[PIR] onednn ops yaml2

paddle/fluid/pir/dialect/operator/ir/ops_onednn_extra.yaml

@@ -25,7 +25,7 @@
   extra_args : bool fuse_with_relu=false
   data_format_tensors : x, out_grad
 
-- op : bilinear_interp
+# - op : bilinear_interp
 
 # - op : cast
 
@@ -165,7 +165,7 @@
 
 - op : mish_grad
 
-- op : multi_gru
+# - op : multi_gru
 
 - op : multiply
 
@@ -255,10 +255,8 @@
 - op : subtract_grad
 
 - op : sum
-  extra_args : str mkldnn_data_type="float32"
 
 - op : sum_grad
-  extra_args : str mkldnn_data_type="float32"
 
 # - op : swish
 

test/legacy_test/test_activation_op.py

@@ -83,10 +83,7 @@ def test_check_output(self):
     def test_check_grad(self):
         if self.dtype == np.float16:
             return
-        self.check_grad(
-            ['X'],
-            'Out',
-        )
+        self.check_grad(['X'], 'Out', check_pir_onednn=self.check_pir_onednn)
 
     def init_dtype(self):
         self.dtype = np.float64

test/mkldnn/test_gaussian_random_mkldnn_op.py

@@ -24,12 +24,14 @@
 class TestMKLDNNGaussianRandomOpSeed10(TestGaussianRandomOp):
     def init_kernel_type(self):
         self.use_mkldnn = True
+        self.check_pir_onednn = True
 
 
 class TestMKLDNNGaussianRandomOpSeed0(TestGaussianRandomOp):
     def setUp(self):
         TestGaussianRandomOp.setUp(self)
         self.use_mkldnn = True
+        self.check_pir_onednn = True
         self.attrs = {
             "shape": [123, 92],
             "mean": 1.0,

test/mkldnn/test_reduce_mkldnn_op.py

@@ -27,14 +27,25 @@ def setUp(self):
         self.inputs = {'X': np.random.random((5, 6, 10)).astype("float32")}
         self.outputs = {'Out': self.inputs['X'].sum(axis=0)}
         self.attrs = {'use_mkldnn': self.use_mkldnn}
+        self.check_pir_onednn = True
 
     def test_check_output(self):
-        self.check_output(check_dygraph=False, check_pir=False)
+        self.check_output(
+            check_dygraph=False,
+            check_pir=False,
+            check_pir_onednn=self.check_pir_onednn,
+        )
 
 
 class TestReduceDefaultWithGradOneDNNOp(TestReduceSumDefaultOneDNNOp):
     def test_check_grad(self):
-        self.check_grad(['X'], 'Out', check_dygraph=False, check_pir=False)
+        self.check_grad(
+            ['X'],
+            'Out',
+            check_dygraph=False,
+            check_pir=False,
+            check_pir_onednn=self.check_pir_onednn,
+        )
 
 
 class TestReduceSum4DOneDNNOp(TestReduceDefaultWithGradOneDNNOp):
@@ -96,6 +107,7 @@ def setUp(self):
         self.outputs = {
             'Out': self.inputs['X'].sum(keepdims=self.attrs['keep_dim'])
         }
+        self.check_pir_onednn = False
 
 
 class TestReduceSum4DReduceAllOneDNNOp(TestReduceDefaultWithGradOneDNNOp):
@@ -105,6 +117,7 @@ def setUp(self):
         self.inputs = {'X': np.random.random((5, 6, 2, 10)).astype("float32")}
         self.attrs = {'reduce_all': True, 'use_mkldnn': self.use_mkldnn}
         self.outputs = {'Out': self.inputs['X'].sum()}
+        self.check_pir_onednn = False
 
 
 @OpTestTool.skip_if(
@@ -238,6 +251,7 @@ def setUp(self):
             'Out': self.inputs['X'].sum()
             / np.asarray(self.inputs['X'].shape).prod()
         }
+        self.check_pir_onednn = False
 
 
 if __name__ == '__main__':