fix(dnn/cuda): fix FuseConvBiasWithZ pass for HSwish activation

GitOrigin-RevId: b290469cb1

src/gopt/impl/inference.cpp

@@ -1875,6 +1875,8 @@ void FuseConvBiasZPass::apply(OptState& state) const {
             auto elem = try_cast_as_op<opr::ElemwiseMultiType>(opr);
             if (elem->param().mode == MultiMode::QFUSE_ADD_RELU)
                 return NonlineMode::RELU;
+            else if (elem->param().mode == MultiMode::QFUSE_ADD_H_SWISH)
+                return NonlineMode::H_SWISH;
         }
         return NonlineMode::IDENTITY;
     };
@@ -1941,7 +1943,8 @@ void FuseConvBiasZPass::apply(OptState& state) const {
         if (elem->input().size() != 2)
             return false;
         if (elem->param().mode != MultiMode::QADD &&
-            elem->param().mode != MultiMode::QFUSE_ADD_RELU)
+            elem->param().mode != MultiMode::QFUSE_ADD_RELU &&
+            elem->param().mode != MultiMode::QFUSE_ADD_H_SWISH)
             return false;
         return try_replace_var_node(opr);
     };

src/gopt/test/inference.cpp

@@ -1701,80 +1701,96 @@ TEST(FuseConvBiasZPass, BlockFuse) {
                 dtype);
     };
 
-    auto x = mkvar("x", {32, 16, 16, 16, 4}, dtype::QuantizedS8(2.5f)),
-         w1 = mkcvar("w1", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
-         b1 = mkcvar("b1", {1, 16, 1, 1, 4}, dtype::QuantizedS32(6.25f)),
-         w2 = mkcvar("w2", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
-         b2 = mkcvar("b2", {1, 16, 1, 1, 4}, dtype::QuantizedS32(6.25f)),
-         w3 = mkcvar("w3", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
-         b3 = mkcvar("b3", {1, 16, 1, 1, 4}, dtype::QuantizedS32(3.0f));
+    using ElemMultiMode = opr::ElemwiseMultiType::Param::Mode;
+    using NonlineMode = opr::ConvBias::Param::NonlineMode;
+    for (auto mode :
+         {ElemMultiMode::QFUSE_ADD_RELU, ElemMultiMode::QFUSE_ADD_H_SWISH}) {
+        auto x = mkvar("x", {32, 16, 16, 16, 4}, dtype::QuantizedS8(2.5f)),
+             w1 = mkcvar("w1", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
+             b1 = mkcvar("b1", {1, 16, 1, 1, 4}, dtype::QuantizedS32(6.25f)),
+             w2 = mkcvar("w2", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
+             b2 = mkcvar("b2", {1, 16, 1, 1, 4}, dtype::QuantizedS32(6.25f)),
+             w3 = mkcvar("w3", {64, 16, 3, 3, 4}, dtype::QuantizedS8(2.5f)),
+             b3 = mkcvar("b3", {1, 16, 1, 1, 4}, dtype::QuantizedS32(3.0f));
+        NonlineMode nonline_mode = NonlineMode::RELU;
+        if (mode == ElemMultiMode::QFUSE_ADD_H_SWISH) {
+            nonline_mode = NonlineMode::H_SWISH;
+        }
 
-    opr::ConvBias::Param param;
-    param.format = opr::Convolution::Param::Format::NCHW4;
-    param.nonlineMode = opr::ConvBias::Param::NonlineMode::RELU;
-    param.stride_h = param.stride_w = 1;
-    param.pad_h = param.pad_w = 1;
+        opr::ConvBias::Param param;
+        param.format = opr::Convolution::Param::Format::NCHW4;
+        param.nonlineMode = nonline_mode;
+        param.stride_h = param.stride_w = 1;
+        param.pad_h = param.pad_w = 1;
 
