jguertl

data_loader = mx.gluon.data.DataLoader(dataset, batch_size=5)

for X_batch, y_batch in data_loader:
    print("X_batch has shape {}, and y_batch has shape {}".format(X_batch.shape, y_batch.shape))

jguertl

class DataSet(gluon.data.Dataset):
    def __init__(self,root,DomainAList, DomainBList):
        self.root = root
        self.DomainAList = DomainAList
        self.DomainBList = DomainBList
        self.load_images()

    def read_images(self, root):
        Aroot = root + 'trainA/'  #data
        Broot = root + 'trainB/'  #label

jguertl

tensorflow/contrib/makefile/download_dependencies.sh

tensorflow/contrib/makefile/compile_ios_protobuf.sh 

make -f tensorflow/contrib/makefile/Makefile TARGET=IOS IOS_ARCH=ARM64

jguertl

class Greeter {
    constructor(public greeting: string) { }
    greet() {
        return "<h1>" + this.greeting + "</h1>";
    }
};
var greeter = new Greeter("FunScript!");
var str = greeter.greet();
document.body.innerHTML = str;

jguertl

#r "tools/FAKE/tools/FakeLib.dll" // include Fake lib
open Fake 


Target "Test" (fun _ ->
    trace "Testing stuff..."
)

Target "Deploy" (fun _ ->
    trace "Heavy deploy action"

jguertl

open Suave                 // always open suave
open Suave.Http.Successful // for OK-result
open Suave.Web             // for config

web_server default_config (OK "Getting started with Suave!")