - Git at Google

 /*
  * Copyright (C) 2024 The Android Open Source 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 android.adservices.ondevicepersonalization;

 import android.annotation.IntRange;
 import android.annotation.NonNull;
 import android.os.Parcelable;

 import com.android.ondevicepersonalization.internal.util.AnnotationValidations;
 import com.android.ondevicepersonalization.internal.util.ByteArrayParceledListSlice;
 import com.android.ondevicepersonalization.internal.util.DataClass;

 /**
  * Parcelable version of {@link InferenceInput}.
  *
  * @hide
  */
 @DataClass(genAidl = false, genBuilder = false)
 public class InferenceInputParcel implements Parcelable {
     /**
      * The location of TFLite model. The model is usually store in REMOTE_DATA or LOCAL_DATA table.
      */
     @NonNull private ModelId mModelId;

     /** The delegate to run model inference. If not specified, CPU delegate is used by default. */
     private @InferenceInput.Params.Delegate int mDelegate;

     /**
      * The number of threads available to the interpreter. Only set and take effective when input
      * tensors are on CPU. Setting cpuNumThread to 0 has the effect to disable multithreading, which
      * is equivalent to setting cpuNumThread to 1. If set to the value -1, the number of threads
      * used will be implementation-defined and platform-dependent.
      */
     private @IntRange(from = 1) int mCpuNumThread;

     /** An array of input data. The inputs should be in the same order as inputs of the model. */
     @NonNull private ByteArrayParceledListSlice mInputData;

     /**
      * The number of input examples. Adopter can set this field to run batching inference. The batch
      * size is 1 by default.
      */
     private int mBatchSize;

     private @InferenceInput.Params.ModelType int mModelType =
             InferenceInput.Params.MODEL_TYPE_TENSORFLOW_LITE;

     /**
      * The empty InferenceOutput representing the expected output structure. For TFLite, the
      * inference code will verify whether this expected output structure matches model output
      * signature.
      */
     @NonNull private InferenceOutputParcel mExpectedOutputStructure;

     /** @hide */
     public InferenceInputParcel(@NonNull InferenceInput value) {
         this(
                 new ModelId.Builder()
                         .setTableId(value.getParams().getKeyValueStore().getTableId())
                         .setKey(value.getParams().getModelKey())
                         .build(),
                 value.getParams().getDelegateType(),
                 value.getParams().getRecommendedNumThreads(),
                 ByteArrayParceledListSlice.create(value.getInputData()),
                 value.getBatchSize(),
                 value.getParams().getModelType(),
                 new InferenceOutputParcel(value.getExpectedOutputStructure()));
     }

     // Code below generated by codegen v1.0.23.
     //
     // DO NOT MODIFY!
     // CHECKSTYLE:OFF Generated code
     //
     // To regenerate run:
     // $ codegen
     // $ANDROID_BUILD_TOP/packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInputParcel.java
     //
     // To exclude the generated code from IntelliJ auto-formatting enable (one-time):
     //   Settings > Editor > Code Style > Formatter Control
     // @formatter:off

     /**
      * Creates a new InferenceInputParcel.
      *
      * @param modelId The location of TFLite model. The model is usually store in REMOTE_DATA or
      *     LOCAL_DATA table.
      * @param delegate The delegate to run model inference. If not specified, CPU delegate is used
      *     by default.
      * @param cpuNumThread The number of threads available to the interpreter. Only set and take
      *     effective when input tensors are on CPU. Setting cpuNumThread to 0 has the effect to
      *     disable multithreading, which is equivalent to setting cpuNumThread to 1. If set to the
      *     value -1, the number of threads used will be implementation-defined and
      *     platform-dependent.
      * @param inputData An array of input data. The inputs should be in the same order as inputs of
      *     the model.
      * @param batchSize The number of input examples. Adopter can set this field to run batching
      *     inference. The batch size is 1 by default.
      * @param expectedOutputStructure The empty InferenceOutput representing the expected output
      *     structure. For TFLite, the inference code will verify whether this expected output
      *     structure matches model output signature.
      */
     @DataClass.Generated.Member
     public InferenceInputParcel(
             @NonNull ModelId modelId,
             @InferenceInput.Params.Delegate int delegate,
             @IntRange(from = 1) int cpuNumThread,
             @NonNull ByteArrayParceledListSlice inputData,
             int batchSize,
             @InferenceInput.Params.ModelType int modelType,
             @NonNull InferenceOutputParcel expectedOutputStructure) {
         this.mModelId = modelId;
         AnnotationValidations.validate(NonNull.class, null, mModelId);
         this.mDelegate = delegate;
         AnnotationValidations.validate(InferenceInput.Params.Delegate.class, null, mDelegate);
         this.mCpuNumThread = cpuNumThread;
         AnnotationValidations.validate(IntRange.class, null, mCpuNumThread, "from", 1);
         this.mInputData = inputData;
         AnnotationValidations.validate(NonNull.class, null, mInputData);
         this.mBatchSize = batchSize;
         this.mModelType = modelType;
         AnnotationValidations.validate(InferenceInput.Params.ModelType.class, null, mModelType);
         this.mExpectedOutputStructure = expectedOutputStructure;
         AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure);

