Merge pull request #41 from basalt-org/matmul

Author: Benny-Nottonson

.gitignore

@@ -5,6 +5,7 @@ basalt.📦
 
 examples/data/mnist_test.csv
 examples/data/mnist_train.csv
+examples/data/mnist_train_small.csv
 
 output_model.onnx
 Makefile

basalt/autograd/graph.mojo

@@ -57,9 +57,7 @@ struct Graph:
         self.symbol_count += 1
         return scalar_id
 
-    fn constant(
-        inout self, shape: TensorShape, data: List[SIMD[dtype, 1]]
-    ) -> Symbol:
+    fn constant(inout self, shape: TensorShape, data: List[SIMD[dtype, 1]]) -> Symbol:
         var cst = Param(data)
         var constant_id = Symbol(self.symbol_count, dtype, shape, trainable=False)
         self.params.put(constant_id, cst)
@@ -111,9 +109,7 @@ struct Graph:
                 self.result_trainable(operand_1),
             )
 
-        self.nodes.append(
-            Node(op, res, operand_1, operand_2, operand_3, attributes)
-        )
+        self.nodes.append(Node(op, res, operand_1, operand_2, operand_3, attributes))
         self.symbol_count += 1
         return res
 

basalt/autograd/ops/basics.mojo

@@ -177,6 +177,7 @@ struct DIV:
                         / (t2.load[nelts](index2) ** 2)
                         * ug.load[nelts](i),
                     )
+
                 vectorize[vec_div_bw_broadcast, 1](ug_shape.num_elements())
 
             else:
@@ -257,9 +258,7 @@ struct EXP:
 
         @parameter
         fn vec_exp_bw[nelts: Int](i: Int):
-            res_grad.store[nelts](
-                i, exp(t1.load[nelts](i)) * ug.load[nelts](i)
-            )
+            res_grad.store[nelts](i, exp(t1.load[nelts](i)) * ug.load[nelts](i))
 
         vectorize[vec_exp_bw, nelts](ug_shape.num_elements())
         return res_grad ^