ARG SWIFT_TF_URL=https://storage.googleapis.com/swift-tensorflow/ubuntu16.04/swift-tensorflow-DEVELOPMENT-2018年04月26日-a-ubuntu16.04.tar.gz

ARG SWIFT_TF_URL=https://storage.googleapis.com/swift-tensorflow/ubuntu16.04/swift-tensorflow-DEVELOPMENT-2019年01月04日-a-ubuntu16.04.tar.gz

RUN curl -fSsL $SWIFT_TF_URL -o swift-tensorflow.tar.gz \

&& tar xzf swift-tensorflow.tar.gz --directory /

&& tar xzf swift-tensorflow.tar.gz --directory / \

&& rm swift-tensorflow.tar.gz

RUN mv -n /usr/lib/libBlocksRuntime.so /usr/lib/libBlocksRuntime.so.0 && ldconfig

RUN swift --version

RUN cd /usr/src

WORKDIR /usr/src

WORKDIR /usr/src

docker run --rm --security-opt seccomp:unconfined -itv ${PWD}:/usr/src \

zachgray/swift-tensorflow:4.2 \

swift -I/usr/lib/swift/clang/include

swift

Assuming you've added a swift file ([like this one shown in the official docs](https://github.com/tensorflow/swift/blob/master/Usage.md#interpreter)) in your current directory with the name `inference.swift`:

Assuming you've added a swift file, like this one copied from [official docs](https://github.com/tensorflow/swift/blob/master/Usage.md#interpreter) in your current directory with the name `inference.swift`:

import TensorFlow

struct MLPClassifier {

var w1 = Tensor<Float>(shape: [2, 4], repeating: 0.1)

var w2 = Tensor<Float>(shape: [4, 1], scalars: [0.4, -0.5, -0.5, 0.4])

var b1 = Tensor<Float>([0.2, -0.3, -0.3, 0.2])

var b2 = Tensor<Float>([[0.4]])

func prediction(for x: Tensor<Float>) -> Tensor<Float> {

let o1 = tanh(matmul(x, w1) + b1)

return tanh(matmul(o1, w2) + b2)

}

}

let input = Tensor<Float>([[0.2, 0.8]])

let classifier = MLPClassifier()

let prediction = classifier.prediction(for: input)

print(prediction)

To use the interpreter:

docker run --rm -v ${PWD}:/usr/src \

docker run --rm -v ${PWD}:/usr/src zachgray/swift-tensorflow:4.2 \

swiftc -O /usr/src/inference.swift

swiftc -O /usr/src/inference.swift -ltensorflow