diff --git a/assets/demo/demo.html b/assets/demo/demo.html
index 0152e60..d753532 100644
--- a/assets/demo/demo.html
+++ b/assets/demo/demo.html
@@ -26,7 +26,7 @@
         </div>
     
         <div class="separator" id="right-separator" style="margin-top: 10px; display: block;">
-            <p style="display: block; font-size: 16px; color: #292929; margin-bottom: 25px;">Welcome to <b>JS-Torch's Web Demo</b>! You can choose the <b>Model Hyperparameters</b> on the left, set tme <b>Model Layers</b> on the right (number of layers and hidden dimension on each). </p>
+            <p style="display: block; font-size: 16px; color: #292929; margin-bottom: 25px;">Welcome to <b>JS-Torch's Web Demo</b>! You can choose the <b>Model Hyperparameters</b> on the left, set the <b>Model Layers</b> on the right (number of layers and hidden dimension on each). </p>
             <ul> 
                 <li>This model was trained on a <b>Dummy dataset</b>, composed of <b>randomly generated images</b>. </li>
                 <br>
diff --git a/src/tensor.js b/src/tensor.js
index 29e095f..51509ae 100644
--- a/src/tensor.js
+++ b/src/tensor.js
@@ -4,13 +4,13 @@
 
 var torch = (function(exports){
         
-    // <<< Tensor class, holds n-dimentional tensors, and multiple useful methods >>> // 
+    // <<< Tensor class, holds n-dimensional tensors, and multiple useful methods >>> // 
 
     class Tensor {
         /**
          * Creates new instance of the Tensor class.
          * @param {object} data - Iterable containing the data to be stored in the Tensor.
-         * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+         * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
          */
         constructor(data, requires_grad=false) {
             if (typeof data === 'object') {
@@ -132,9 +132,9 @@ var torch = (function(exports){
         };
 
         /**
-         * Gets the sum of the Tensor over a specified dimention.
-         * @param {number} dim - Dimention to sum over.
-         * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+         * Gets the sum of the Tensor over a specified dimension.
+         * @param {number} dim - Dimension to sum over.
+         * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         sum(dim=-1, keepdims=false) {
@@ -143,9 +143,9 @@ var torch = (function(exports){
         };
 
         /**
-         * Gets the mean of the Tensor over a specified dimention.
-         * @param {number} dim - Dimention to get mean over.
-         * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+         * Gets the mean of the Tensor over a specified dimension.
+         * @param {number} dim - Dimension to get mean over.
+         * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         mean(dim=-1, keepdims=false) {
@@ -154,9 +154,9 @@ var torch = (function(exports){
         };
 
         /**
-         * Gets the variance of the Tensor over a specified dimention.
-         * @param {number} dim - Dimention to get variance over.
-         * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+         * Gets the variance of the Tensor over a specified dimension.
+         * @param {number} dim - Dimension to get variance over.
+         * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         variance(dim=-1, keepdims=false) {
@@ -791,10 +791,10 @@ var torch = (function(exports){
 
     class Sum {
         /**
-         * Gets the sum of a Tensor over a specified dimention.
+         * Gets the sum of a Tensor over a specified dimension.
          * @param {Tensor} a - Tensor to sum.
-         * @param {dim} dim - Dimention to sum over.
-         * @param {keepdims} keepdims - Wether to keep dimentions of original tensor.
+         * @param {dim} dim - Dimension to sum over.
+         * @param {keepdims} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         forward(a, dim, keepdims=false) {
@@ -805,7 +805,7 @@ var torch = (function(exports){
             if (dim < 0) {
                 dim = a.shape.length + dim;
             };
-            // Return error if dimention is out of bounds:
+            // Return error if dimension is out of bounds:
             if (dim >= a.shape.length) {
                 throw Error('Dimension larger than array.')
             };
@@ -845,10 +845,10 @@ var torch = (function(exports){
 
