| /* |
| * 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.FlaggedApi; |
| import android.annotation.IntDef; |
| import android.annotation.IntRange; |
| import android.annotation.NonNull; |
| import android.annotation.SuppressLint; |
| |
| import com.android.adservices.ondevicepersonalization.flags.Flags; |
| import com.android.ondevicepersonalization.internal.util.AnnotationValidations; |
| import com.android.ondevicepersonalization.internal.util.DataClass; |
| |
| import java.lang.annotation.Retention; |
| import java.lang.annotation.RetentionPolicy; |
| |
| /** |
| * Contains all the information needed for a run of model inference. The input of {@link |
| * ModelManager#run}. |
| */ |
| @FlaggedApi(Flags.FLAG_ON_DEVICE_PERSONALIZATION_APIS_ENABLED) |
| @DataClass(genBuilder = true, genEqualsHashCode = true) |
| public final class InferenceInput { |
| /** The configuration that controls runtime interpreter behavior. */ |
| @NonNull private Params mParams; |
| |
| /** |
| * An array of input data. The inputs should be in the same order as inputs of the model. |
| * |
| * <p>For example, if a model takes multiple inputs: |
| * |
| * <pre>{@code |
| * String[] input0 = {"foo", "bar"}; // string tensor shape is [2]. |
| * int[] input1 = new int[]{3, 2, 1}; // int tensor shape is [3]. |
| * Object[] inputData = {input0, input1, ...}; |
| * }</pre> |
| * |
| * For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: |
| * https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 |
| */ |
| @NonNull private Object[] mInputData; |
| |
| /** |
| * The number of input examples. Adopter can set this field to run batching inference. The batch |
| * size is 1 by default. The batch size should match the input data size. |
| */ |
| private int mBatchSize = 1; |
| |
| /** |
| * The empty InferenceOutput representing the expected output structure. For TFLite, the |
| * inference code will verify whether this expected output structure matches model output |
| * signature. |
| * |
| * <p>If a model produce string tensors: |
| * |
| * <pre>{@code |
| * String[] output = new String[3][2]; // Output tensor shape is [3, 2]. |
| * HashMap<Integer, Object> outputs = new HashMap<>(); |
| * outputs.put(0, output); |
| * expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build(); |
| * }</pre> |
| */ |
| @NonNull private InferenceOutput mExpectedOutputStructure; |
| |
| @DataClass(genBuilder = true, genHiddenConstructor = true, genEqualsHashCode = true) |
| public static class Params { |
| /** |
| * A {@link KeyValueStore} where pre-trained model is stored. Only supports TFLite model |
| * now. |
| */ |
| @NonNull private KeyValueStore mKeyValueStore; |
| |
| /** |
| * The key of the table where the corresponding value stores a pre-trained model. Only |
| * supports TFLite model now. |
| */ |
| @NonNull private String mModelKey; |
| |
| /** The model inference will run on CPU. */ |
| public static final int DELEGATE_CPU = 1; |
| |
| /** |
| * The delegate to run model inference. |
| * |
| * @hide |
| */ |
| @IntDef( |
| prefix = "DELEGATE_", |
| value = {DELEGATE_CPU}) |
| @Retention(RetentionPolicy.SOURCE) |
| public @interface Delegate {} |
| |
| /** |
| * The delegate to run model inference. If not set, the default value is {@link |
| * #DELEGATE_CPU}. |
| */ |
| private @Delegate int mDelegateType = DELEGATE_CPU; |
| |
| /** The model is a tensorflow lite model. */ |
| public static final int MODEL_TYPE_TENSORFLOW_LITE = 1; |
| |
| /** |
| * The type of the model. |
| * |
| * @hide |
| */ |
| @IntDef( |
| prefix = "MODEL_TYPE", |
| value = {MODEL_TYPE_TENSORFLOW_LITE}) |
| @Retention(RetentionPolicy.SOURCE) |
| public @interface ModelType {} |
| |
| /** |
