fix fuse square mat order and refine test

test=develop

paddle/fluid/framework/ir/repeated_fc_relu_fuse_pass.h

@@ -33,7 +33,7 @@ class RepeatedFCReluFusePass : public FusePassBase {
  protected:
   std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
 
-  const std::string name_scope_{"repeated_fc_relu"};
+  const std::string name_scope_{"repeated_fc_relu_fuse"};
 };
 
 }  // namespace ir

paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.cc

@@ -51,7 +51,7 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
 
   auto next_op = [=](Node* x, const std::string& op_type) -> Node* {
     if (!(x && x->IsVar())) {
-      return false;
+      return nullptr;
     }
     for (auto* op : x->outputs) {
       if (op && op->IsOp() && op->Op() && op->Op()->Type() == op_type) {
@@ -63,7 +63,7 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
 
   auto get_op_input_var = [=](Node* x, const std::string& arg_name) -> Node* {
     if (!(x && x->IsOp())) {
-      return false;
+      return nullptr;
     }
     for (auto* var : x->inputs) {
       for (auto name : x->Op()->Input(arg_name)) {
@@ -93,10 +93,10 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
     if (!next_is_matmul_from_arg) {
       return false;
     }
-    auto* sub_x = squared_x->outputs[0]->outputs[0];
-    return var_is_op_input(sub_x, "elementwise_sub", "X") &&
-           sub_x->outputs[0]->outputs.size() == 1 &&
-           var_is_op_input(sub_x->outputs[0]->outputs[0], "elementwise_mul");
+    auto* sub_y_in = squared_x->outputs[0]->outputs[0];
+    return var_is_op_input(sub_y_in, "elementwise_sub", "Y") &&
+           sub_y_in->outputs[0]->outputs.size() == 1 &&
+           var_is_op_input(sub_y_in->outputs[0]->outputs[0], "elementwise_mul");
   };
 
   auto is_fusion_first_mul_out = [=](Node* x) -> bool {
@@ -120,10 +120,10 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
     if (!next_is_square) {
       return false;
     }
-    auto* sub_y = x->outputs[0]->outputs[0];
-    return var_is_op_input(sub_y, "elementwise_sub", "Y") &&
-           sub_y->outputs[0]->outputs.size() == 1 &&
-           var_is_op_input(sub_y->outputs[0]->outputs[0], "elementwise_mul");
+    auto* sub_x_in = x->outputs[0]->outputs[0];
+    return var_is_op_input(sub_x_in, "elementwise_sub", "X") &&
+           sub_x_in->outputs[0]->outputs.size() == 1 &&
+           var_is_op_input(sub_x_in->outputs[0]->outputs[0], "elementwise_mul");
   };
 
   auto* x = pattern->NewNode(
@@ -219,7 +219,7 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
     if (!is_sub_op) {
       return false;
     }
-    auto* matmul_sqx_sqy_var = get_op_input_var(x, "X");
+    auto* matmul_sqx_sqy_var = get_op_input_var(x, "Y");
     return is_fusion_mat_squared_x_y_op_out(matmul_sqx_sqy_var);
   };
 
@@ -280,7 +280,7 @@ PDNode* BuildSquaredMatSubPattern(PDPattern* pattern,
   matmul_squared_x_y_op->LinksFrom({squared_x, squared_y})
       .LinksTo({mat_squared_x_y_op_out});
   square_matmuled_xy_op->LinksFrom({matmuled_xy}).LinksTo({squared_xmuly});
-  sub_op->LinksFrom({mat_squared_x_y_op_out, squared_xmuly})
+  sub_op->LinksFrom({squared_xmuly, mat_squared_x_y_op_out})
       .LinksTo({sub_op_out});
   constant_op->LinksFrom({}).LinksTo({constant_op_out});
   elementmul_op->LinksFrom({constant_op_out, sub_op_out})

paddle/fluid/framework/ir/squared_mat_sub_fuse_pass.h

@@ -33,7 +33,7 @@ class SquaredMatSubFusePass : public FusePassBase {
  protected:
   std::unique_ptr<ir::Graph> ApplyImpl(std::unique_ptr<ir::Graph> graph) const;
 
-  const std::string name_scope_{"squared_mat_sub"};
+  const std::string name_scope_{"squared_mat_sub_fuse"};
 };
 
 }  // namespace ir

paddle/fluid/inference/tests/api/analyzer_seq_pool1_tester.cc

@@ -21,6 +21,12 @@ namespace paddle {
 namespace inference {
 namespace analysis {
 
