fix(gopt): gen nchw_nchw44 when kernel is optimized

GitOrigin-RevId: 89083be200

src/gopt/impl/tensor_reformat.cpp

@@ -1811,7 +1811,15 @@ VarNode* EnableNchwxxPass::on_graph_endpoint_var(VarNode* new_var,
     }
     return new_var;
 }
-
+//! nchw_nchwxx_valid is used to indicate optimized nchw_nchw44 conv
+static inline bool nchw_nchwxx_valid(const size_t oc, const size_t ic,
+                                     const size_t pack_c_size, const size_t fh,
+                                     const size_t fw, const size_t stride_h,
+                                     const size_t stride_w) {
+    return ic < pack_c_size && oc % pack_c_size == 0 && fh == fw &&
+           stride_h == stride_w && (stride_h == 1 || stride_h == 2) &&
+           (fh == 2 || fh == 3 || fh == 5 || fh == 7);
+}
 void EnableNchwxxPass::fill_opr_convert_fun(size_t pack_c_size) {
     using RelayoutMode = RelayoutPlaceholder::LayoutType;
     using TestFilterResult = std::pair<TransType, RelayoutMode>;
@@ -1848,15 +1856,19 @@ void EnableNchwxxPass::fill_opr_convert_fun(size_t pack_c_size) {
              weight_to_nchwxx_mode_group, weight_to_nchwxx_mode_chan,
              hybrid_nchw_nchwxx](
                     const megdnn::param::Convolution::Sparse conv_mode,
-                    const VarNode* filter) -> TestFilterResult {
+                    const VarNode* filter, const size_t stride_h,
+                    const size_t stride_w) -> TestFilterResult {
         TestFilterResult ret{TransType::TRANS_NONE, {}};
         if (conv_mode == megdnn::param::Convolution::Sparse::DENSE) {
-            size_t IC = filter->shape()[1];
             size_t OC = filter->shape()[0];
+            size_t IC = filter->shape()[1];
+            size_t FH = filter->shape()[2];
+            size_t FW = filter->shape()[3];
             if ((IC % pack_c_size == 0) && (OC % pack_c_size == 0)) {
                 ret.first = TransType::TRANS_PURE_NCHWXX;
                 ret.second = weight_to_nchwxx_mode_dense;
-            } else if (IC < pack_c_size && OC % pack_c_size == 0) {
+            } else if (nchw_nchwxx_valid(OC, IC, pack_c_size, FH, FW, stride_h,
+                                         stride_w)) {
                 ret.first = TransType::TRANS_HYBIRD_NCHWXX;
                 ret.second = hybrid_nchw_nchwxx;
             }
@@ -1883,7 +1895,9 @@ void EnableNchwxxPass::fill_opr_convert_fun(size_t pack_c_size) {
         mgb_assert(conv_opr.param().format ==
                            megdnn::param::Convolution::Format::NCHW,
                    "ConvertFormat Pass only support converting NCHW to NCHWXX");
-        auto is_trans = test_trans_nchwxx(conv_opr.param().sparse, new_inp[1]);
+        auto is_trans = test_trans_nchwxx(conv_opr.param().sparse, new_inp[1],
+                                          conv_opr.param().stride_h,
+                                          conv_opr.param().stride_w);
         //! can not trans to nchwxx
         if (is_trans.first == TransType::TRANS_NONE) {
             mgb_assert(new_inp[1]->shape().ndim == 4 ||
@@ -1957,8 +1971,9 @@ void EnableNchwxxPass::fill_opr_convert_fun(size_t pack_c_size) {
         mgb_assert(conv_bias_opr.param().format ==
                            megdnn::param::ConvBias::Format::NCHW,
                    "ConvertFormat Pass only support converting NCHW to NCHWXX");
-        auto is_trans =
-                test_trans_nchwxx(conv_bias_opr.param().sparse, new_inp[1]);
+        auto is_trans = test_trans_nchwxx(
+                conv_bias_opr.param().sparse, new_inp[1],
+                conv_bias_opr.param().stride_h, conv_bias_opr.param().stride_w);
         //! can not trans to nchwxx
         if (is_trans.first == TransType::TRANS_NONE) {
             mgb_assert(new_inp[1]->shape().ndim == 4 ||
@@ -2199,17 +2214,21 @@ EnableNchw44DotPass::make_nchw44_dot_converter() {
     constexpr size_t pack_c_size = 4_z;
     auto test_trans_nchw44_dot =
             [](const megdnn::param::Convolution::Sparse conv_mode,
-               const VarNode* filter) -> TestTransResult {
+               const VarNode* filter, const size_t stride_h,
+               const size_t stride_w) -> TestTransResult {
         TestTransResult ret{TransType::TRANS_NONE, {}, {}};
         if (conv_mode == megdnn::param::Convolution::Sparse::DENSE) {
-            size_t IC = filter->shape()[1];
             size_t OC = filter->shape()[0];
+            size_t IC = filter->shape()[1];
+            size_t FH = filter->shape()[2];
+            size_t FW = filter->shape()[3];
             if ((IC % pack_c_size == 0) && (OC % pack_c_size == 0)) {
                 ret.trans_type = TransType::TRANS_PURE_NCHWXX;
                 ret.relayout_mod =
                         RelayoutMode::WEIGHT_NCHW_TO_NCHW44_DOT_DENSE;
                 ret.conv_format = megdnn::param::ConvBias::Format::NCHW44_DOT;
-            } else if (IC < pack_c_size && OC % pack_c_size == 0) {
+            } else if (nchw_nchwxx_valid(OC, IC, pack_c_size, FH, FW, stride_h,
+                                         stride_w)) {
                 ret.trans_type = TransType::TRANS_HYBIRD_NCHWXX;
                 ret.relayout_mod = RelayoutMode::WEIGHT_HYBIRD_NCHW_NCHW44;
                 ret.conv_format = megdnn::param::ConvBias::Format::NCHW44_DOT;
@@ -2241,8 +2260,9 @@ EnableNchw44DotPass::make_nchw44_dot_converter() {
                            megdnn::param::Convolution::Format::NCHW,
                    "ConvertFormat Pass only support converting NCHW to "
                    "NCHW44_DOT");
-        auto is_trans =
-                test_trans_nchw44_dot(conv_opr.param().sparse, new_inp[1]);
+        auto is_trans = test_trans_nchw44_dot(
+                conv_opr.param().sparse, new_inp[1], conv_opr.param().stride_h,
+                conv_opr.param().stride_w);
         //! can not trans to nchwxx
         if (is_trans.trans_type == TransType::TRANS_NONE) {
             mgb_assert(new_inp[1]->shape().ndim == 4 ||
@@ -2315,8 +2335,9 @@ EnableNchw44DotPass::make_nchw44_dot_converter() {
         mgb_assert(conv_bias_opr.param().format ==
                            megdnn::param::ConvBias::Format::NCHW,
                    "ConvertFormat Pass only support converting NCHW to NCHWXX");
-        auto is_trans =
-                test_trans_nchw44_dot(conv_bias_opr.param().sparse, new_inp[1]);
+        auto is_trans = test_trans_nchw44_dot(
+                conv_bias_opr.param().sparse, new_inp[1],
+                conv_bias_opr.param().stride_h, conv_bias_opr.param().stride_w);
         //! can not trans to nchwxx
         if (is_trans.trans_type == TransType::TRANS_NONE) {
             mgb_assert(new_inp[1]->shape().ndim == 4 ||

