Merge pull request #9 from dantp-ai/solution/task0_3

Implement reduce

Author: dantp-ai

minitorch/operators.py

@@ -197,17 +197,21 @@ def reduce(
          $x_1 \ldots x_n$ and computes the reduction :math:`fn(x_3, fn(x_2,
          fn(x_1, x_0)))`
     """
-    # TODO: Implement for Task 0.3.
-    raise NotImplementedError("Need to implement for Task 0.3")
+
+    def new_fn(ls: Iterable[float]) -> float:
+        res = start
+        for x in ls:
+            res = fn(res, x)
+        return res
+
+    return new_fn
 
 
 def sum(ls: Iterable[float]) -> float:
     "Sum up a list using `reduce` and `add`."
-    # TODO: Implement for Task 0.3.
-    raise NotImplementedError("Need to implement for Task 0.3")
+    return reduce(add, 0)(ls)
 
 
 def prod(ls: Iterable[float]) -> float:
     "Product of a list using `reduce` and `mul`."
-    # TODO: Implement for Task 0.3.
-    raise NotImplementedError("Need to implement for Task 0.3")
+    return reduce(mul, 1)(ls)

tests/test_operators.py

@@ -198,8 +198,7 @@ def test_sum_distribute(ls1: List[float], ls2: List[float]) -> None:
     Write a test that ensures that the sum of `ls1` plus the sum of `ls2`
     is the same as the sum of each element of `ls1` plus each element of `ls2`.
     """
-    # TODO: Implement for Task 0.3.
-    raise NotImplementedError("Need to implement for Task 0.3")
+    assert_close(sum(ls1) + sum(ls2), sum(addLists(ls1, ls2)))
 
 
 @pytest.mark.task0_3