Class TensorflowModel<T extends Output<T>>

java.lang.Object

org.tribuo.Model<T>

org.tribuo.interop.tensorflow.TensorflowModel<T>

All Implemented Interfaces:

com.oracle.labs.mlrg.olcut.provenance.Provenancable<ModelProvenance>, Closeable, Serializable, AutoCloseable

public class TensorflowModel<T extends Output<T>>
extends Model<T>
implements Closeable

This model encapsulates a simple model with a single input tensor (labelled INPUT_NAME), and produces a single output tensor (labelled OUTPUT_NAME).

It accepts an ExampleTransformer that converts an example's features into a Tensor, and an OutputTransformer that converts a Tensor into a Prediction.

The model's serialVersionUID is set to the major Tensorflow version number times 100.

N.B. Tensorflow support is experimental and may change without a major version bump.

See Also:

• Serialized Form

Field Summary

Fields

Modifier and Type	Field	Description
static final String	INPUT_NAME
static final String	OUTPUT_NAME

Fields inherited from class org.tribuo.Model

ALL_OUTPUTS, BIAS_FEATURE, featureIDMap, generatesProbabilities, name, outputIDInfo, provenance, provenanceOutput

Method Summary

Modifier and Type	Method	Description
void	close()
protected TensorflowModel<T>	copy(String newName, ModelProvenance newProvenance)	Copies a model, replacing it's provenance and name with the supplied values.
int	getBatchSize()	Gets the current testing batch size.
Optional<Excuse<T>>	getExcuse(Example<T> example)	Deep learning models don't do excuses.
Map<String, List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>>	getTopFeatures(int n)	Deep learning models don't do feature rankings.
protected List<Prediction<T>>	innerPredict(Iterable<Example<T>> examples)	Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).
Prediction<T>	predict(Example<T> example)	Uses the model to predict the output for a single example.
void	setBatchSize(int batchSize)	Sets a new batch size.

Methods inherited from class org.tribuo.Model

copy, generatesProbabilities, getExcuses, getFeatureIDMap, getName, getOutputIDInfo, getProvenance, predict, predict, setName, toString, validate

Methods inherited from class java.lang.Object

clone, equals, finalize, getClass, hashCode, notify, notifyAll, wait, wait, wait

Field Details

INPUT_NAME

public static final String INPUT_NAME

See Also:

• Constant Field Values

OUTPUT_NAME

public static final String OUTPUT_NAME

See Also:

• Constant Field Values

Method Details

predict

public Prediction<T> predict(Example<T> example)

Description copied from class: Model

Uses the model to predict the output for a single example.

predict does not mutate the example.

Throws IllegalArgumentException if the example has no features or no feature overlap with the model.

Specified by:

predict in class Model<T extends Output<T>>

Parameters:

example - the example to predict.

Returns:

the result of the prediction.

innerPredict

protected List<Prediction<T>> innerPredict(Iterable<Example<T>> examples)

Description copied from class: Model

Called by the base implementations of Model.predict(Iterable) and Model.predict(Dataset).

Overrides:

innerPredict in class Model<T extends Output<T>>

Parameters:

examples - The examples to predict.

Returns:

The results of the predictions, in the same order as the examples.

getBatchSize

public int getBatchSize()

Gets the current testing batch size.

Returns:

The batch size.

setBatchSize

public void setBatchSize(int batchSize)

Sets a new batch size. Throws IllegalArgumentException if the batch size isn't positive.

Parameters:

batchSize - The batch size to use.

getTopFeatures

public Map<String, List<com.oracle.labs.mlrg.olcut.util.Pair<String,Double>>> getTopFeatures(int n)

Deep learning models don't do feature rankings. Use an Explainer.

This method always returns the empty map.

Specified by:

getTopFeatures in class Model<T extends Output<T>>

Parameters:

n - the number of features to return.

Returns:

The empty map.

getExcuse

public Optional<Excuse<T>> getExcuse(Example<T> example)

Deep learning models don't do excuses. Use an Explainer.

This method always returns Optional.empty().

Specified by:

getExcuse in class Model<T extends Output<T>>

Parameters:

example - The input example.

Returns:

Optional.empty().

copy

protected TensorflowModel<T> copy(String newName,
 ModelProvenance newProvenance)

Description copied from class: Model

Copies a model, replacing it's provenance and name with the supplied values.

Used to provide the provenance removal functionality.

Specified by:

copy in class Model<T extends Output<T>>

Parameters:

newName - The new name.

newProvenance - The new provenance.

Returns:

A copy of the model.

close

public void close()

Specified by:

close in interface AutoCloseable

Specified by:

close in interface Closeable