[Doc] Update data_oriented_class.md (#6181)

docs/lang/articles/advanced/data_oriented_class.md

@@ -71,16 +71,12 @@ ti.init()
 @ti.data_oriented
 class Calc:
     def __init__(self):
-        self.x = ti.field(dtype=ti.f32, shape=16)
-        self.y = ti.field(dtype=ti.f32, shape=4)
+        self.x = ti.field(dtype=ti.f32, shape=8)
 
     @ti.kernel
     def func(self, temp: ti.template()):
         for i in range(8):
-            temp[i] = self.x[i * 2] + self.x[i * 2 + 1]
-
-        for i in range(4):
-            self.y[i] = max(temp[i * 2], temp[i * 2 + 1])
+            temp[i] = self.x[i * 2]
 
     def call_func(self):
         fb = ti.FieldsBuilder()
@@ -171,65 +167,13 @@ ti.init()
 
 @ti.data_oriented
 class Array2D:
-    def __init__(self, n, m, increment):
-        self.n = n
-        self.m = m
-        self.val = ti.field(ti.f32)
-        self.total = ti.field(ti.f32)
-        self.increment = float(increment)
-        ti.root.dense(ti.ij, (self.n, self.m)).place(self.val)
-        ti.root.place(self.total)
+    def __init__(self, n):
+        self.arr = ti.Vector([0.] * n)
 
     @staticmethod
     @ti.func
     def clamp(x):  # Clamp to [0, 1)
-        return max(0., min(1 - 1e-6, x))
-
-    @ti.kernel
-    def inc(self):
-        for i, j in self.val:
-            ti.atomic_add(self.val[i, j], self.increment)
-
-    @ti.kernel
-    def inc2(self, increment: ti.i32):
-        for i, j in self.val:
-            ti.atomic_add(self.val[i, j], increment)
-
-    @ti.kernel
-    def reduce(self):
-        for i, j in self.val:
-            ti.atomic_add(self.total[None], self.val[i, j] * 4)
-
-arr = Array2D(2, 2, 3)
-
-double_total = ti.field(ti.f32, shape=())
-
-ti.root.lazy_grad()
-
-arr.inc()
-arr.inc.grad()
-print(arr.val[0, 0])  # 3
-arr.inc2(4)
-print(arr.val[0, 0])  # 7
-
-with ti.ad.Tape(loss=arr.total):
-    arr.reduce()
-
-for i in range(arr.n):
-    for j in range(arr.m):
-        print(arr.val.grad[i, j])  # 4
-
-@ti.kernel
-def double():
-    double_total[None] = 2 * arr.total[None]
-
-with ti.ad.Tape(loss=double_total):
-    arr.reduce()
-    double()
-
-for i in range(arr.n):
-    for j in range(arr.m):
-        print(arr.val.grad[i, j])  # 8
+        return max(0, min(1, x))
 ```
 
 `classmethod` example: