Add WrapperAware trait

src/GridSearch.php

@@ -23,6 +23,7 @@
 use Rubix\ML\Specifications\EstimatorIsCompatibleWithMetric;
 use Rubix\ML\Specifications\SamplesAreCompatibleWithEstimator;
 use Rubix\ML\Exceptions\InvalidArgumentException;
+use Rubix\ML\Traits\WrapperAware;
 
 /**
  * Grid Search
@@ -41,7 +42,7 @@
  */
 class GridSearch implements Wrapper, Learner, Parallel, Verbose, Persistable
 {
-    use AutotrackRevisions, Multiprocessing, LoggerAware;
+    use AutotrackRevisions, Multiprocessing, LoggerAware, WrapperAware;
 
     /**
      * The class name of the base estimator.
@@ -71,13 +72,6 @@ class GridSearch implements Wrapper, Learner, Parallel, Verbose, Persistable
      */
     protected \Rubix\ML\CrossValidation\Validator $validator;
 
-    /**
-     * The base estimator instance.
-     *
-     * @var Learner
-     */
-    protected \Rubix\ML\Learner $base;
-
     /**
      * The validation scores obtained from the last search.
      *
@@ -179,18 +173,6 @@ public function __construct(
         $this->backend = new Serial();
     }
 
-    /**
-     * Return the estimator type.
-     *
-     * @internal
-     *
-     * @return EstimatorType
-     */
-    public function type() : EstimatorType
-    {
-        return $this->base->type();
-    }
-
     /**
      * Return the data types that the estimator is compatible with.
      *
@@ -232,16 +214,6 @@ public function trained() : bool
         return $this->base->trained();
     }
 
-    /**
-     * Return the base learner instance.
-     *
-     * @return Estimator
-     */
-    public function base() : Estimator
-    {
-        return $this->base;
-    }
-
     /**
      * Train one estimator per combination of parameters given by the grid and
      * assign the best one as the base estimator of this instance.
@@ -304,18 +276,6 @@ public function train(Dataset $dataset) : void
         }
     }
 
-    /**
-     * Make a prediction on a given sample dataset.
-     *
-     * @param Dataset $dataset
-     * @throws Exceptions\RuntimeException
-     * @return mixed[]
-     */
-    public function predict(Dataset $dataset) : array
-    {
-        return $this->base->predict($dataset);
-    }
-
     /**
      * The callback that executes after the cross validation task.
      *

src/PersistentModel.php

@@ -10,6 +10,7 @@
 use Rubix\ML\AnomalyDetectors\Scoring;
 use Rubix\ML\Exceptions\InvalidArgumentException;
 use Rubix\ML\Exceptions\RuntimeException;
+use Rubix\ML\Traits\WrapperAware;
 
 /**
  * Persistent Model
@@ -23,12 +24,7 @@
  */
 class PersistentModel implements Wrapper, Learner, Probabilistic, Scoring
 {
-    /**
-     * The persistable base learner.
-     *
-     * @var Learner
-     */
-    protected \Rubix\ML\Learner $base;
+    use WrapperAware;
 
     /**
      * The persister used to interface with the storage layer.
@@ -84,30 +80,6 @@ public function __construct(Learner $base, Persister $persister, ?Serializer $se
         $this->serializer = $serializer ?? new RBX();
     }
 
-    /**
-     * Return the estimator type.
-     *
-     * @internal
-     *
-     * @return EstimatorType
-     */
-    public function type() : EstimatorType
-    {
-        return $this->base->type();
-    }
-
-    /**
-     * Return the data types that the estimator is compatible with.
-     *
-     * @internal
-     *
-     * @return list<\Rubix\ML\DataType>
-     */
-    public function compatibility() : array
-    {
-        return $this->base->compatibility();
-    }
-
     /**
      * Return the settings of the hyper-parameters in an associative array.
      *
@@ -134,16 +106,6 @@ public function trained() : bool
         return $this->base->trained();
     }
 
-    /**
-     * Return the base estimator instance.
-     *
-     * @return Estimator
-     */
-    public function base() : Estimator
-    {
-        return $this->base;
-    }
-
     /**
      * Save the model to storage.
      */
@@ -168,17 +130,6 @@ public function train(Dataset $dataset) : void
         $this->base->train($dataset);
     }
 
