[HEU][Paddle TensorRT No.3,67] Add pd_op.selu pd_op.relu6 converter

paddle/fluid/pir/transforms/tensorrt/trt_op_marker_pass.cc

@@ -59,6 +59,7 @@ DEFINE_GENERAL_PATTERN(Bmm, paddle::dialect::BmmOp)
 DEFINE_GENERAL_PATTERN(Concat, paddle::dialect::ConcatOp)
 DEFINE_GENERAL_PATTERN(Nonzero, paddle::dialect::NonzeroOp)
 DEFINE_GENERAL_PATTERN(Gelu, paddle::dialect::GeluOp)
+DEFINE_GENERAL_PATTERN(Relu6, paddle::dialect::Relu6Op)
 DEFINE_GENERAL_PATTERN(Fused_gemm_epilogue,
                        paddle::dialect::FusedGemmEpilogueOp)
 DEFINE_GENERAL_PATTERN(Layer_norm, paddle::dialect::LayerNormOp)
@@ -85,6 +86,7 @@ DEFINE_GENERAL_PATTERN(Log, paddle::dialect::LogOp)
 DEFINE_GENERAL_PATTERN(Floor, paddle::dialect::FloorOp)
 DEFINE_GENERAL_PATTERN(Roll, paddle::dialect::RollOp)
 DEFINE_GENERAL_PATTERN(Elu, paddle::dialect::EluOp)
+DEFINE_GENERAL_PATTERN(Selu, paddle::dialect::SeluOp)
 DEFINE_GENERAL_PATTERN(Stanh, paddle::dialect::StanhOp)
 DEFINE_GENERAL_PATTERN(Softplus, paddle::dialect::SoftplusOp)
 DEFINE_GENERAL_PATTERN(ThresholdedRelu, paddle::dialect::ThresholdedReluOp)
@@ -2195,6 +2197,7 @@ class TrtOpMarkerPass : public pir::PatternRewritePass {
     ADD_PATTERN(DepthwiseConv2d)
     ADD_PATTERN(Nonzero)
     ADD_PATTERN(Gelu)
+    ADD_PATTERN(Relu6)
     ADD_PATTERN(Shape)
     ADD_PATTERN(Shape64)
     ADD_PATTERN(Expand)
@@ -2212,6 +2215,7 @@ class TrtOpMarkerPass : public pir::PatternRewritePass {
     ADD_PATTERN(Floor)
     ADD_PATTERN(Roll)
     ADD_PATTERN(Elu)
+    ADD_PATTERN(Selu)
     ADD_PATTERN(Stanh)
     ADD_PATTERN(Softplus)
     ADD_PATTERN(ThresholdedRelu)

python/paddle/tensorrt/impls/activation.py

@@ -45,6 +45,14 @@ def activation_converter(network, paddle_op, inputs):
     return layer.get_output(0)
 
 
+@converter_registry.register("pd_op.relu6", trt_version="trt_version_ge=8.0")
+def relu6_converter(network, paddle_op, inputs):
+    layer = network.add_activation(inputs[0], trt.ActivationType.CLIP)
+    layer.alpha = 0.0
+    layer.beta = 6.0
+    return layer.get_output(0)
+
+
 @converter_registry.register("pd_op.softmax", trt_version="trt_version_ge=8.0")
 def softmax_converter(network, paddle_op, inputs):
     axis = paddle_op.attrs().get("axis", 0)
@@ -243,3 +251,14 @@ def thresholded_relu_converter(network, paddle_op, inputs):
     )
     thresholded_relu_layer.alpha = threshold
     return thresholded_relu_layer.get_output(0)
+
+
+@converter_registry.register("pd_op.selu", trt_version="8.x")
+def selu_converter(network, paddle_op, inputs):
+    x = inputs[0]
+    alpha = paddle_op.attrs()["alpha"]
+    scale = paddle_op.attrs()["scale"]
+    selu_layer = network.add_activation(x, trt.ActivationType.SELU)
+    selu_layer.alpha = alpha
+    selu_layer.beta = scale
+    return selu_layer.get_output(0)

test/tensorrt/test_converter_activation.py

@@ -90,6 +90,21 @@ def test_trt_result(self):
         self.check_trt_result()
 
 
+class TestRelu6TRTPattern(TensorRTBaseTest):
+    def setUp(self):
+        self.python_api = paddle.nn.functional.relu6
+        self.api_args = {"x": np.random.randn(3).astype("float32")}
+        self.program_config = {"feed_list": ["x"]}
+        self.min_shape = {"x": [1]}
+        self.max_shape = {"x": [5]}
+
+    def test_trt_result(self):
+        self.check_trt_result()
+
+    def test_trt_result_fp16(self):
+        self.check_trt_result(precision_mode="fp16")
+
+
 class TestTanhTRTPattern(TensorRTBaseTest):
     def setUp(self):
         self.python_api = paddle.tanh
@@ -291,5 +306,22 @@ def test_trt_result(self):
         self.check_trt_result()
 
 
+class TestSeluTRTPattern(TensorRTBaseTest):
+    def setUp(self):
+        self.python_api = paddle.nn.functional.selu
+        self.api_args = {
+            "x": np.random.randn(2, 3).astype("float32"),
+        }
+        self.program_config = {"feed_list": ["x"]}
+        self.min_shape = {"x": [1, 3]}
+        self.max_shape = {"x": [5, 3]}
+
+    def test_trt_result(self):
+        self.check_trt_result()
+
+    def test_trt_result_fp16(self):
+        self.check_trt_result(precision_mode="fp16")
+
+
 if __name__ == '__main__':
     unittest.main()