     class Mean {
         /**
-         * Gets the mean of a Tensor over a specified dimention.
+         * Gets the mean of a Tensor over a specified dimension.
          * @param {Tensor} a - Tensor to get mean from.
-         * @param {dim} dim - Dimention to get mean over.
-         * @param {keepdims} keepdims - Wether to keep dimentions of original tensor.
+         * @param {dim} dim - Dimension to get mean over.
+         * @param {keepdims} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         forward(a, dim, keepdims=false) {
@@ -856,7 +856,7 @@ var torch = (function(exports){
             if (dim < 0) {
                 dim = a.shape.length + dim;
             };
-            // Return error if dimention is out of bounds:
+            // Return error if dimension is out of bounds:
             if (dim >= a.shape.length) {
                 throw Error('Dimension larger than array.')
             };
@@ -897,10 +897,10 @@ var torch = (function(exports){
 
     class Variance {
         /**
-         * Gets the variance of a Tensor over a specified dimention.
+         * Gets the variance of a Tensor over a specified dimension.
          * @param {Tensor} a - Tensor to get variance of.
-         * @param {dim} dim - Dimention to get variance over.
-         * @param {keepdims} keepdims - Wether to keep dimentions of original tensor.
+         * @param {dim} dim - Dimension to get variance over.
+         * @param {keepdims} keepdims - Whether to keep dimensions of original tensor.
          * @returns {Tensor} - Final tensor.
          */
         forward(a, dim, keepdims=false) {
@@ -908,7 +908,7 @@ var torch = (function(exports){
             if (dim < 0) {
                 dim = a.shape.length + dim;
             };
-            // Return error if dimention is out of bounds:
+            // Return error if dimension is out of bounds:
             if (dim >= a.shape.length) {
                 throw Error('Dimension larger than array.');
             };
@@ -1131,10 +1131,10 @@ var torch = (function(exports){
     // <<< Tensor Operation Aliases >>> //
 
     /**
-     * Gets the sum of the Tensor over a specified dimention.
+     * Gets the sum of the Tensor over a specified dimension.
      * @param {Tensor} a - Original Tensor.
-     * @param {number} dim - Dimention to sum over.
-     * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+     * @param {number} dim - Dimension to sum over.
+     * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
      * @returns {Tensor} - Final tensor.
      */
     function sum(a, dim=-1, keepdims=false) {
@@ -1142,10 +1142,10 @@ var torch = (function(exports){
     };
 
     /**
-     * Gets the mean of the Tensor over a specified dimention.
+     * Gets the mean of the Tensor over a specified dimension.
      * @param {Tensor} a - Original Tensor.
-     * @param {number} dim - Dimention to get mean over.
-     * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+     * @param {number} dim - Dimension to get mean over.
+     * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
      * @returns {Tensor} - Final tensor.
      */
     function mean(a, dim=-1, keepdims=false) {
@@ -1153,10 +1153,10 @@ var torch = (function(exports){
     };
 
     /**
-     * Gets the variance of the Tensor over a specified dimention.
+     * Gets the variance of the Tensor over a specified dimension.
      * @param {Tensor} a - Original Tensor.
-     * @param {number} dim - Dimention to get variance over.
-     * @param {boolean} keepdims - Wether to keep dimentions of original tensor.
+     * @param {number} dim - Dimension to get variance over.
+     * @param {boolean} keepdims - Whether to keep dimensions of original tensor.
      * @returns {Tensor} - Final tensor.
      */
     function variance(a, dim=-1, keepdims=false) {
@@ -1328,7 +1328,7 @@ var torch = (function(exports){
     function _sum(a, dim, keepdims) {
                 
         // In recursive call, when depth increases, subtract one from dim. 
-        // When we reach the dimention intended (dim === 0),
+        // When we reach the dimension intended (dim === 0),
         // we add all elements in this dimension.
         if ( dim == 0 ) {
             let sum = a.reduce((a,b) => _add(a, b), 0);
@@ -1347,7 +1347,7 @@ var torch = (function(exports){
     function _mean(a, dim, keepdims) {
                 
