Comments (3)
Hi @cfasana,
The Java Interpreter API currently doesn't have GpuDelegateV2 directly. However if you would like to achieve the faster inference speed you can use GpuDelegate
class by setting the isPrecisionLossAllowed
flag to true
in the following way as a workaround. But for memory usage and max precision, feature requests will be raised. Thanks for letting us know.
GpuDelegateOptions options = new GpuDelegateOptions();
options.isPrecisionLossAllowed = true;
GpuDelegate gpuDelegate = new GpuDelegate(options);
InterpreterOptions interpreterOptions = new InterpreterOptions();
interpreterOptions.addDelegate(gpuDelegate);
Interpreter interpreter = new Interpreter(modelBuffer, interpreterOptions);
or
Also try with tflite_flutter library which will provide access to GpuDelegateV2 through DART API.
Hi @pkgoogle,
As @cfasana mentioned, GpuDelegateV2
need to be included in Java Interpreter API with the support of (TFLITE_GPU_INFERENCE_PRIORITY_MIN_LATENCY, TFLITE_GPU_INFERENCE_PRIORITY_MIN_MEMORY_USAGE, TFLITE_GPU_INFERENCE_PRIORITY_MAX_PRECISION)
. Raised a feature request.
Thank You
from tensorflow.
Hi @LakshmiKalaKadali,
thanks for the feedback.
I will proceed as you suggested while awaiting the Java Interpreter API update.
from tensorflow.
Hi @sirakiin, can you please take a look a this feature request? Thanks.
from tensorflow.
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