Interpreter.Options

public static class Interpreter.Options

An options class for controlling runtime interpreter behavior.

Public Constructors

Options()

Public Methods

Interpreter.Options	addDelegate(Delegate delegate) Adds a `Delegate` to be applied during interpreter creation.
Interpreter.Options	setAllowBufferHandleOutput(boolean allow) Advanced: Set if buffer handle output is allowed.
Interpreter.Options	setAllowFp16PrecisionForFp32(boolean allow) This method was deprecated in API level . Prefer using `ERROR(/org.tensorflow.lite.nnapi.NnApiDelegate.Options#setAllowFp16(boolean enable))`.
Interpreter.Options	setNumThreads(int numThreads) Sets the number of threads to be used for ops that support multi-threading.
Interpreter.Options	setUseNNAPI(boolean useNNAPI) Sets whether to use NN API (if available) for op execution.
Interpreter.Options	setUseXNNPACK(boolean useXNNPACK) Experimental: Enable an optimized set of floating point CPU kernels (provided by XNNPACK).

Inherited Methods

From class java.lang.Object

boolean	equals(Object arg0)
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()

Public Constructors

public Options ()

Public Methods

public Interpreter.Options addDelegate (Delegate delegate)

Adds a Delegate to be applied during interpreter creation.

WARNING: This is an experimental interface that is subject to change.

public Interpreter.Options setAllowBufferHandleOutput (boolean allow)

Advanced: Set if buffer handle output is allowed.

When a Delegate supports hardware acceleration, the interpreter will make the data of output tensors available in the CPU-allocated tensor buffers by default. If the client can consume the buffer handle directly (e.g. reading output from OpenGL texture), it can set this flag to false, avoiding the copy of data to the CPU buffer. The delegate documentation should indicate whether this is supported and how it can be used.

WARNING: This is an experimental interface that is subject to change.

public Interpreter.Options setAllowFp16PrecisionForFp32 (boolean allow)

This method was deprecated in API level .
Prefer using ERROR(/org.tensorflow.lite.nnapi.NnApiDelegate.Options#setAllowFp16(boolean enable)).

Sets whether to allow float16 precision for FP32 calculation when possible. Defaults to false (disallow).

public Interpreter.Options setNumThreads (int numThreads)

Sets the number of threads to be used for ops that support multi-threading. Defaults to a platform-dependent value.

public Interpreter.Options setUseNNAPI (boolean useNNAPI)

Sets whether to use NN API (if available) for op execution. Defaults to false (disabled).

public Interpreter.Options setUseXNNPACK (boolean useXNNPACK)

Experimental: Enable an optimized set of floating point CPU kernels (provided by XNNPACK).

Enabling this flag will enable use of a new, highly optimized set of CPU kernels provided via the XNNPACK delegate. Currently, this is restricted to a subset of floating point operations. Eventually, we plan to enable this by default, as it can provide significant peformance benefits for many classes of floating point models. See https://github.com/tensorflow/tensorflow/blob/master/tensorflow/lite/delegates/xnnpack/README.md for more details.

Things to keep in mind when enabling this flag:

Startup time and resize time may increase.
Baseline memory consumption may increase.
Compatibility with other delegates (e.g., GPU) has not been fully validated.
Quantized models will not see any benefit.

WARNING: This is an experimental interface that is subject to change.