More refactoring

Sources/Adapters/TFOptimizer.swift

@@ -20,7 +20,7 @@ public extension TFOptimizer {
     /// This information can later be used by the 'activationNeuron' function
     func addNeuronIfThere(node: TFNode) {
         let outgoing = node.outgoingNodes()
-        if outgoing.count == 1, let next = (outgoing.first as? TFNode),
+        if let next = (outgoing.first as? TFNode),
             next.nodeDef.isTFReLuOp || next.nodeDef.isTFTanhOp || next.nodeDef.isTFSigmoidOp {
             var neuron = Tensorflow_AttrValue()
             neuron.value = Tensorflow_AttrValue.OneOf_Value.s(next.nodeDef.op.data(using: .utf8)!)

Sources/Core/Network.swift

@@ -100,10 +100,10 @@ public class Network {
 
     func set(layers: [NetworkLayer]) {
         nodes = layers
-        let inputNodes = nodes.filter { $0.getIncoming().count == 0 }
+        let inputNodes = nodes.filter { $0.getIncoming().isEmpty }
         assert(inputNodes.count == startNodes.count, "Number of network inputs(\(inputNodes.count)) and input sizes(\(startNodes.count)) are not equal")
-        if inputNodes.count == 1 {
-            inputNodes[0].addIncomingEdge(from: startNodes[0])
+        if let first = inputNodes.first {
+            first.addIncomingEdge(from: startNodes[0])
             nodes.insert(startNodes[0], at: 0)
         } else {
             for node in startNodes {

Sources/Core/ParameterLoader.swift

@@ -47,7 +47,7 @@ extension ParameterLoader {
         let w = UnsafePointer(hdrW!.bindMemory(to: Float.self, capacity: Int(sizeWeights)))
 
         close(fd_w)
-        assert(w != UnsafePointer<Float>.init(bitPattern: -1), "mmap failed with errno = \(errno)")
+        assert(w != UnsafePointer<Float>(bitPattern: -1), "mmap failed with errno = \(errno)")
         return w
     }