         // onConstructed(); // You can define this method to get a callback
     }

     /**
      * The location of TFLite model. The model is usually store in REMOTE_DATA or LOCAL_DATA table.
      */
     @DataClass.Generated.Member
     public @NonNull ModelId getModelId() {
         return mModelId;
     }

     /** The delegate to run model inference. If not specified, CPU delegate is used by default. */
     @DataClass.Generated.Member
     public @InferenceInput.Params.Delegate int getDelegate() {
         return mDelegate;
     }

     /**
      * The number of threads available to the interpreter. Only set and take effective when input
      * tensors are on CPU. Setting cpuNumThread to 0 has the effect to disable multithreading, which
      * is equivalent to setting cpuNumThread to 1. If set to the value -1, the number of threads
      * used will be implementation-defined and platform-dependent.
      */
     @DataClass.Generated.Member
     public @IntRange(from = 1) int getCpuNumThread() {
         return mCpuNumThread;
     }

     /** An array of input data. The inputs should be in the same order as inputs of the model. */
     @DataClass.Generated.Member
     public @NonNull ByteArrayParceledListSlice getInputData() {
         return mInputData;
     }

     /**
      * The number of input examples. Adopter can set this field to run batching inference. The batch
      * size is 1 by default.
      */
     @DataClass.Generated.Member
     public int getBatchSize() {
         return mBatchSize;
     }

     @DataClass.Generated.Member
     public @InferenceInput.Params.ModelType int getModelType() {
         return mModelType;
     }

     /**
      * The empty InferenceOutput representing the expected output structure. For TFLite, the
      * inference code will verify whether this expected output structure matches model output
      * signature.
      */
     @DataClass.Generated.Member
     public @NonNull InferenceOutputParcel getExpectedOutputStructure() {
         return mExpectedOutputStructure;
     }

     @Override
     @DataClass.Generated.Member
     public void writeToParcel(@NonNull android.os.Parcel dest, int flags) {
         // You can override field parcelling by defining methods like:
         // void parcelFieldName(Parcel dest, int flags) { ... }

         dest.writeTypedObject(mModelId, flags);
         dest.writeInt(mDelegate);
         dest.writeInt(mCpuNumThread);
         dest.writeTypedObject(mInputData, flags);
         dest.writeInt(mBatchSize);
         dest.writeInt(mModelType);
         dest.writeTypedObject(mExpectedOutputStructure, flags);
     }

     @Override
     @DataClass.Generated.Member
     public int describeContents() {
         return 0;
     }

     /** @hide */
     @SuppressWarnings({"unchecked", "RedundantCast"})
     @DataClass.Generated.Member
     protected InferenceInputParcel(@NonNull android.os.Parcel in) {
         // You can override field unparcelling by defining methods like:
         // static FieldType unparcelFieldName(Parcel in) { ... }

         ModelId modelId = (ModelId) in.readTypedObject(ModelId.CREATOR);
         int delegate = in.readInt();
         int cpuNumThread = in.readInt();
         ByteArrayParceledListSlice inputData =
                 (ByteArrayParceledListSlice) in.readTypedObject(ByteArrayParceledListSlice.CREATOR);
         int batchSize = in.readInt();
         int modelType = in.readInt();
         InferenceOutputParcel expectedOutputStructure =
                 (InferenceOutputParcel) in.readTypedObject(InferenceOutputParcel.CREATOR);

         this.mModelId = modelId;
         AnnotationValidations.validate(NonNull.class, null, mModelId);
         this.mDelegate = delegate;
         AnnotationValidations.validate(InferenceInput.Params.Delegate.class, null, mDelegate);
         this.mCpuNumThread = cpuNumThread;
         AnnotationValidations.validate(IntRange.class, null, mCpuNumThread, "from", 1);
         this.mInputData = inputData;
         AnnotationValidations.validate(NonNull.class, null, mInputData);
         this.mBatchSize = batchSize;
         this.mModelType = modelType;
         AnnotationValidations.validate(InferenceInput.Params.ModelType.class, null, mModelType);
         this.mExpectedOutputStructure = expectedOutputStructure;
         AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure);