src/gopt/test/inference.cpp

@@ -2976,11 +2976,16 @@ TEST(TestGoptInference, ConvertFormatNCHW44) {
 
     auto host_x = gen({2, 3, 16, 16}, cn);
     auto x = opr::Host2DeviceCopy::make(*graph, host_x);
-    //! Hybrid nchw88 mode
+    //! Hybrid nchw44 mode
     opr::Convolution::Param param_conv;
     param_conv.pad_h = param_conv.pad_w = 1;
+    opr::ConvBias::Param param_conv_bias_stride4;
+    param_conv_bias_stride4.stride_h = param_conv_bias_stride4.stride_w = 4;
     auto w1 = mkcvar("w1", {8, 3, 3, 3}),
          conv1 = opr::Convolution::make(x, w1, param_conv);
+    auto w1_1 = mkcvar("w1_1", {8, 3, 4, 4}), b1 = mkcvar("b2", {1, 8, 1, 1}),
+         conv1_f4 = opr::Convolution::make(x, w1_1, param_conv);
+    auto conv1_s4 = opr::ConvBias::make(x, w1, b1, param_conv_bias_stride4);
     //! channel wise
     opr::ConvBias::Param param_conv_bias;
     param_conv_bias.pad_h = param_conv_bias.pad_w = 1;
@@ -3015,22 +3020,35 @@ TEST(TestGoptInference, ConvertFormatNCHW44) {
     auto w6 = mkcvar("w6", {4, 6, 3, 3}), b6 = mkcvar("b6", {1, 4, 1, 1}),
          y = opr::ConvBias::make(conv5, w6, b6, param_conv_bias);
 