| * The type of the pre-trained model. If not set, the default value is {@link |
| * #MODEL_TYPE_TENSORFLOW_LITE} . Only supports {@link #MODEL_TYPE_TENSORFLOW_LITE} for now. |
| */ |
| private @ModelType int mModelType = MODEL_TYPE_TENSORFLOW_LITE; |
| |
| /** |
| * The number of threads used for intraop parallelism on CPU, must be positive number. |
| * Adopters can set this field based on model architecture. The actual thread number depends |
| * on system resources and other constraints. |
| */ |
| private @IntRange(from = 1) int mRecommendedNumThreads = 1; |
| |
| // 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/InferenceInput.java |
| // |
| // To exclude the generated code from IntelliJ auto-formatting enable (one-time): |
| // Settings > Editor > Code Style > Formatter Control |
| // @formatter:off |
| |
| /** |
| * Creates a new Params. |
| * |
| * @param keyValueStore A {@link KeyValueStore} where pre-trained model is stored. Only |
| * supports TFLite model now. |
| * @param modelKey The key of the table where the corresponding value stores a pre-trained |
| * model. Only supports TFLite model now. |
| * @param delegateType The delegate to run model inference. If not set, the default value is |
| * {@link #DELEGATE_CPU}. |
| * @param modelType The type of the pre-trained model. If not set, the default value is |
| * {@link #MODEL_TYPE_TENSORFLOW_LITE} . Only supports {@link |
| * #MODEL_TYPE_TENSORFLOW_LITE} for now. |
| * @param recommendedNumThreads The number of threads used for intraop parallelism on CPU, |
| * must be positive number. Adopters can set this field based on model architecture. The |
| * actual thread number depends on system resources and other constraints. |
| * @hide |
| */ |
| @DataClass.Generated.Member |
| public Params( |
| @NonNull KeyValueStore keyValueStore, |
| @NonNull String modelKey, |
| @Delegate int delegateType, |
| @ModelType int modelType, |
| @IntRange(from = 1) int recommendedNumThreads) { |
| this.mKeyValueStore = keyValueStore; |
| AnnotationValidations.validate(NonNull.class, null, mKeyValueStore); |
| this.mModelKey = modelKey; |
| AnnotationValidations.validate(NonNull.class, null, mModelKey); |
| this.mDelegateType = delegateType; |
| AnnotationValidations.validate(Delegate.class, null, mDelegateType); |
| this.mModelType = modelType; |
| AnnotationValidations.validate(ModelType.class, null, mModelType); |
| this.mRecommendedNumThreads = recommendedNumThreads; |
| AnnotationValidations.validate(IntRange.class, null, mRecommendedNumThreads, "from", 1); |
| |
| // onConstructed(); // You can define this method to get a callback |
| } |
| |
| /** |
| * A {@link KeyValueStore} where pre-trained model is stored. Only supports TFLite model |
| * now. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull KeyValueStore getKeyValueStore() { |
| return mKeyValueStore; |
| } |
| |
| /** |
| * The key of the table where the corresponding value stores a pre-trained model. Only |
| * supports TFLite model now. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull String getModelKey() { |
| return mModelKey; |
| } |
| |
| /** |
| * The delegate to run model inference. If not set, the default value is {@link |
| * #DELEGATE_CPU}. |
| */ |
| @DataClass.Generated.Member |
| public @Delegate int getDelegateType() { |
| return mDelegateType; |
| } |
| |
| /** |
| * The type of the pre-trained model. If not set, the default value is {@link |
| * #MODEL_TYPE_TENSORFLOW_LITE} . Only supports {@link #MODEL_TYPE_TENSORFLOW_LITE} for now. |
| */ |
| @DataClass.Generated.Member |
| public @ModelType int getModelType() { |
| return mModelType; |
| } |
| |
| /** |
| * The number of threads used for intraop parallelism on CPU, must be positive number. |
