work more on tensors.

lib/src/splat/tensor.dart

@@ -50,6 +50,16 @@ List<dynamic> listBroadcast(List<dynamic> l1, List<dynamic> l2,
   });
 }
 
+List<dynamic> listStack(List<List<dynamic>> lists, int dim) {
+  List<dynamic> newData = [];
+
+  for (int i = 0; i < lists.first.data.length; ++i) {
+    List<dynamic> subData = lists.map((l => l.data[i]))
+  }
+
+  return newData;
+}
+
 class Tensor {
   List<dynamic> data = [];
   List<int> shape = [];
@@ -84,48 +94,30 @@ class Tensor {
     return data.equals(other.data);
   }
 
-// Static method 'stack' that takes a list of Tensors and optionally an integer `dim` as arguments,
+  static Tensor cat(List<Tensor> tensors) {
-// implementing pytorch's stack method.
+    return Tensor.fromList(tensors.map((el) {
-  static Tensor stack(List<Tensor> tensors, [int dim = 0]) {
+      return el.data;
-    // If the provided dimension is less than 0 or greater than the number of dimensions in all Tensors, use 0 as the default value for dim.
+    }).toList());
-    dim = (dim < 0 || tensors.any((tensor) => tensor.shape.length <= dim))
+  }
-        ? 0
-        : dim;
 
-    List<dynamic> newShape = [
+  static Tensor stack(List<Tensor> tensors, {int dim = 0}) {
-      ...List<dynamic>.filled(tensors.length, 1),
+    int maxShape = tensors.map((Tensor t) {
-      ...tensors[0].shape
+      return t.shape.max;
-    ];
+    }).max;
-
+    if (dim < 0 || dim > maxShape) {
-    // If the provided dimension is not the first dimension of all Tensors, adjust the shape accordingly.
+      throw Exception("Invalid dimension");
-    if (dim > 0) {
-      for (var i = 0; i < tensors.length; i++) {
-        newShape[i] *= tensors[i].shape[dim];
-      }
     }
-
+    List<double> newList = [];
-    // If the provided dimension is not the first dimension of all Tensors, adjust the shape accordingly.
+    List<int> path = [];
-    if (dim > 0) {
+    for (int i = 0; i < tensors.length; i++) {
-      for (var i = 0; i < tensors.length; i++) {
-        newShape[i] *= tensors[i].shape[dim];
-      }
     }
+  }
 
-    List<dynamic> stackedData = [];
+  List<dynamic> toList({int depth = 0}) {
-
+    if (depth == 0 || ((data.length > 0 && this.data[0].runtimetype == double))) {
-    // Iterate through the data of each tensor and concatenate it to the stackedData list.
+      return data
-    for (var i = 0; i < newShape[0]; i++) {
-      int currentIndex = 0;
-      for (var j = 0; j < tensors.length; j++) {
-        if (i >= currentIndex * tensors[j].shape[dim] &&
-            i < (currentIndex + 1) * tensors[j].shape[dim]) {
-          stackedData.add(tensors[j].data[currentIndex]);
-          currentIndex++;
-        }
-      }
     }
-
+    return data.map((d) { return d.toList(depth-1) })
-    return Tensor.fromList(stackedData);
   }
 
   operator *(Tensor other) {

lib/src/test/splat/tensor_test.dart

@@ -79,22 +79,27 @@ void main() {
 
   test("tensors can be stacked", () {
     List<List<double>> l = [
-      [0.3367, 0.1288, 02345],
+      [1, 2, 3],
-      [0.2303, -1.1229, -0.1863]
+      [4, 5, 6]
     ];
     Tensor baseTensor = Tensor.fromList(l);
     Tensor stacked_1 = Tensor.stack([baseTensor, baseTensor]);
-    expect(
+    Tensor expectedStacked1 = Tensor.fromList([l, l]);
-        stacked_1.data,
+    expect(stacked_1.equals(expectedStacked1), isTrue);
-        equals([
+
-          [
+    List<List<List<double>>> ld1 = [
-            [0.3367, 0.1288, 0.2345],
+      [
-            [0.2303, -1.1229, -0.1863]
+        [1, 2, 3],
-          ],
+        [1, 2, 3],
-          [
+      ],
-            [0.3367, 0.1288, 0.2345],
+      [
-            [0.2303, -1.1229, -0.1863]
+        [4, 5, 6],
-          ]
+        [4, 5, 6]
-        ]));
+      ]
+    ];
+
+    Tensor stacked_2 = Tensor.stack([baseTensor, baseTensor], dim: 1);
+    Tensor expectedStacked2 = Tensor.fromList(ld1);
+    expect(stacked_2.equals(expectedStacked2), isTrue);
   });
 }