-    SymbolVar y_opt;
+    SymbolVar y_opt, conv1_opt, conv1_f4_opt, conv1_s4_opt, conv2_opt;
     auto options = gopt::OptimizeForInferenceOptions{};
     options.enable_nchw44();
-    unpack_vector(gopt::optimize_for_inference({y}, options), y_opt);
+    unpack_vector(gopt::optimize_for_inference(
+                          {y, conv1, conv1_f4, conv1_s4, conv2}, options),
+                  y_opt, conv1_opt, conv1_f4_opt, conv1_s4_opt, conv2_opt);
 
     ASSERT_EQ(opr::ConvBias::Param::Format::NCHW44,
+              find_opr<opr::Convolution>(conv1_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW,
+              find_opr<opr::ConvBias>(conv1_s4_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW,
+              find_opr<opr::Convolution>(conv1_f4_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW44,
+              find_opr<opr::ConvBias>(conv2_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW44,
               find_opr<opr::ConvBias>(y_opt).param().format);
 
-    graph->compile({{y_opt, {}}})
+    graph->compile({{y_opt, {}}, {conv2, {}}})
             ->to_json()
             ->writeto_fpath(
                     output_file("TestGoptInference.ConvertFormatNCHW44.json"));
 
     HostTensorND host_y_opt, host_y;
+    HostTensorND host_conv1;
     auto func = graph->compile({make_callback_copy(y, host_y),
-                                make_callback_copy(y_opt, host_y_opt)});
+                                make_callback_copy(y_opt, host_y_opt),
+                                make_callback_copy(conv1, host_conv1)});
+
     func->execute();
     //! meybe go to winograd in x86-32, so set error 1e-1
     MGB_ASSERT_TENSOR_NEAR(host_y, host_y_opt, 1e-1);
@@ -3140,11 +3158,16 @@ TEST(TestGoptInference, ConvertFormatNCHW44_DOT) {
 
     auto host_x = gen({2, 3, 16, 16}, cn);
     auto x = opr::Host2DeviceCopy::make(*graph, host_x);
-    //! Hybrid nchw88 mode
+    //! Hybrid nchw44 mode
     opr::Convolution::Param param_conv;
     param_conv.pad_h = param_conv.pad_w = 1;
+    opr::ConvBias::Param param_conv_bias_stride4;
+    param_conv_bias_stride4.stride_h = param_conv_bias_stride4.stride_w = 4;
     auto w1 = mkcvar("w1", {8, 3, 3, 3}),
          conv1 = opr::Convolution::make(x, w1, param_conv);
+    auto w1_1 = mkcvar("w1_1", {8, 3, 4, 4}), b1 = mkcvar("b2", {1, 8, 1, 1}),
+         conv1_f4 = opr::Convolution::make(x, w1_1, param_conv);
+    auto conv1_s4 = opr::ConvBias::make(x, w1, b1, param_conv_bias_stride4);
     //! channel wise
     opr::ConvBias::Param param_conv_bias;
     param_conv_bias.pad_h = param_conv_bias.pad_w = 1;
@@ -3179,12 +3202,20 @@ TEST(TestGoptInference, ConvertFormatNCHW44_DOT) {
     auto w6 = mkcvar("w6", {4, 6, 3, 3}), b6 = mkcvar("b6", {1, 4, 1, 1}),
          y = opr::ConvBias::make(conv5, w6, b6, param_conv_bias);
 
-    SymbolVar y_opt;
+    SymbolVar y_opt, conv1_opt, conv1_f4_opt, conv1_s4_opt;
     auto options = gopt::OptimizeForInferenceOptions{};
     options.enable_nchw44_dot();
-    unpack_vector(gopt::optimize_for_inference({y}, options), y_opt);
+    unpack_vector(gopt::optimize_for_inference({y, conv1, conv1_f4, conv1_s4},
+                                               options),
+                  y_opt, conv1_opt, conv1_f4_opt, conv1_s4_opt);
 
     ASSERT_EQ(opr::ConvBias::Param::Format::NCHW44_DOT,
+              find_opr<opr::Convolution>(conv1_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW,
+              find_opr<opr::ConvBias>(conv1_s4_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW,
+              find_opr<opr::Convolution>(conv1_f4_opt).param().format);
+    ASSERT_EQ(opr::ConvBias::Param::Format::NCHW44_DOT,
               find_opr<opr::Convolution>(y_opt).param().format);
     ASSERT_EQ(opr::Convolution::Param::Format::NCHW44,
               find_opr<opr::ConvBias>(y_opt).param().format);