         // onConstructed(); // You can define this method to get a callback
     }

     @DataClass.Generated.Member
     public static final @NonNull Parcelable.Creator<InferenceInputParcel> CREATOR =
             new Parcelable.Creator<InferenceInputParcel>() {
                 @Override
                 public InferenceInputParcel[] newArray(int size) {
                     return new InferenceInputParcel[size];
                 }

                 @Override
                 public InferenceInputParcel createFromParcel(@NonNull android.os.Parcel in) {
                     return new InferenceInputParcel(in);
                 }
             };

     @DataClass.Generated(
             time = 1708579683131L,
             codegenVersion = "1.0.23",
             sourceFile =
                     "packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInputParcel.java",
             inputSignatures =
                     "private @android.annotation.NonNull android.adservices.ondevicepersonalization.ModelId mModelId\nprivate @android.adservices.ondevicepersonalization.InferenceInput.Params.Delegate int mDelegate\nprivate @android.annotation.IntRange int mCpuNumThread\nprivate @android.annotation.NonNull com.android.ondevicepersonalization.internal.util.ByteArrayParceledListSlice mInputData\nprivate  int mBatchSize\nprivate @android.adservices.ondevicepersonalization.InferenceInput.Params.ModelType int mModelType\nprivate @android.annotation.NonNull android.adservices.ondevicepersonalization.InferenceOutputParcel mExpectedOutputStructure\nclass InferenceInputParcel extends java.lang.Object implements [android.os.Parcelable]\[email protected](genAidl=false, genBuilder=false)")
     @Deprecated
     private void __metadata() {}

     // @formatter:on
     // End of generated code

 }
	/*
	* Copyright (C) 2024 The Android Open Source 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 android.adservices.ondevicepersonalization;

	import android.annotation.IntRange;
	import android.annotation.NonNull;
	import android.os.Parcelable;

	import com.android.ondevicepersonalization.internal.util.AnnotationValidations;
	import com.android.ondevicepersonalization.internal.util.ByteArrayParceledListSlice;
	import com.android.ondevicepersonalization.internal.util.DataClass;

	/**
	* Parcelable version of {@link InferenceInput}.
	*
	* @hide
	*/
	@DataClass(genAidl = false, genBuilder = false)
	public class InferenceInputParcel implements Parcelable {
	/**
	* The location of TFLite model. The model is usually store in REMOTE_DATA or LOCAL_DATA table.
	*/
	@NonNull private ModelId mModelId;

	/** The delegate to run model inference. If not specified, CPU delegate is used by default. */
	private @InferenceInput.Params.Delegate int mDelegate;

	/**
	* The number of threads available to the interpreter. Only set and take effective when input
	* tensors are on CPU. Setting cpuNumThread to 0 has the effect to disable multithreading, which
	* is equivalent to setting cpuNumThread to 1. If set to the value -1, the number of threads
	* used will be implementation-defined and platform-dependent.
	*/
	private @IntRange(from = 1) int mCpuNumThread;

	/** An array of input data. The inputs should be in the same order as inputs of the model. */
	@NonNull private ByteArrayParceledListSlice mInputData;

	/**
	* The number of input examples. Adopter can set this field to run batching inference. The batch
	* size is 1 by default.
	*/
	private int mBatchSize;

	private @InferenceInput.Params.ModelType int mModelType =
	InferenceInput.Params.MODEL_TYPE_TENSORFLOW_LITE;

	/**
	* The empty InferenceOutput representing the expected output structure. For TFLite, the
	* inference code will verify whether this expected output structure matches model output
	* signature.
	*/
	@NonNull private InferenceOutputParcel mExpectedOutputStructure;

