Fix tests and such

Author: andrewdalpino

src/Classifiers/LogisticRegression.php

@@ -108,9 +108,9 @@ class LogisticRegression implements Estimator, Learner, Online, Probabilistic, R
     /**
      * The underlying neural network instance.
      *
-     * @var \Rubix\ML\NeuralNet\Network|null
+     * @var Network|null
      */
-    protected ?\Rubix\ML\NeuralNet\Network $network = null;
+    protected ?Network $network = null;
 
     /**
      * The unique class labels.
@@ -267,7 +267,7 @@ public function losses() : ?array
     /**
      * Return the underlying neural network instance or null if not trained.
      *
-     * @return \Rubix\ML\NeuralNet\Network|null
+     * @return Network|null
      */
     public function network() : ?Network
     {

src/Classifiers/MultilayerPerceptron.php

@@ -139,9 +139,9 @@ class MultilayerPerceptron implements Estimator, Learner, Online, Probabilistic,
     /**
      * The underlying neural network instance.
      *
-     * @var \Rubix\ML\NeuralNet\Network|null
+     * @var Network|null
      */
-    protected ?\Rubix\ML\NeuralNet\Network $network = null;
+    protected ?Network $network = null;
 
     /**
      * The unique class labels.
@@ -167,12 +167,7 @@ class MultilayerPerceptron implements Estimator, Learner, Online, Probabilistic,
     /**
      * @param \Rubix\ML\NeuralNet\Layers\Hidden[] $hiddenLayers
      * @param int $batchSize
-<<<<<<< HEAD
-     * @param \Rubix\ML\NeuralNet\Optimizers\Optimizer|null $optimizer
-=======
      * @param Optimizer|null $optimizer
-     * @param float $l2Penalty
->>>>>>> 2.5
      * @param int $epochs
      * @param float $minChange
      * @param int $evalInterval
@@ -349,7 +344,7 @@ public function losses() : ?array
     /**
      * Return the underlying neural network instance or null if not trained.
      *
-     * @return \Rubix\ML\NeuralNet\Network|null
+     * @return Network|null
      */
     public function network() : ?Network
     {

src/Classifiers/SoftmaxClassifier.php

@@ -104,9 +104,9 @@ class SoftmaxClassifier implements Estimator, Learner, Online, Probabilistic, Ve
     /**
      * The underlying neural network instance.
      *
-     * @var \Rubix\ML\NeuralNet\Network|null
+     * @var Network|null
      */
-    protected ?\Rubix\ML\NeuralNet\Network $network = null;
+    protected ?Network $network = null;
 
     /**
      * The unique class labels.
@@ -263,7 +263,7 @@ public function losses() : ?array
     /**
      * Return the underlying neural network instance or null if not trained.
      *
-     * @return \Rubix\ML\NeuralNet\Network|null
+     * @return Network|null
      */
     public function network() : ?Network
     {

src/NeuralNet/FeedForward.php

@@ -34,7 +34,7 @@ class Network
      *
      * @var Input
      */
-    protected \Rubix\ML\NeuralNet\Layers\Input $input;
+    protected Input $input;
 
     /**
      * The hidden layers of the network.
@@ -59,14 +59,14 @@ class Network
      *
      * @var Output
      */
-    protected \Rubix\ML\NeuralNet\Layers\Output $output;
+    protected Output $output;
 
     /**
      * The gradient descent optimizer used to train the network.
      *
      * @var Optimizer
      */
-    protected \Rubix\ML\NeuralNet\Optimizers\Optimizer $optimizer;
+    protected Optimizer $optimizer;
 
     /**
      * @param Input $input

src/NeuralNet/Network.php

@@ -109,9 +109,9 @@ class Adaline implements Estimator, Learner, Online, RanksFeatures, Verbose, Per
     /**
      * The underlying neural network instance.
      *
-     * @var \Rubix\ML\NeuralNet\Network|null
+     * @var Network|null
      */
-    protected ?\Rubix\ML\NeuralNet\Network $network = null;
+    protected ?Network $network = null;
 
     /**
      * The loss at each epoch from the last training session.
@@ -261,7 +261,7 @@ public function losses() : ?array
     /**
      * Return the underlying neural network instance or null if not trained.
      *
-     * @return \Rubix\ML\NeuralNet\Network|null
+     * @return Network|null
      */
     public function network() : ?Network
     {