Builder

Kotlin |Java

class Builder

kotlin.Any
↳	android.adservices.ondevicepersonalization.InferenceInput.Builder

A builder for InferenceInput

Summary

Public constructors
`Builder(params: InferenceInput.Params, inputData: Array<Any!>, expectedOutputStructure: InferenceOutput)` Creates a new Builder.

Public methods
InferenceInput	`build()` Builds the instance.
InferenceInput.Builder	`setBatchSize(value: Int)` The number of input examples.
InferenceInput.Builder	`setExpectedOutputStructure(value: InferenceOutput)` The empty InferenceOutput representing the expected output structure.
InferenceInput.Builder	`setInputData(vararg value: Any!)` An array of input data.
InferenceInput.Builder	`setParams(value: InferenceInput.Params)` The configuration that controls runtime interpreter behavior.

Public constructors

Builder

Added in API level VanillaIceCream

Builder(
    params: InferenceInput.Params, 
    inputData: Array<Any!>, 
    expectedOutputStructure: InferenceOutput)

Creates a new Builder.

Parameters

params InferenceInput.Params: The configuration that controls runtime interpreter behavior. This value cannot be null.

Parameters
`params`	InferenceInput.Params: The configuration that controls runtime interpreter behavior. This value cannot be `null`.
`inputData`	Array<Any!>: An array of input data. The inputs should be in the same order as inputs of the model. For example, if a model takes multiple inputs: <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, ...}; </code> For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 This value cannot be `null`.
`expectedOutputStructure`	InferenceOutput: The empty InferenceOutput representing the expected output structure. For TFLite, the inference code will verify whether this expected output structure matches model output signature. If a model produce string tensors: <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(); </code> This value cannot be `null`.

inputData

Array<Any!>: An array of input data. The inputs should be in the same order as inputs of the model.

For example, if a model takes multiple inputs:

<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, ...};
 
  </code>

For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9 This value cannot be null.

expectedOutputStructure

InferenceOutput: The empty InferenceOutput representing the expected output structure. For TFLite, the inference code will verify whether this expected output structure matches model output signature.

If a model produce string tensors:

<code>String[] output = new String[3][2];  // Output tensor shape is [3, 2].
  HashMap&lt;Integer, Object&gt; outputs = new HashMap&lt;&gt;();
  outputs.put(0, output);
  expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build();
 
  </code>

This value cannot be null.

Public methods

build

Added in API level VanillaIceCream

fun build(): InferenceInput

Builds the instance.

Return
`InferenceInput`	This value cannot be `null`.

setBatchSize

Added in API level VanillaIceCream

fun setBatchSize(value: Int): InferenceInput.Builder

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.

Return
`InferenceInput.Builder`	This value cannot be `null`.

setExpectedOutputStructure

Added in API level VanillaIceCream

fun setExpectedOutputStructure(value: InferenceOutput): InferenceInput.Builder

The empty InferenceOutput representing the expected output structure. For TFLite, the inference code will verify whether this expected output structure matches model output signature.

If a model produce string tensors:

<code>String[] output = new String[3][2];  // Output tensor shape is [3, 2].
  HashMap&lt;Integer, Object&gt; outputs = new HashMap&lt;&gt;();
  outputs.put(0, output);
  expectedOutputStructure = new InferenceOutput.Builder().setDataOutputs(outputs).build();
  </code>

Parameters
`value`	InferenceOutput: This value cannot be `null`.

Return
`InferenceInput.Builder`	This value cannot be `null`.

setInputData

Added in API level VanillaIceCream

fun setInputData(vararg value: Any!): InferenceInput.Builder

An array of input data. The inputs should be in the same order as inputs of the model.

For example, if a model takes multiple inputs:

<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, ...};
  </code>

For TFLite, this field is mapped to inputs of runForMultipleInputsOutputs: https://www.tensorflow.org/lite/api_docs/java/org/tensorflow/lite/InterpreterApi#parameters_9

Parameters
`value`	Any!: This value cannot be `null`.

Return
`InferenceInput.Builder`	This value cannot be `null`.

setParams

Added in API level VanillaIceCream

fun setParams(value: InferenceInput.Params): InferenceInput.Builder

The configuration that controls runtime interpreter behavior.

Parameters
`value`	InferenceInput.Params: This value cannot be `null`.

Return
`InferenceInput.Builder`	This value cannot be `null`.