	/** @hide */
	public InferenceInputParcel(@NonNull InferenceInput value) {
	this(
	new ModelId.Builder()
	.setTableId(value.getParams().getKeyValueStore().getTableId())
	.setKey(value.getParams().getModelKey())
	.build(),
	value.getParams().getDelegateType(),
	value.getParams().getRecommendedNumThreads(),
	ByteArrayParceledListSlice.create(value.getInputData()),
	value.getBatchSize(),
	value.getParams().getModelType(),
	new InferenceOutputParcel(value.getExpectedOutputStructure()));
	}

	// Code below generated by codegen v1.0.23.
	//
	// DO NOT MODIFY!
	// CHECKSTYLE:OFF Generated code
	//
	// To regenerate run:
	// $ codegen
	// $ANDROID_BUILD_TOP/packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInputParcel.java
	//
	// To exclude the generated code from IntelliJ auto-formatting enable (one-time):
	// Settings > Editor > Code Style > Formatter Control
	// @formatter:off

	/**
	* Creates a new InferenceInputParcel.
	*
	* @param modelId The location of TFLite model. The model is usually store in REMOTE_DATA or
	* LOCAL_DATA table.
	* @param delegate The delegate to run model inference. If not specified, CPU delegate is used
	* by default.
	* @param cpuNumThread The number of threads available to the interpreter. Only set and take
	* effective when input tensors are on CPU. Setting cpuNumThread to 0 has the effect to
	* disable multithreading, which is equivalent to setting cpuNumThread to 1. If set to the
	* value -1, the number of threads used will be implementation-defined and
	* platform-dependent.
	* @param inputData An array of input data. The inputs should be in the same order as inputs of
	* the model.
	* @param batchSize The number of input examples. Adopter can set this field to run batching
	* inference. The batch size is 1 by default.
	* @param expectedOutputStructure The empty InferenceOutput representing the expected output
	* structure. For TFLite, the inference code will verify whether this expected output
	* structure matches model output signature.
	*/
	@DataClass.Generated.Member
	public InferenceInputParcel(
	@NonNull ModelId modelId,
	@InferenceInput.Params.Delegate int delegate,
	@IntRange(from = 1) int cpuNumThread,
	@NonNull ByteArrayParceledListSlice inputData,
	int batchSize,
	@InferenceInput.Params.ModelType int modelType,
	@NonNull InferenceOutputParcel expectedOutputStructure) {
	this.mModelId = modelId;
	AnnotationValidations.validate(NonNull.class, null, mModelId);
	this.mDelegate = delegate;
	AnnotationValidations.validate(InferenceInput.Params.Delegate.class, null, mDelegate);
	this.mCpuNumThread = cpuNumThread;
	AnnotationValidations.validate(IntRange.class, null, mCpuNumThread, "from", 1);
	this.mInputData = inputData;
	AnnotationValidations.validate(NonNull.class, null, mInputData);
	this.mBatchSize = batchSize;
	this.mModelType = modelType;
	AnnotationValidations.validate(InferenceInput.Params.ModelType.class, null, mModelType);
	this.mExpectedOutputStructure = expectedOutputStructure;
	AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure);

	// onConstructed(); // You can define this method to get a callback
	}

	/**
	* The location of TFLite model. The model is usually store in REMOTE_DATA or LOCAL_DATA table.
	*/
	@DataClass.Generated.Member
	public @NonNull ModelId getModelId() {
	return mModelId;
	}

	/** The delegate to run model inference. If not specified, CPU delegate is used by default. */
	@DataClass.Generated.Member
	public @InferenceInput.Params.Delegate int getDelegate() {
	return mDelegate;
	}

	/**
	* The number of threads available to the interpreter. Only set and take effective when input
	* tensors are on CPU. Setting cpuNumThread to 0 has the effect to disable multithreading, which
	* is equivalent to setting cpuNumThread to 1. If set to the value -1, the number of threads
	* used will be implementation-defined and platform-dependent.
	*/
	@DataClass.Generated.Member
	public @IntRange(from = 1) int getCpuNumThread() {
	return mCpuNumThread;
	}

	/** An array of input data. The inputs should be in the same order as inputs of the model. */
	@DataClass.Generated.Member
	public @NonNull ByteArrayParceledListSlice getInputData() {
	return mInputData;
	}

	/**
	* The number of input examples. Adopter can set this field to run batching inference. The batch
	* size is 1 by default.
	*/
	@DataClass.Generated.Member
	public int getBatchSize() {
	return mBatchSize;
	}