| * Adopters can set this field based on model architecture. The actual thread number depends |
| * on system resources and other constraints. |
| */ |
| @DataClass.Generated.Member |
| public @IntRange(from = 1) int getRecommendedNumThreads() { |
| return mRecommendedNumThreads; |
| } |
| |
| @Override |
| @DataClass.Generated.Member |
| public boolean equals(@android.annotation.Nullable Object o) { |
| // You can override field equality logic by defining either of the methods like: |
| // boolean fieldNameEquals(Params other) { ... } |
| // boolean fieldNameEquals(FieldType otherValue) { ... } |
| |
| if (this == o) return true; |
| if (o == null || getClass() != o.getClass()) return false; |
| @SuppressWarnings("unchecked") |
| Params that = (Params) o; |
| //noinspection PointlessBooleanExpression |
| return true |
| && java.util.Objects.equals(mKeyValueStore, that.mKeyValueStore) |
| && java.util.Objects.equals(mModelKey, that.mModelKey) |
| && mDelegateType == that.mDelegateType |
| && mModelType == that.mModelType |
| && mRecommendedNumThreads == that.mRecommendedNumThreads; |
| } |
| |
| @Override |
| @DataClass.Generated.Member |
| public int hashCode() { |
| // You can override field hashCode logic by defining methods like: |
| // int fieldNameHashCode() { ... } |
| |
| int _hash = 1; |
| _hash = 31 * _hash + java.util.Objects.hashCode(mKeyValueStore); |
| _hash = 31 * _hash + java.util.Objects.hashCode(mModelKey); |
| _hash = 31 * _hash + mDelegateType; |
| _hash = 31 * _hash + mModelType; |
| _hash = 31 * _hash + mRecommendedNumThreads; |
| return _hash; |
| } |
| |
| /** A builder for {@link Params} */ |
| @SuppressWarnings("WeakerAccess") |
| @DataClass.Generated.Member |
| public static final class Builder { |
| |
| private @NonNull KeyValueStore mKeyValueStore; |
| private @NonNull String mModelKey; |
| private @Delegate int mDelegateType; |
| private @ModelType int mModelType; |
| private @IntRange(from = 1) int mRecommendedNumThreads; |
| |
| private long mBuilderFieldsSet = 0L; |
| |
| /** |
| * Creates a new Builder. |
| * |
| * @param keyValueStore A {@link KeyValueStore} where pre-trained model is stored. Only |
| * supports TFLite model now. |
| * @param modelKey The key of the table where the corresponding value stores a |
| * pre-trained model. Only supports TFLite model now. |
| */ |
| public Builder(@NonNull KeyValueStore keyValueStore, @NonNull String modelKey) { |
| mKeyValueStore = keyValueStore; |
| AnnotationValidations.validate(NonNull.class, null, mKeyValueStore); |
| mModelKey = modelKey; |
| AnnotationValidations.validate(NonNull.class, null, mModelKey); |
| } |
| |
| /** |
| * A {@link KeyValueStore} where pre-trained model is stored. Only supports TFLite model |
| * now. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setKeyValueStore(@NonNull KeyValueStore value) { |
| mBuilderFieldsSet |= 0x1; |
| mKeyValueStore = value; |
| return this; |
| } |
| |
| /** |
| * The key of the table where the corresponding value stores a pre-trained model. Only |
| * supports TFLite model now. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setModelKey(@NonNull String value) { |
| mBuilderFieldsSet |= 0x2; |
| mModelKey = value; |
| return this; |
| } |
| |
| /** |
| * The delegate to run model inference. If not set, the default value is {@link |
| * #DELEGATE_CPU}. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setDelegateType(@Delegate int value) { |
| mBuilderFieldsSet |= 0x4; |
| mDelegateType = value; |
| return this; |
| } |
| |
| /** |
| * The type of the pre-trained model. If not set, the default value is {@link |
| * #MODEL_TYPE_TENSORFLOW_LITE} . Only supports {@link #MODEL_TYPE_TENSORFLOW_LITE} for |
