FirebaseModelInterpreter

public final class FirebaseModelInterpreter extends Object
implements Closeable

This class is deprecated.
For more information refer to the custom model implementation instructions.

Interpreter to run custom models with TensorFlow Lite (requires API level 16+)

A model interpreter is created via getInstance(FirebaseModelInterpreterOptions) Follow the steps below to specify the FirebaseCustomRemoteModel or FirebaseCustomLocalModel, create a FirebaseModelInterpreterOptions and then create a FirebaseModelInterpreter and all the way to running an inference with the model.

Firstly, create at least one of FirebaseCustomRemoteModel and FirebaseCustomLocalModel. If you want to use FirebaseCustomRemoteModel, you need to download it through FirebaseModelManager first.

The following code creates the model and the interpreterOptions:



 FirebaseCustomRemoteModel remoteModel = new FirebaseCustomRemoteModel.Builder(REMOTE_MODEL_NAME)
     .build();

 FirebaseModelInterpreterOptions interpreterOptions =
      new FirebaseModelInterpreterOptions.Builder(remoteModel).build();

 Or

 FirebaseCustomLocalModel localModel = new FirebaseCustomLocalModel.Builder()
     .setFilePath(filePath).build();

 FirebaseModelInterpreterOptions interpreterOptions =
     new FirebaseModelInterpreterOptions.Builder(localModel).build();

Secondly, create an instance of FirebaseModelInterpreter with the FirebaseModelInterpreterOptions


 FirebaseModelInterpreter interpreter = FirebaseModelInterpreter.getInstance(interpreterOptions);

Thirdly, create a FirebaseModelInputs and a FirebaseModelInputOutputOptions. You need to know the input and output data specifications of the model, including the data types and input/output dimensions. The following code is an example:


 FirebaseModelInputs modelInputs = new FirebaseModelInputs.Builder().add(...).build();

 FirebaseModelInputOutputOptions inputOutputOptions =
     new FirebaseModelInputOutputOptions.Builder()
         .setInputFormat(0, FirebaseModelDataType.FLOAT32, inputDims)
         .setOutputFormat(0, FirebaseModelDataType.FLOAT32, outputDims)
         .build();

Lastly, feed the inputs to run(FirebaseModelInputs, FirebaseModelInputOutputOptions). The following code is an example:


 Task<FirebaseModelOutputs> task = interpreter.run(modelInputs, inputOutputOptions);
 task.addOnSuccessListener(...).addOnFailureListener(...);

Public Method Summary

void
close()
Task<Integer>
getInputIndex(String name)
Gets the index of an input by its name.
static FirebaseModelInterpreter
getInstance(FirebaseModelInterpreterOptions options)
Gets an instance of the FirebaseModelInterpreter to support custom model specified in FirebaseModelOptions.
Task<Integer>
getOutputIndex(String name)
Gets the index of an output by its name.
boolean
isStatsCollectionEnabled()
Determines whether stats collection in Model Interpreter is enabled.
Task<FirebaseModelOutputs>
run(FirebaseModelInputs inputs, FirebaseModelInputOutputOptions options)
Runs inference with input and data configurations.
void
setStatsCollectionEnabled(boolean enable)
Enables stats collection in ML Kit model interpreter.

Inherited Method Summary

Object
clone()
boolean
equals(Object arg0)
void
finalize()
final Class<?>
getClass()
int
hashCode()
final void
notify()
final void
notifyAll()
String
toString()
final void
wait(long arg0, int arg1)
final void
wait(long arg0)
final void
wait()
abstract void
close()
abstract void
close()

Public Methods

public void close ()

public Task<Integer> getInputIndex (String name)

Gets the index of an input by its name.

Parameters
name the name of the input
Returns

public static FirebaseModelInterpreter getInstance (FirebaseModelInterpreterOptions options)

Gets an instance of the FirebaseModelInterpreter to support custom model specified in FirebaseModelOptions.

Parameters
options the options for the model to use.
Returns
  • an instance of FirebaseModelInterpreter. Note that the interpreter instance will be the same instance if the supplied options are the same.
Throws
IllegalArgumentException if FirebaseModelInterpreterOptions contains no model
FirebaseMLException

public Task<Integer> getOutputIndex (String name)

Gets the index of an output by its name.

Parameters
name the name of the output
Returns

public boolean isStatsCollectionEnabled ()

Determines whether stats collection in Model Interpreter is enabled.

Returns
  • true if stats collection is enabled.

public Task<FirebaseModelOutputs> run (FirebaseModelInputs inputs, FirebaseModelInputOutputOptions options)

Runs inference with input and data configurations.

Parameters
inputs an instance of FirebaseModelInputs containing input data
options an instance of FirebaseModelInputOutputOptions containing types and dimensions of input and output data.

public void setStatsCollectionEnabled (boolean enable)

Enables stats collection in ML Kit model interpreter. The stats include API calls counts, errors, API call durations, options, etc. No personally identifiable information is logged.

The setting is per MlKitContext, and it is persistent together with app's private data. It means if the user uninstalls the app or clears all app data, the setting will be erased. The best practice is to set the flag in each initialization.

By default the logging is enabled. You have to specifically set it to false here to disable logging for FirebaseModelInterpreter.