+// diff: similarity_norm.tmp_0, for speed: fc_4.tmp_1
+static const char out_var_name[] = "reduce_sum_0.tmp_0";
+
+// for diff: 154, for speed 111
+constexpr int num_slots = 154;
+
 struct OneSlotInBatch {
   std::string name;
   std::vector<std::vector<float>> data;
@@ -41,7 +47,6 @@ struct DataRecord {
 
   void Load(const std::string &path) {
     std::ifstream file(path);
-    constexpr int num_slots = 154;
     std::string line;
     int num_lines = 0;
     while (std::getline(file, line)) {
@@ -190,13 +195,15 @@ void analysis_fuse_statis(bool use_zerocopy) {
   auto predictor = CreatePaddlePredictor<AnalysisConfig>(cfg);
   auto fuse_statis = GetFuseStatis(predictor.get(), &num_ops);
   ASSERT_TRUE(fuse_statis.count("fc_fuse"));
-  ASSERT_EQ(fuse_statis.at("fc_fuse"), 10);
   ASSERT_TRUE(fuse_statis.count("seqpool_concat_fuse"));
+  ASSERT_TRUE(fuse_statis.count("squared_mat_sub_fuse"));
+  ASSERT_TRUE(fuse_statis.count("repeated_fc_relu_fuse"));
+  ASSERT_EQ(fuse_statis.at("fc_fuse"), 10);
   EXPECT_EQ(fuse_statis.at("seqpool_concat_fuse"), 2);
-  ASSERT_TRUE(fuse_statis.count("repeated_fc_relu"));
-  EXPECT_EQ(fuse_statis.at("repeated_fc_relu"), 2);
+  EXPECT_EQ(fuse_statis.at("squared_mat_sub_fuse"), 2);
+  EXPECT_EQ(fuse_statis.at("repeated_fc_relu_fuse"), 2);
   LOG(INFO) << "num_ops: " << num_ops;
-  EXPECT_EQ(num_ops, 185);
+  EXPECT_EQ(num_ops, 171);
 }
 
 // Check the fuse status
@@ -219,9 +226,6 @@ void PrepareZeroCopyInputs(
   }
 }
 
-// diff: similarity_norm.tmp_0, // speed: fc_4.tmp_1
-static const char out_var_name[] = "reduce_sum_0.tmp_0";
-
 // return the output values
 std::vector<float> zerocopy_profile(int repeat_times) {
   AnalysisConfig config;

paddle/fluid/operators/fused/fusion_squared_mat_sub_op.cc

@@ -68,7 +68,7 @@ void FusionSquaredMatSubOpMaker::Make() {
   AddComment(R"DOC(
     Fusion Squared Matrix and substrct operator.
     
-    ( (A.^2 * B.^2) - (A * B).^2 ) .* scalar
+    ( (X * Y).^2 - (X.^2 * Y.^2) ) .* scalar
 )DOC");
 }
 
@@ -112,14 +112,14 @@ class FusionSquaredMatSubKernel : public framework::OpKernel<T> {
     T* squared_xy_data = squared_xy->mutable_data<T>(place);
     T* o_data = out->mutable_data<T>(place);
 
+    matmul(x_data, y_data, squared_xy_data, m, n, k);
+    vsquare_xy(squared_xy_data, squared_xy_data, o_numel);
+
     vsquare_x(x_data, squared_x_data, m * k);
     vsquare_y(y_data, squared_y_data, k * n);
-
-    matmul(x_data, y_data, o_data, m, n, k);
-    vsquare_xy(o_data, squared_xy_data, o_numel);
-
     matmul(squared_x_data, squared_y_data, o_data, m, n, k);
-    vsub(o_data, squared_xy_data, o_data, o_numel);
+
+    vsub(squared_xy_data, o_data, o_data, o_numel);
     vscal(&scalar, o_data, o_data, o_numel);
   }
 };

python/paddle/fluid/tests/unittests/test_fusion_squared_mat_sub_op.py

@@ -33,7 +33,7 @@ class TestFusionSquaredMatSubOp(OpTest):
         self.inputs = {'X': matx, 'Y': maty}
         self.outputs = {
             'Out':
-            (np.dot(matx**2, maty**2) - np.dot(matx, maty)**2) * self.scalar
+            (np.dot(matx, maty)**2 - np.dot(matx**2, maty**2)) * self.scalar
         }
         self.attrs = {'scalar': self.scalar, }