| * now. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setModelType(@ModelType int value) { |
| mBuilderFieldsSet |= 0x8; |
| mModelType = value; |
| return this; |
| } |
| |
| /** |
| * The number of threads used for intraop parallelism on CPU, must be positive number. |
| * Adopters can set this field based on model architecture. The actual thread number |
| * depends on system resources and other constraints. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setRecommendedNumThreads(@IntRange(from = 1) int value) { |
| mBuilderFieldsSet |= 0x10; |
| mRecommendedNumThreads = value; |
| return this; |
| } |
| |
| /** Builds the instance. */ |
| public @NonNull Params build() { |
| mBuilderFieldsSet |= 0x20; // Mark builder used |
| |
| if ((mBuilderFieldsSet & 0x4) == 0) { |
| mDelegateType = DELEGATE_CPU; |
| } |
| if ((mBuilderFieldsSet & 0x8) == 0) { |
| mModelType = MODEL_TYPE_TENSORFLOW_LITE; |
| } |
| if ((mBuilderFieldsSet & 0x10) == 0) { |
| mRecommendedNumThreads = 1; |
| } |
| Params o = |
| new Params( |
| mKeyValueStore, |
| mModelKey, |
| mDelegateType, |
| mModelType, |
| mRecommendedNumThreads); |
| return o; |
| } |
| } |
| |
| @DataClass.Generated( |
| time = 1709250081597L, |
| codegenVersion = "1.0.23", |
| sourceFile = |
| "packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInput.java", |
| inputSignatures = |
| "private @android.annotation.NonNull android.adservices.ondevicepersonalization.KeyValueStore mKeyValueStore\nprivate @android.annotation.NonNull java.lang.String mModelKey\npublic static final int DELEGATE_CPU\nprivate @android.adservices.ondevicepersonalization.Params.Delegate int mDelegateType\npublic static final int MODEL_TYPE_TENSORFLOW_LITE\nprivate @android.adservices.ondevicepersonalization.Params.ModelType int mModelType\nprivate @android.annotation.IntRange int mRecommendedNumThreads\nclass Params extends java.lang.Object implements []\[email protected](genBuilder=true, genHiddenConstructor=true, genEqualsHashCode=true)") |
| @Deprecated |
| private void __metadata() {} |
| |
| // @formatter:on |
| // End of generated code |
| |
| } |
| |
| // 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/InferenceInput.java |
| // |
| // To exclude the generated code from IntelliJ auto-formatting enable (one-time): |
| // Settings > Editor > Code Style > Formatter Control |
| // @formatter:off |
| |
| @DataClass.Generated.Member |
| /* package-private */ InferenceInput( |
| @NonNull Params params, |
| @NonNull Object[] inputData, |
| int batchSize, |
| @NonNull InferenceOutput expectedOutputStructure) { |
| this.mParams = params; |
| AnnotationValidations.validate(NonNull.class, null, mParams); |
| this.mInputData = inputData; |
| AnnotationValidations.validate(NonNull.class, null, mInputData); |
| this.mBatchSize = batchSize; |
| this.mExpectedOutputStructure = expectedOutputStructure; |
| AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure); |
| |
| // onConstructed(); // You can define this method to get a callback |
| } |
| |
| /** The configuration that controls runtime interpreter behavior. */ |
| @DataClass.Generated.Member |
| public @NonNull Params getParams() { |
| return mParams; |
| } |
| |
| /** |
| * An array of input data. The inputs should be in the same order as inputs of the model. |
| * |
| * <p>For example, if a model takes multiple inputs: |
| * |
| * <pre>{@code |
| * String[] input0 = {"foo", "bar"}; // string tensor shape is [2]. |
| * int[] input1 = new int[]{3, 2, 1}; // int tensor shape is [3]. |
| * Object[] inputData = {input0, input1, ...}; |
| * }</pre> |
| * |
| * For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: |
| * https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 |
