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STT-tensorflow/tensorflow/lite/experimental/swift/Tests
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YoungSeok Yoon 772433a2a2 Add flag for using optimized TFLite CPU kernels on iOS 
This adds new experimental flags to the interpreter options of TFLite Obj-C and
Swift APIs, which can be used for opting in to a set of highly optimized
floating point kernels provided via the XNNPACK delegate. The flags can be used
as follows.

Obj-C:

    TFLInterpreterOptions *options = [[TFLInterpreterOptions alloc] init];
    options.useXNNPACK = YES;
    NSError *error;
    TFLInterpreter *interpreter =
        [[TFLInterpreter alloc] initWithModelPath:@"model/path"
                                          options:options
                                            error:&error];

Swift:

    var options = InterpreterOptions()
    options.isXNNPackEnabled = true
    var interpreter = try Interpreter(modelPath: "model/path", options: options)

PiperOrigin-RevId: 317270012
Change-Id: I82aae43c3de13ab08af3c70513e2a458e807b0f1
2020-06-19 02:03:48 -07:00
..
InterpreterTests.swift Add flag for using optimized TFLite CPU kernels on iOS 2020-06-19 02:03:48 -07:00
MetalDelegateTests.swift
ModelTests.swift Updates InterpreterOptions, TensorShape, and TensorDataType to be nested types. 2019-08-23 16:43:22 -07:00
QuantizationParametersTests.swift
TensorFlowLiteTests.swift
TensorTests.swift