Fix l1loss ci error

oneflow/python/nn/modules/loss.py

@@ -99,7 +99,7 @@ def forward(self, input, target):
             input.shape == target.shape
         ), "The Input shape must be the same as Target shape"
 
-        l1_value = flow.experimental.abs(flow.experimental.sub(target, input))
+        l1_value = flow.experimental.abs(flow.experimental.sub(input, target))
         if self.reduction == "mean":
             return flow.experimental.mean(l1_value)
         elif self.reduction == "sum":

oneflow/python/test/modules/test_l1loss.py

@@ -36,7 +36,8 @@ def _np_l1loss(np_input, np_target):
 
 def _np_l1loss_grad(np_input, np_target):
     elem_cnt = np_input.size
-    np_grad = np.where(np_target - np_input > 0, -1, 1)
+    np_grad = np.zeros_like(np_target)
+    np_grad = np.sign(np_input - np_target)
     np_l1_grad_sum = np_grad
     np_l1_grad_mean = np_l1_grad_sum / elem_cnt
 
@@ -48,8 +49,8 @@ def _np_l1loss_grad(np_input, np_target):
 
 
 def _test_l1loss_impl(test_case, device, shape, reduction):
-    x = np.random.randn(*shape)
-    y = np.random.randn(*shape)
+    x = np.random.randn(*shape).astype(np.float32)
+    y = np.random.randn(*shape).astype(np.float32)
     input = flow.Tensor(
         x, dtype=flow.float32, requires_grad=True, device=flow.device(device)
     )

oneflow/user/kernels/math_unary_elementwise_func.h

@@ -46,7 +46,12 @@ template<typename T>
 struct AbsFunctor {
   static OF_DEVICE_FUNC const T Forward(const T x) { return x < T(0) ? -x : x; }
 
-  static OF_DEVICE_FUNC const T Backward(const T x, const T dy) { return x < T(0) ? -dy : dy; }
+  static OF_DEVICE_FUNC const T Backward(const T x, const T dy) {
+    if (x == T(0))
+      return T(0);
+    else
+      return x < T(0) ? -dy : dy;
+  }
 };
 
 template<typename T>