| */ |
| @SuppressLint("ArrayReturn") |
| @DataClass.Generated.Member |
| public @NonNull Object[] getInputData() { |
| return mInputData; |
| } |
| |
| /** |
| * The number of input examples. Adopter can set this field to run batching inference. The batch |
| * size is 1 by default. The batch size should match the input data size. |
| */ |
| @DataClass.Generated.Member |
| public int getBatchSize() { |
| return mBatchSize; |
| } |
| |
| /** |
| * The empty InferenceOutput representing the expected output structure. For TFLite, the |
| * inference code will verify whether this expected output structure matches model output |
| * signature. |
| * |
| * <p>If a model produce string tensors: |
| * |
| * <pre>{@code |
| * String[] output = new String[3][2]; // Output tensor shape is [3, 2]. |
| * HashMap<Integer, Object> outputs = new HashMap<>(); |
| * outputs.put(0, output); |
| * expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build(); |
| * }</pre> |
| */ |
| @DataClass.Generated.Member |
| public @NonNull InferenceOutput getExpectedOutputStructure() { |
| return mExpectedOutputStructure; |
| } |
| |
| @Override |
| @DataClass.Generated.Member |
| public boolean equals(@android.annotation.Nullable Object o) { |
| // You can override field equality logic by defining either of the methods like: |
| // boolean fieldNameEquals(InferenceInput other) { ... } |
| // boolean fieldNameEquals(FieldType otherValue) { ... } |
| |
| if (this == o) return true; |
| if (o == null || getClass() != o.getClass()) return false; |
| @SuppressWarnings("unchecked") |
| InferenceInput that = (InferenceInput) o; |
| //noinspection PointlessBooleanExpression |
| return true |
| && java.util.Objects.equals(mParams, that.mParams) |
| && java.util.Arrays.equals(mInputData, that.mInputData) |
| && mBatchSize == that.mBatchSize |
| && java.util.Objects.equals( |
| mExpectedOutputStructure, that.mExpectedOutputStructure); |
| } |
| |
| @Override |
| @DataClass.Generated.Member |
| public int hashCode() { |
| // You can override field hashCode logic by defining methods like: |
| // int fieldNameHashCode() { ... } |
| |
| int _hash = 1; |
| _hash = 31 * _hash + java.util.Objects.hashCode(mParams); |
| _hash = 31 * _hash + java.util.Arrays.hashCode(mInputData); |
| _hash = 31 * _hash + mBatchSize; |
| _hash = 31 * _hash + java.util.Objects.hashCode(mExpectedOutputStructure); |
| return _hash; |
| } |
| |
| /** A builder for {@link InferenceInput} */ |
| @SuppressWarnings("WeakerAccess") |
| @DataClass.Generated.Member |
| public static final class Builder { |
| |
| private @NonNull Params mParams; |
| private @NonNull Object[] mInputData; |
| private int mBatchSize; |
| private @NonNull InferenceOutput mExpectedOutputStructure; |
| |
| private long mBuilderFieldsSet = 0L; |
| |
| /** |
| * Creates a new Builder. |
| * |
| * @param params The configuration that controls runtime interpreter behavior. |
| * @param inputData An array of input data. The inputs should be in the same order as inputs |
| * of the model. |
| * <p>For example, if a model takes multiple inputs: |
| * <pre>{@code |
| * String[] input0 = {"foo", "bar"}; // string tensor shape is [2]. |
| * int[] input1 = new int[]{3, 2, 1}; // int tensor shape is [3]. |
| * Object[] inputData = {input0, input1, ...}; |
| * |
| * }</pre> |
| * For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: |
| * https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 |
| * @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. |
| * <p>If a model produce string tensors: |
| * <pre>{@code |
| * String[] output = new String[3][2]; // Output tensor shape is [3, 2]. |
| * HashMap<Integer, Object> outputs = new HashMap<>(); |
