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> | |
static FirebaseModelInterpreter |
getInstance(FirebaseModelInterpreterOptions
options)
Gets an instance of the
FirebaseModelInterpreter to support custom
model specified in FirebaseModelOptions .
|
Task<Integer> | |
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
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
- a
Task
for the index of the input. TheTask
will fail withFirebaseMLException
if the input name does not exist in the model.
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
- a
Task
for the index of the output name. TheTask
will fail withFirebaseMLException
if the output name does not exist in the model.
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
.