ML-385 renamed ValidatesShapes into AssertsShapes::assertSameShape

Author: apphp

src/NeuralNet/CostFunctions/CrossEntropy/CrossEntropy.php

@@ -7,7 +7,7 @@
 use NDArray;
 use NumPower;
 use Rubix\ML\NeuralNet\CostFunctions\Base\Contracts\ClassificationLoss;
-use Rubix\ML\Traits\ValidatesShapes;
+use Rubix\ML\Traits\AssertsShapes;
 use const Rubix\ML\EPSILON;
 
 /**
@@ -27,7 +27,7 @@
  */
 class CrossEntropy implements ClassificationLoss
 {
-    use ValidatesShapes;
+    use AssertsShapes;
 
     /**
      * Compute the loss score.
@@ -40,7 +40,7 @@ class CrossEntropy implements ClassificationLoss
      */
     public function compute(NDArray $output, NDArray $target) : float
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         // Clip values to avoid log(0)
         $output = NumPower::clip($output, EPSILON, 1.0);
@@ -63,7 +63,7 @@ public function compute(NDArray $output, NDArray $target) : float
      */
     public function differentiate(NDArray $output, NDArray $target) : NDArray
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         // Numerator = ŷ - y (calculate before clipping to preserve zeros)
         $numerator = NumPower::subtract($output, $target);

src/NeuralNet/CostFunctions/HuberLoss/HuberLoss.php

@@ -8,7 +8,7 @@
 use NumPower;
 use Rubix\ML\NeuralNet\CostFunctions\Base\Contracts\RegressionLoss;
 use Rubix\ML\NeuralNet\CostFunctions\HuberLoss\Exceptions\InvalidAlphaException;
-use Rubix\ML\Traits\ValidatesShapes;
+use Rubix\ML\Traits\AssertsShapes;
 
 /**
  * Huber Loss
@@ -25,7 +25,7 @@
  */
 class HuberLoss implements RegressionLoss
 {
-    use ValidatesShapes;
+    use AssertsShapes;
 
     /**
      * The alpha quantile i.e the pivot point at which numbers larger will be
@@ -70,7 +70,7 @@ public function __construct(float $alpha = 0.9)
      */
     public function compute(NDArray $output, NDArray $target) : float
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         $difference = NumPower::subtract($target, $output);
         $scaled = NumPower::divide($difference, $this->alpha);
@@ -94,7 +94,7 @@ public function compute(NDArray $output, NDArray $target) : float
      */
     public function differentiate(NDArray $output, NDArray $target) : NDArray
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         $difference = NumPower::subtract($output, $target);
         $squared = NumPower::pow($difference, 2);

src/NeuralNet/CostFunctions/LeastSquares/LeastSquares.php

@@ -7,7 +7,7 @@
 use NDArray;
 use NumPower;
 use Rubix\ML\NeuralNet\CostFunctions\Base\Contracts\RegressionLoss;
-use Rubix\ML\Traits\ValidatesShapes;
+use Rubix\ML\Traits\AssertsShapes;
 
 /**
  * Least Squares
@@ -22,7 +22,7 @@
  */
 class LeastSquares implements RegressionLoss
 {
-    use ValidatesShapes;
+    use AssertsShapes;
 
     /**
      * Compute the loss score.
@@ -35,7 +35,7 @@ class LeastSquares implements RegressionLoss
      */
     public function compute(NDArray $output, NDArray $target) : float
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         $difference = NumPower::subtract($output, $target);
         $squared = NumPower::pow($difference, 2);
@@ -55,7 +55,7 @@ public function compute(NDArray $output, NDArray $target) : float
      */
     public function differentiate(NDArray $output, NDArray $target) : NDArray
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         return NumPower::subtract($output, $target);
     }

src/NeuralNet/CostFunctions/MeanAbsoluteError/MeanAbsoluteError.php

@@ -7,7 +7,7 @@
 use NDArray;
 use NumPower;
 use Rubix\ML\NeuralNet\CostFunctions\Base\Contracts\RegressionLoss;
-use Rubix\ML\Traits\ValidatesShapes;
+use Rubix\ML\Traits\AssertsShapes;
 
 /**
  * Mean Absolute Error
@@ -23,7 +23,7 @@
  */
 class MeanAbsoluteError implements RegressionLoss
 {
-    use ValidatesShapes;
+    use AssertsShapes;
 
     /**
      * Compute the loss score.
@@ -36,7 +36,7 @@ class MeanAbsoluteError implements RegressionLoss
      */
     public function compute(NDArray $output, NDArray $target) : float
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         $difference = NumPower::subtract($output, $target);
         $absolute = NumPower::abs($difference);
@@ -55,7 +55,7 @@ public function compute(NDArray $output, NDArray $target) : float
      */
     public function differentiate(NDArray $output, NDArray $target) : NDArray
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         $difference = NumPower::subtract($output, $target);
 

src/NeuralNet/CostFunctions/RelativeEntropy/RelativeEntropy.php

@@ -7,7 +7,7 @@
 use NDArray;
 use NumPower;
 use Rubix\ML\NeuralNet\CostFunctions\Base\Contracts\ClassificationLoss;
-use Rubix\ML\Traits\ValidatesShapes;
+use Rubix\ML\Traits\AssertsShapes;
 use const Rubix\ML\EPSILON;
 
 /**
@@ -23,7 +23,7 @@
  */
 class RelativeEntropy implements ClassificationLoss
 {
-    use ValidatesShapes;
+    use AssertsShapes;
 
     /**
      * Compute the loss.
@@ -38,7 +38,7 @@ class RelativeEntropy implements ClassificationLoss
      */
     public function compute(NDArray $output, NDArray $target) : float
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         // Clip values to avoid log(0)
         $target = NumPower::clip($target, EPSILON, 1.0);
@@ -64,7 +64,7 @@ public function compute(NDArray $output, NDArray $target) : float
      */
     public function differentiate(NDArray $output, NDArray $target) : NDArray
     {
-        $this->validateShapes($output, $target);
+        $this->assertSameShape($output, $target);
 
         // Clip values to avoid division by zero
         $target = NumPower::clip($target, EPSILON, 1.0);

src/Traits/ValidatesShapes.php renamed to src/Traits/AssertsShapes.php

@@ -17,19 +17,19 @@
  * @package     Rubix/ML
  * @author      Samuel Akopyan <[email protected]>
  */
-trait ValidatesShapes
+trait AssertsShapes
 {
     /**
-     * Validate that output and target have the same shape.
+     * Assert that the output and target NDArrays have identical shapes.
      *
-     * @param NDArray $output
-     * @param NDArray $target
-     * @throws InvalidArgumentException
+     * @param NDArray $output The output array to check.
+     * @param NDArray $target The target array to compare against.
+     * @throws InvalidArgumentException If the shapes do not match.
      */
-    protected function validateShapes(NDArray $output, NDArray $target) : void
+    protected function assertSameShape(NDArray $output, NDArray $target) : void
     {
         if ($output->shape() !== $target->shape()) {
-            throw new InvalidArgumentException('Output and target must have the same shape.');
+            throw new InvalidArgumentException('Output and target must have identical shapes.');
         }
     }
 }