| * outputs.put(0, output); |
| * expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build(); |
| * |
| * }</pre> |
| */ |
| public Builder( |
| @NonNull Params params, |
| @SuppressLint("ArrayReturn") @NonNull Object[] inputData, |
| @NonNull InferenceOutput expectedOutputStructure) { |
| mParams = params; |
| AnnotationValidations.validate(NonNull.class, null, mParams); |
| mInputData = inputData; |
| AnnotationValidations.validate(NonNull.class, null, mInputData); |
| mExpectedOutputStructure = expectedOutputStructure; |
| AnnotationValidations.validate(NonNull.class, null, mExpectedOutputStructure); |
| } |
| |
| /** The configuration that controls runtime interpreter behavior. */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setParams(@NonNull Params value) { |
| mBuilderFieldsSet |= 0x1; |
| mParams = value; |
| return this; |
| } |
| |
| /** |
| * An array of input data. The inputs should be in the same order as inputs of the model. |
| * |
| * <p>For example, if a model takes multiple inputs: |
| * |
| * <pre>{@code |
| * String[] input0 = {"foo", "bar"}; // string tensor shape is [2]. |
| * int[] input1 = new int[]{3, 2, 1}; // int tensor shape is [3]. |
| * Object[] inputData = {input0, input1, ...}; |
| * }</pre> |
| * |
| * For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: |
| * https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setInputData(@NonNull Object... value) { |
| mBuilderFieldsSet |= 0x2; |
| mInputData = value; |
| return this; |
| } |
| |
| /** |
| * The number of input examples. Adopter can set this field to run batching inference. The |
| * batch size is 1 by default. The batch size should match the input data size. |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setBatchSize(int value) { |
| mBuilderFieldsSet |= 0x4; |
| mBatchSize = value; |
| return this; |
| } |
| |
| /** |
| * The empty InferenceOutput representing the expected output structure. For TFLite, the |
| * inference code will verify whether this expected output structure matches model output |
| * signature. |
| * |
| * <p>If a model produce string tensors: |
| * |
| * <pre>{@code |
| * String[] output = new String[3][2]; // Output tensor shape is [3, 2]. |
| * HashMap<Integer, Object> outputs = new HashMap<>(); |
| * outputs.put(0, output); |
| * expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build(); |
| * }</pre> |
| */ |
| @DataClass.Generated.Member |
| public @NonNull Builder setExpectedOutputStructure(@NonNull InferenceOutput value) { |
| mBuilderFieldsSet |= 0x8; |
| mExpectedOutputStructure = value; |
| return this; |
| } |
| |
| /** Builds the instance. */ |
| public @NonNull InferenceInput build() { |
| mBuilderFieldsSet |= 0x10; // Mark builder used |
| |
| if ((mBuilderFieldsSet & 0x4) == 0) { |
| mBatchSize = 1; |
| } |
| InferenceInput o = |
| new InferenceInput(mParams, mInputData, mBatchSize, mExpectedOutputStructure); |
| return o; |
| } |
| } |
| |
| @DataClass.Generated( |
| time = 1709250081618L, |
| codegenVersion = "1.0.23", |
| sourceFile = |
| "packages/modules/OnDevicePersonalization/framework/java/android/adservices/ondevicepersonalization/InferenceInput.java", |
| inputSignatures = |
| "private @android.annotation.NonNull android.adservices.ondevicepersonalization.Params mParams\nprivate @android.annotation.NonNull java.lang.Object[] mInputData\nprivate int mBatchSize\nprivate @android.annotation.NonNull android.adservices.ondevicepersonalization.InferenceOutput mExpectedOutputStructure\nclass InferenceInput extends java.lang.Object implements []\[email protected](genBuilder=true, genEqualsHashCode=true)") |
| @Deprecated |
| private void __metadata() {} |
| |
| // @formatter:on |
| // End of generated code |
| |
| } |