optimize imports, cleanup code

Signed-off-by: Alex <[email protected]>

Author: loxal

dl4j-examples/src/main/kotlin/org/deeplearning4j/examples/feedforward/mnist/MLPMnistTwoLayerExample.kt

@@ -16,28 +16,18 @@
 
 package org.deeplearning4j.examples.feedforward.mnist
 
-
-import org.nd4j.linalg.activations.Activation
-import org.nd4j.linalg.dataset.api.iterator.DataSetIterator
 import org.deeplearning4j.datasets.iterator.impl.MnistDataSetIterator
-import org.deeplearning4j.eval.Evaluation
-import org.deeplearning4j.nn.api.OptimizationAlgorithm
-import org.deeplearning4j.nn.conf.MultiLayerConfiguration
 import org.deeplearning4j.nn.conf.NeuralNetConfiguration
-import org.deeplearning4j.nn.conf.Updater
 import org.deeplearning4j.nn.conf.layers.DenseLayer
 import org.deeplearning4j.nn.conf.layers.OutputLayer
 import org.deeplearning4j.nn.multilayer.MultiLayerNetwork
 import org.deeplearning4j.nn.weights.WeightInit
 import org.deeplearning4j.optimize.listeners.ScoreIterationListener
-import org.nd4j.linalg.api.ndarray.INDArray
-import org.nd4j.linalg.dataset.DataSet
+import org.nd4j.linalg.activations.Activation
 import org.nd4j.linalg.learning.config.Nesterovs
 import org.nd4j.linalg.lossfunctions.LossFunctions.LossFunction
-import org.slf4j.Logger
 import org.slf4j.LoggerFactory
 
-
 /** A slightly more involved multilayered (MLP) applied to digit classification for the MNIST dataset (http://yann.lecun.com/exdb/mnist/).
 
  * This example uses two input layers and one hidden layer.