-    /**
-     * Make a prediction on a given sample dataset.
-     *
-     * @param Dataset $dataset
-     * @return mixed[]
-     */
-    public function predict(Dataset $dataset) : array
-    {
-        return $this->base->predict($dataset);
-    }
-
     /**
      * Estimate the joint probabilities for each possible outcome.
      *

src/Pipeline.php

@@ -4,6 +4,7 @@
 
 use Rubix\ML\Helpers\Params;
 use Rubix\ML\Datasets\Dataset;
+use Rubix\ML\Traits\WrapperAware;
 use Rubix\ML\Transformers\Elastic;
 use Rubix\ML\Transformers\Stateful;
 use Rubix\ML\Transformers\Transformer;
@@ -27,7 +28,7 @@
  */
 class Pipeline implements Online, Probabilistic, Scoring, Persistable, Wrapper
 {
-    use AutotrackRevisions;
+    use AutotrackRevisions, WrapperAware;
 
     /**
      * A list of transformers to be applied in series.
@@ -38,13 +39,6 @@ class Pipeline implements Online, Probabilistic, Scoring, Persistable, Wrapper
         //
     ];
 
-    /**
-     * An instance of a base estimator to receive the transformed data.
-     *
-     * @var Estimator
-     */
-    protected \Rubix\ML\Estimator $base;
-
     /**
      * Should we update the elastic transformers during partial train?
      *
@@ -72,30 +66,6 @@ public function __construct(array $transformers, Estimator $base, bool $elastic
         $this->elastic = $elastic;
     }
 
-    /**
-     * Return the estimator type.
-     *
-     * @internal
-     *
-     * @return EstimatorType
-     */
-    public function type() : EstimatorType
-    {
-        return $this->base->type();
-    }
-
-    /**
-     * Return the data types that the estimator is compatible with.
-     *
-     * @internal
-     *
-     * @return list<\Rubix\ML\DataType>
-     */
-    public function compatibility() : array
-    {
-        return $this->base->compatibility();
-    }
-
     /**
      * Return the settings of the hyper-parameters in an associative array.
      *
@@ -124,16 +94,6 @@ public function trained() : bool
             : true;
     }
 
-    /**
-     * Return the base estimator instance.
-     *
-     * @return Estimator
-     */
-    public function base() : Estimator
-    {
-        return $this->base;
-    }
-
     /**
      * Run the training dataset through all transformers in order and use the
      * transformed dataset to train the estimator.

src/Traits/WrapperAware.php

@@ -0,0 +1,73 @@
+<?php
+
+namespace Rubix\ML\Traits;
+
+use Rubix\ML\Datasets\Dataset;
+use Rubix\ML\Estimator;
+use Rubix\ML\EstimatorType;
+use Rubix\ML\Exceptions\RuntimeException;
+use Rubix\ML\Learner;
+
+/**
+ * Wrapper Aware
+ *
+ * This trait fulfills the requirements of the Wrapper interface and is suitable for most implementations.
+ *
+ * @category    Machine Learning
+ * @package     Rubix/ML
+ */
+trait WrapperAware
+{
+    /**
+     * The base estimator.
+     *
+     * @var Learner
+     */
+    protected Estimator $base;
+
+    /**
+     * Return the base estimator instance.
+     *
+     * @return Estimator
+     */
+    public function base(): Estimator
+    {
+        return $this->base;
+    }
+
+    /**
+     * Return the estimator type.
+     *
+     * @internal
+     *
+     * @return EstimatorType
+     */
+    public function type() : EstimatorType
+    {
+        return $this->base->type();
+    }
+
+    /**
+     * Return the data types that the estimator is compatible with.
+     *
+     * @internal
+     *
+     * @return list<\Rubix\ML\DataType>
+     */
+    public function compatibility() : array
+    {
+        return $this->base->compatibility();
+    }
+
+    /**
+     * Make a prediction on a given sample dataset.
+     *
+     * @param Dataset $dataset
+     * @throws RuntimeException
+     * @return mixed[]
+     */
+    public function predict(Dataset $dataset) : array
+    {
+        return $this->base->predict($dataset);
+    }
+}

src/Wrapper.php

@@ -0,0 +1,20 @@
+<?php
+
+namespace Rubix\ML;
+
+/**
+ * Wrapper
+ *
+ * @category    Machine Learning
+ * @package     Rubix/ML
+ * @author      Andrew DalPino
+ */
+interface Wrapper extends Estimator
+{
+    /**
+     * Return the base estimator instance.
+     *
+     * @return Estimator
+     */
+    public function base(): Estimator;
+}