Added ELU FP32 FWD/BWD oneDNN kernel

paddle/fluid/operators/activation_op.cc

@@ -568,6 +568,10 @@ class ELUOpMaker : public framework::OpProtoAndCheckerMaker {
               "The output is a multi-dimensional Tensor which has same "
               "dimension and data type as the ``x``.");
     AddAttr<float>("alpha", "The alpha value of ELU").SetDefault(1.0f);
+    AddAttr<bool>("use_mkldnn",
+                  "(bool, default false) Only used in mkldnn kernel")
+        .SetDefault(false)
+        .AsExtra();
     AddComment(R"DOC(
 ELU Activation Operator.
 
@@ -743,6 +747,10 @@ class HardSwishOpMaker : public framework::OpProtoAndCheckerMaker {
         .SetDefault(6.0f);
     AddAttr<float>("offset", "The offset parameter of HardSwish operator")
         .SetDefault(3.0f);
+    AddAttr<bool>("use_mkldnn",
+                  "(bool, default false) Only used in mkldnn kernel")
+        .SetDefault(false)
+        .AsExtra();
     AddComment(R"DOC(
 HardSwish Activation Operator.
 

paddle/fluid/operators/mkldnn/activation_mkldnn_op.cc

@@ -209,6 +209,10 @@ template <typename T>
 using AbsMKLDNNFunctor =
     MKLDNNActivationFunc<T, mkldnn::algorithm::eltwise_abs>;
 
+template <typename T>
+using EluMKLDNNFunctor =
+    MKLDNNActivationFunc<T, mkldnn::algorithm::eltwise_elu>;
+
 template <typename T>
 using ReluMKLDNNGradFunctor =
     MKLDNNActivationGradFunc<T, mkldnn::algorithm::eltwise_relu>;
@@ -240,6 +244,10 @@ using SqrtMKLDNNGradFunctor =
 template <typename T>
 using AbsMKLDNNGradFunctor =
     MKLDNNActivationGradFunc<T, mkldnn::algorithm::eltwise_abs>;
+
+template <typename T>
+using EluMKLDNNGradFunctor =
+    MKLDNNActivationGradFunc<T, mkldnn::algorithm::eltwise_elu>;
 }  // namespace operators
 }  // namespace paddle
 
@@ -264,14 +272,15 @@ namespace ops = paddle::operators;
       ops::MKLDNNActivationGradKernel<                                        \
           ops::grad_functor<paddle::platform::bfloat16>>);
 
-#define FOR_EACH_MKLDNN_KERNEL_FUNCTOR(__macro)                           \
-  __macro(relu6, Relu6MKLDNNFunctor, Relu6MKLDNNGradFunctor);             \
-  __macro(leaky_relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor);          \
-  __macro(swish, SwishMKLDNNFunctor, SwishMKLDNNGradFunctor);             \
-  __macro(hardswish, HardSwishMKLDNNFunctor, HardSwishMKLDNNGradFunctor); \
-  __macro(tanh, TanhMKLDNNFunctor, TanhMKLDNNGradFunctor);                \
-  __macro(sqrt, SqrtMKLDNNFunctor, SqrtMKLDNNGradFunctor);                \
-  __macro(abs, AbsMKLDNNFunctor, AbsMKLDNNGradFunctor);
+#define FOR_EACH_MKLDNN_KERNEL_FUNCTOR(__macro)                            \
+  __macro(relu6, Relu6MKLDNNFunctor, Relu6MKLDNNGradFunctor);              \
+  __macro(leaky_relu, ReluMKLDNNFunctor, ReluMKLDNNGradFunctor);           \
+  __macro(swish, SwishMKLDNNFunctor, SwishMKLDNNGradFunctor);              \
+  __macro(hard_swish, HardSwishMKLDNNFunctor, HardSwishMKLDNNGradFunctor); \
+  __macro(tanh, TanhMKLDNNFunctor, TanhMKLDNNGradFunctor);                 \
+  __macro(sqrt, SqrtMKLDNNFunctor, SqrtMKLDNNGradFunctor);                 \
+  __macro(abs, AbsMKLDNNFunctor, AbsMKLDNNGradFunctor);                    \
+  __macro(elu, EluMKLDNNFunctor, EluMKLDNNGradFunctor);
 
 FOR_EACH_MKLDNN_KERNEL_FUNCTOR(REGISTER_ACTIVATION_MKLDNN_KERNEL);
 REGISTER_ACTIVATION_MKLDNN_BF16_KERNEL(relu, ReluMKLDNNFunctor,

python/paddle/fluid/tests/unittests/mkldnn/test_activation_mkldnn_op.py

@@ -326,6 +326,29 @@ def setUp(self):
         self.attrs = {"use_mkldnn": True}
 
 
+class TestMKLDNNEluDefaultAlpha(TestActivation):
+    def setUp(self):
+        self.op_type = "elu"
+        self.set_alpha()
+
+        x = np.random.random((5, 5, 4)).astype("float32")
+
+        self.inputs = {'X': x}
+        self.attrs = {'use_mkldnn': True, 'alpha': self.alpha}
+        self.outputs = {
+            'Out':
+            np.maximum(0, x) + np.minimum(0, self.alpha * (np.exp(x) - 1))
+        }
+
+    def set_alpha(self):
+        self.alpha = 1.0
+
+
+class TestMKLDNNEluCustomAlpha(TestMKLDNNEluDefaultAlpha):
+    def set_alpha(self):
+        self.alpha = 2.5
+
+
 # Check if primitives already exist in backward
 class TestMKLDNNAbsPrimitivesAlreadyExist(unittest.TestCase):
     def setUp(self):