<prompt> Andika mpango wa Golang unaotumia TensorFlow kutoa mafunzo kwa mtandao wa neva kwenye mkusanyiko wa data wa MNIST kwa utambuzi wa tarakimu ulioandikwa kwa mkono, na kutathmini utendaji wake kwenye seti ya majaribio.PLINFORMAT  <response>: kifurushi kikuukuagiza fmtlogitf github.comtensorflowtensorflowtensorflowgogithub.comtensorflowtensorflowtensorflowgoopconst Ukubwa wa picha 28 28nambariLabels 10siriLayer 1024batchSize 100numHatua 1000func main mzizi : op.NewScopeX : op.Placeholderroot.SubScopeinput, tf.Float, op.PlaceholderShapetf.MakeShapebatchSize, imageSizeY : op.Placeholderroot.SubScopeoutput, tf.Float, op.PlaceholderShapetf.MakeShapebatchSize, numLabelsw1 : weightVariablemizizi, int64imageSize, hiddenLayerb1 : biasVariablemizizi, int64hiddenLayerw2 : weightVariablemizizi, int64hiddenLayer, numLabelsb2 : biasVariablemizizi, int64numLabelslayer1 : op.Ongezamizizi, op.MatMulmzizi, X, w1, b1safu1 op.ReLUmzizi, safu1kumbukumbu : op.Ongezamizizi, op.MatMulmizizi, safu1, w2, b2utabiri : op.ArgMaxmizizi, kumbukumbu, 1lebo : op.ArgMaxmizizi, Y, 1correctPrediction : op.Equalmizizi, ubashiri, lebousahihi : op.ReduceMeanmzizi, op.Castmzizi, correctPrediction, tf.Floathasara : op.ReduceMeanmizizi, op.SoftmaxCrossEntropyWithLogitsmizizi, kumbukumbu, YtreniHatua : op.GradientDescentmizizi, hasara, 0.5grafu, kosa : root.Finalizeikiwa makosa ! nil log.Fatalhitilafusess, makosa : tf.NewSessiongrafu, tf.SessionOptionsikiwa makosa ! nil log.Fatalhitilafuahirisha sess.Fungamnist : loadMNISTDatakwa i : 0; i numHatua; i batchX, batchY : mnist.train.nextBatchbatchSizeikiwa _, err sess.Runmaptf.Outputtf.TensorX: batchX, Y: batchY, tf.OutputtrainStep, nil; makosa ! nil log.Fatalhitilafuikiwa mimi100 0 testAccuracy, err : sess.Runmaptf.Outputtf.TensorX: mnist.test.images, Y: mnist.test.labels, tf.Outputusahihi, nilikiwa makosa ! nil log.Fatalhitilafufmt.PrintfHatua d, usahihi wa jaribio: fn, i, testAccuracy0.Thamanifunc weightVariables op.Scope, shape int64 tf.Output init : op.TruncatedNormals.SubScopeuzito, umbo, tf.Floatreturn op.Vigezo, init.Shape, tf.Floatfunc biasVariables op.Scope, shape int64 tf.Output init : op.Zeross.SubScopeupendeleo, umbo, tf.Floatreturn op.Vigezo, init.Shape, tf.Floatfunc loadMNISTData mnistData Pakia seti ya data ya MNIST kwa kutumia maktaba au msimbo maalum. Data inapaswa kuchakatwa na kugawanywa katika seti za mafunzo na majaribio. Rudisha mfano wa mnistData na treni na sifa za majaribio zilizo na picha na lebo.chapa muundo wa mnistData treni mnistDataSettest mnistDataSetchapa muundo wa mnistDataSet picha tf.Tensorlebo tf.Tensor 