-    auto y1 = opr::ConvBias::make(x, w1, b1, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
-    param.nonlineMode = opr::ConvBias::Param::NonlineMode::IDENTITY;
-    auto y2 = opr::ConvBias::make(y1, w2, b2, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
-         y3 = opr::ElemwiseMultiType::make(
-                 {y1, y2},
-                 {opr::ElemwiseMultiType::Param::Mode::QFUSE_ADD_RELU},
-                 OperatorNodeConfig{dtype::QuantizedS8(1.2f)});
-    param.nonlineMode = opr::ConvBias::Param::NonlineMode::RELU;
-    auto y4 = opr::ConvBias::make(y3, w3, b3, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
-         z = opr::ElemwiseMultiType::make(
-                 {y3, y4},
-                 {opr::ElemwiseMultiType::Param::Mode::QADD},
-                 OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
-    z = opr::TypeCvt::make(z, dtype::Float32());
-
-    //! fuse z mannually
-    auto z0 = opr::ConvBias::make(x, w1, b1, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
-    auto z1 = opr::ConvBias::make(z0, w2, b2, z0, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(1.2f)}),
-         z2 = opr::ConvBias::make(z1, w3, b3, param, {},
-                                  OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
-         z4 = opr::ElemwiseMultiType::make(
-                 {z1, z2}, {opr::ElemwiseMultiType::Mode::QADD},
-                 OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
-    z4 = opr::TypeCvt::make(z4, dtype::Float32());
-
-    SymbolVar z_fuse;
-    SymbolVar z_nonfuse;
-    {
-        auto options = gopt::OptimizeForInferenceOptions{};
-        options.enable_fuse_conv_bias_nonlinearity()
-                .enable_fuse_conv_bias_with_z();
-        unpack_vector(gopt::optimize_for_inference({z}, options), z_fuse);
-    }
-    {
-        auto options = gopt::OptimizeForInferenceOptions{};
-        options.enable_fuse_conv_bias_nonlinearity();
-        unpack_vector(gopt::optimize_for_inference({z4}, options), z_nonfuse);
-    }
-    auto nr_elem_multi_type = find_opr_num<mgb::opr::ElemwiseMultiType>(z_fuse);
-    MGB_MARK_USED_VAR(nr_elem_multi_type);
-    ASSERT_EQ(1u, nr_elem_multi_type);
-    graph->compile({{z_fuse, {}}})
-            ->to_json()
-            ->writeto_fpath(
-                    output_file("FuseConvBiasZPass.BlockFuse_fuse.json"));
-    graph->compile({{z_nonfuse, {}}})
-            ->to_json()
-            ->writeto_fpath(
-                    output_file("FuseConvBiasZPass.BlockFuse_nonfuse.json"));
-
-    HostTensorND host_z_fuse, host_z_nonfuse;
-    auto func = graph->compile({make_callback_copy(z_nonfuse, host_z_nonfuse),
+        auto y1 = opr::ConvBias::make(
+                x, w1, b1, param, {},
+                OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
+        param.nonlineMode = opr::ConvBias::Param::NonlineMode::IDENTITY;
+        auto y2 = opr::ConvBias::make(
+                     y1, w2, b2, param, {},
+                     OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
+             y3 = opr::ElemwiseMultiType::make(
+                     {y1, y2}, {mode},
+                     OperatorNodeConfig{dtype::QuantizedS8(1.2f)});
+        param.nonlineMode = nonline_mode;
+        auto y4 = opr::ConvBias::make(
+                     y3, w3, b3, param, {},
+                     OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
+             z = opr::ElemwiseMultiType::make(
+                     {y3, y4}, {opr::ElemwiseMultiType::Param::Mode::QADD},
+                     OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
+        z = opr::TypeCvt::make(z, dtype::Float32());
+
+        //! fuse z mannually
+        auto z0 = opr::ConvBias::make(
+                x, w1, b1, param, {},
+                OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
+        auto z1 = opr::ConvBias::make(
+                     z0, w2, b2, z0, param, {},
+                     OperatorNodeConfig{dtype::QuantizedS8(1.2f)}),
+             z2 = opr::ConvBias::make(
+                     z1, w3, b3, param, {},
+                     OperatorNodeConfig{dtype::QuantizedS8(2.5f)}),
+             z4 = opr::ElemwiseMultiType::make(
+                     {z1, z2}, {opr::ElemwiseMultiType::Mode::QADD},
+                     OperatorNodeConfig{dtype::QuantizedS8(2.5f)});
+        z4 = opr::TypeCvt::make(z4, dtype::Float32());
+
+        SymbolVar z_fuse;
+        SymbolVar z_nonfuse;
+        {
+            auto options = gopt::OptimizeForInferenceOptions{};
+            options.enable_fuse_conv_bias_nonlinearity()
+                    .enable_fuse_conv_bias_with_z();
+            unpack_vector(gopt::optimize_for_inference({z}, options), z_fuse);
+        }
+        {
+            auto options = gopt::OptimizeForInferenceOptions{};
+            options.enable_fuse_conv_bias_nonlinearity();
+            unpack_vector(gopt::optimize_for_inference({z4}, options),
+                          z_nonfuse);
+        }
+        auto nr_elem_multi_type =
+                find_opr_num<mgb::opr::ElemwiseMultiType>(z_fuse);
+        MGB_MARK_USED_VAR(nr_elem_multi_type);
+        ASSERT_EQ(1u, nr_elem_multi_type);
+        graph->compile({{z_fuse, {}}})
+                ->to_json()
+                ->writeto_fpath(
+                        output_file("FuseConvBiasZPass.BlockFuse_fuse.json"));
+        graph->compile({{z_nonfuse, {}}})
+                ->to_json()
+                ->writeto_fpath(output_file(
+                        "FuseConvBiasZPass.BlockFuse_nonfuse.json"));
+
+        HostTensorND host_z_fuse, host_z_nonfuse;
+        auto func =
+                graph->compile({make_callback_copy(z_nonfuse, host_z_nonfuse),
                                 make_callback_copy(z_fuse, host_z_fuse)});
-    func->execute();
-    MGB_ASSERT_TENSOR_EQ(host_z_fuse, host_z_nonfuse);
+        func->execute();
+        MGB_ASSERT_TENSOR_EQ(host_z_fuse, host_z_nonfuse);
+    }
 }
 
 TEST(TestEnableTensorCore, ShuffleMerge) {