	@DataClass.Generated.Member
	public @InferenceInput.Params.ModelType int getModelType() {
	return mModelType;
	}

	/**
	* The empty InferenceOutput representing the expected output structure. For TFLite, the
	* inference code will verify whether this expected output structure matches model output
	* signature.
	*/
	@DataClass.Generated.Member
	public @NonNull InferenceOutputParcel getExpectedOutputStructure() {
	return mExpectedOutputStructure;
	}

	@Override
	@DataClass.Generated.Member
	public void writeToParcel(@NonNull android.os.Parcel dest, int flags) {
	// You can override field parcelling by defining methods like:
	// void parcelFieldName(Parcel dest, int flags) { ... }

	dest.writeTypedObject(mModelId, flags);
	dest.writeInt(mDelegate);
	dest.writeInt(mCpuNumThread);
	dest.writeTypedObject(mInputData, flags);
	dest.writeInt(mBatchSize);
	dest.writeInt(mModelType);
	dest.writeTypedObject(mExpectedOutputStructure, flags);
	}

	@Override
	@DataClass.Generated.Member
	public int describeContents() {
	return 0;
	}

	/** @hide */
	@SuppressWarnings({"unchecked", "RedundantCast"})
	@DataClass.Generated.Member
	protected InferenceInputParcel(@NonNull android.os.Parcel in) {
	// You can override field unparcelling by defining methods like:
	// static FieldType unparcelFieldName(Parcel in) { ... }

	ModelId modelId = (ModelId) in.readTypedObject(ModelId.CREATOR);
	int delegate = in.readInt();
	int cpuNumThread = in.readInt();
	ByteArrayParceledListSlice inputData =
	(ByteArrayParceledListSlice) in.readTypedObject(ByteArrayParceledListSlice.CREATOR);
	int batchSize = in.readInt();
	int modelType = in.readInt();
	InferenceOutputParcel expectedOutputStructure =
	(InferenceOutputParcel) in.readTypedObject(InferenceOutputParcel.CREATOR);

	this.mModelId = modelId;
	AnnotationValidations.validate(NonNull.class, null, mModelId);
	this.mDelegate = delegate;
	AnnotationValidations.validate(InferenceInput.Params.Delegate.class, null, mDelegate);
	this.mCpuNumThread = cpuNumThread;
	AnnotationValidations.validate(IntRange.class, null, mCpuNumThread, "from", 1);
	this.mInputData = inputData;
	AnnotationValidations.validate(NonNull.class, null, mInputData);
	this.mBatchSize = batchSize;
	this.mModelType = modelType;
	AnnotationValidations.validate(InferenceInput.Params.ModelType.class, null, mModelType);
	this.mExpectedOutputStructure = expectedOutputStructure;
	AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure);

	// onConstructed(); // You can define this method to get a callback
	}

	@DataClass.Generated.Member
	public static final @NonNull Parcelable.Creator<InferenceInputParcel> CREATOR =
	new Parcelable.Creator<InferenceInputParcel>() {
	@Override
	public InferenceInputParcel[] newArray(int size) {
	return new InferenceInputParcel[size];
	}

	@Override
	public InferenceInputParcel createFromParcel(@NonNull android.os.Parcel in) {
	return new InferenceInputParcel(in);
	}
	};

	@DataClass.Generated(
	time = 1708579683131L,
	codegenVersion = "1.0.23",
	sourceFile =
	"packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInputParcel.java",
	inputSignatures =
	"private @android.annotation.NonNull android.adservices.ondevicepersonalization.ModelId mModelId\nprivate @android.adservices.ondevicepersonalization.InferenceInput.Params.Delegate int mDelegate\nprivate @android.annotation.IntRange int mCpuNumThread\nprivate @android.annotation.NonNull com.android.ondevicepersonalization.internal.util.ByteArrayParceledListSlice mInputData\nprivate int mBatchSize\nprivate @android.adservices.ondevicepersonalization.InferenceInput.Params.ModelType int mModelType\nprivate @android.annotation.NonNull android.adservices.ondevicepersonalization.InferenceOutputParcel mExpectedOutputStructure\nclass InferenceInputParcel extends java.lang.Object implements [android.os.Parcelable]\[email protected](genAidl=false, genBuilder=false)")
	@Deprecated
	private void __metadata() {}

	// @formatter:on
	// End of generated code

	}