[CINN] reopen elementwise_div/cumsum prim+cinn unittest (#51465)

python/paddle/fluid/tests/unittests/test_cumsum_op.py

@@ -117,7 +117,7 @@ class TestSumOp1(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2}
         self.inputs = {'X': np.random.random((5, 6, 10)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=2)}
@@ -134,7 +134,7 @@ class TestSumOp2(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': -1, 'reverse': True}
         self.inputs = {'X': np.random.random((5, 6, 10)).astype("float64")}
         self.outputs = {
@@ -155,7 +155,7 @@ class TestSumOp3(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 1}
         self.inputs = {'X': np.random.random((5, 6, 10)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=1)}
@@ -172,7 +172,7 @@ class TestSumOp4(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 0}
         self.inputs = {'X': np.random.random((5, 6, 10)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=0)}
@@ -189,7 +189,7 @@ class TestSumOp5(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.inputs = {'X': np.random.random((5, 20)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=1)}
 
@@ -222,7 +222,7 @@ class TestSumOp7(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.inputs = {'X': np.random.random((100)).astype("float64")}
         self.outputs = {'Out': self.inputs['X'].cumsum(axis=0)}
 
@@ -263,7 +263,7 @@ class TestSumOpExclusive1(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, "exclusive": True}
         a = np.random.random((4, 5, 20)).astype("float64")
         self.inputs = {'X': a}
@@ -289,7 +289,7 @@ class TestSumOpExclusive2(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, "exclusive": True}
         a = np.random.random((1, 1, 100)).astype("float64")
         self.inputs = {'X': a}
@@ -315,7 +315,7 @@ class TestSumOpExclusive3(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, "exclusive": True}
         a = np.random.random((4, 5, 20)).astype("float64")
         self.inputs = {'X': a}
@@ -341,7 +341,7 @@ class TestSumOpExclusive4(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, "exclusive": True}
         a = np.random.random((1, 1, 100)).astype("float64")
         self.inputs = {'X': a}
@@ -367,7 +367,7 @@ class TestSumOpExclusive5(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, "exclusive": True}
         a = np.random.random((4, 5, 40)).astype("float64")
         self.inputs = {'X': a}
@@ -419,7 +419,7 @@ class TestSumOpReverseExclusive(OpTest):
         self.op_type = "cumsum"
         self.prim_op_type = "prim"
         self.python_api = paddle.cumsum
-        self.enable_cinn = False
+        self.enable_cinn = True
         self.attrs = {'axis': 2, 'reverse': True, "exclusive": True}
         a = np.random.random((4, 5, 6)).astype("float64")
         self.inputs = {'X': a}

python/paddle/fluid/tests/unittests/test_elementwise_div_op.py

@@ -65,7 +65,7 @@ class ElementwiseDivOp(OpTest):
         self.grad_y = grad_y
 
     def if_enable_cinn(self):
-        pass
+        self.enable_cinn = True
 
     def init_args(self):
         self.check_dygraph = True
@@ -136,9 +136,6 @@ class TestElementwiseDivPrimOpFp32(ElementwiseDivOp):
         self.dtype = np.float32
         self.val_dtype = np.float32
 
-    def if_enable_cinn(self):
-        pass
-
 
 class TestElementwiseDivOp_ZeroDim1(ElementwiseDivOp):
     def init_shape(self):
@@ -208,6 +205,9 @@ class TestElementwiseDivOpBF16(ElementwiseDivOp):
     def if_check_prim(self):
         self.check_prim = False
 
+    def if_enable_cinn(self):
+        self.enable_cinn = False
+
 
 @skip_check_grad_ci(
     reason="[skip shape check] Use y_shape(1) to test broadcast."
@@ -375,9 +375,6 @@ class TestElementwiseDivOpXsizeLessThanYsize(ElementwiseDivOp):
     def compute_gradient_x(self, grad_out, y):
         return np.sum(grad_out / y, axis=(0, 1))
 
-    def if_enable_cinn(self):
-        self.enable_cinn = False
-
 
 class TestElementwiseDivOpInt(ElementwiseDivOp):
     def init_dtype(self):
@@ -400,7 +397,7 @@ class TestElementwiseDivOpFp16(ElementwiseDivOp):
         self.val_dtype = np.float16
 
     def if_enable_cinn(self):
-        self.enable_cinn = False
+        self.enable_cinn = True
 
 
 class TestElementwiseDivBroadcast(unittest.TestCase):