         // In recursive call, when depth increases, subtract one from dim. 
-        // When we reach the dimention intended (dim === 0),
+        // When we reach the dimension intended (dim === 0),
         // we add all elements in this dimension.
         if ( dim == 0 ) {
             let reduced = _div(a.reduce((a,b) => _add(a, b), 0), a.length);
@@ -1366,7 +1366,7 @@ var torch = (function(exports){
     function _variance(a, dim, keepdims) {
                 
         // In recursive call, when depth increases, subtract one from dim. 
-        // When we reach the dimention intended (dim === 0),
+        // When we reach the dimension intended (dim === 0),
         // we add all elements in this dimension.
         if ( dim == 0 ) {
             // Get mean over current dim:
@@ -1744,7 +1744,7 @@ var torch = (function(exports){
     /**
      * Creates new instance of the Tensor class.
      * @param {object} data - Iterable containing the data to be stored in the Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function tensor(data, requires_grad=false) {
@@ -1754,7 +1754,7 @@ var torch = (function(exports){
     /**
      * Creates new instance of the Tensor class filled with only zeros.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function zeros(shape, requires_grad=false) {
@@ -1764,7 +1764,7 @@ var torch = (function(exports){
     /**
      * Creates new instance of the Tensor class filled with only ones.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function ones(shape, requires_grad=false) {
@@ -1774,7 +1774,7 @@ var torch = (function(exports){
     /**
      * Creates new instance of a lower-triangular 2D Tensor.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function tril(shape, requires_grad=false) {
@@ -1793,7 +1793,7 @@ var torch = (function(exports){
     /**
      * Creates new instance of the Tensor class filled with numbers in a uniform distribution in ]0,1[.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function rand(shape, requires_grad=false) {
@@ -1803,8 +1803,8 @@ var torch = (function(exports){
     /**
      * Creates new instance of the Tensor class filled with numbers in a normal distribution.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
-     * @param {boolean} xavier - Wether to use xavier initialization (divide by square root of first input dimension).
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
+     * @param {boolean} xavier - Whether to use xavier initialization (divide by square root of first input dimension).
      * @returns {object} New tensor.
      */
     function randn(shape, requires_grad=false, xavier=false,) {
@@ -1827,7 +1827,7 @@ var torch = (function(exports){
      * @param {number} low - Lowest number that can be sampled.
      * @param {number} high - One above highest number that can be sampled.
      * @param {object} shape - List containing the shape of the new tensor Tensor.
-     * @param {boolean} requires_grad - Wether to keep track of this tensor's gradients.
+     * @param {boolean} requires_grad - Whether to keep track of this tensor's gradients.
      * @returns {object} New tensor.
      */
     function randint(low=0, high=1, shape=[1,], requires_grad=false) {
@@ -1908,10 +1908,10 @@ var torch = (function(exports){
                 function _broadcastSideways (out, b) {
                     if (b.length != out.length) {
                         if (b.length === 1){
-                            // Base case, contract existing dimention:
+                            // Base case, contract existing dimension:
                             return [_sum(out, 0),];
                         } else if (out.length === 1){
-                            // Base case, expand existing dimention:
+                            // Base case, expand existing dimension:
                             emptyArray = Array(b.length).fill(zeros);
                             return emptyArray.map(() => out[0]);
                         } else { Error(`Shapes ${utils.getShape(out)} and ${utils.getShape(b)} not broadcastable.`) };
@@ -1950,7 +1950,7 @@ var torch = (function(exports){
     function broadcastUp (inElement, outElement) {
         function _broadcastUp (inElement, outElement) {
             if (utils.getShape(inElement).length + 1 === utils.getShape(outElement).length) {
-                // Base case, create new dimention:
+                // Base case, create new dimension:
                 emptyArray = Array(outElement.length).fill(zeros);
                 return emptyArray.map(() => inElement);
             } else {