Drop additional logging for ResNet-CIFAR10

Author: shadaj

Examples/ResNet-CIFAR10/main.swift

@@ -16,7 +16,7 @@ import Datasets
 import ImageClassificationModels
 import TensorFlow
 
-let batchSize = 512
+let batchSize = 10
 
 let dataset = CIFAR10(batchSize: batchSize)
 
@@ -34,7 +34,6 @@ for (epoch, epochBatches) in dataset.training.prefix(10).enumerated() {
     Context.local.learningPhase = .training
     var trainingLossSum: Float = 0
     var trainingBatchCount = 0
-    let batchCount = epochBatches.count
     for batch in epochBatches {
         let (images, labels) = (batch.data, batch.label)
         let (loss, gradients) = valueWithGradient(at: model) { model -> Tensor<Float> in
@@ -44,7 +43,6 @@ for (epoch, epochBatches) in dataset.training.prefix(10).enumerated() {
         trainingLossSum += loss.scalarized()
         trainingBatchCount += 1
         optimizer.update(&model, along: gradients)
-        print(trainingLossSum / Float(trainingBatchCount), Float(trainingBatchCount) / Float(batchCount))
     }
 
     Context.local.learningPhase = .inference