Fix for split op in BF16 inference (#39548)

* Fix for split bf16 inference

* added test for pass

* changes after review

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -2516,6 +2516,15 @@ PDNode *patterns::DuplicatedInputs::operator()() {
   return op;
 }
 
+PDNode *patterns::DuplicatedOutputs::operator()() {
+  auto op = pattern->NewNode(op_repr())->assert_is_ops({"split"});
+  op->assert_more([&](Node *node) {
+    return node->Op()->GetAttrIfExists<std::string>("mkldnn_data_type") ==
+           "bfloat16";
+  });
+  return op;
+}
+
 PDNode *patterns::MKLDNNInPlace::operator()() {
   const std::unordered_set<std::string> &supported_op_types = {
       "abs", "gelu", "leaky_relu", "relu", "softmax", "sqrt", "swish", "tanh"};

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -1495,6 +1495,15 @@ struct DuplicatedInputs : public PatternBase {
   PATTERN_DECL_NODE(op);
 };
 
+struct DuplicatedOutputs : public PatternBase {
+  DuplicatedOutputs(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "many_outputs_op") {}
+
+  PDNode* operator()();
+
+  PATTERN_DECL_NODE(op);
+};
+
 // Pattern used for enforcing inplace computation for in-place computation
 // supporting DNNL ops. softmax, batch_norm and layer_norm
 struct MKLDNNInPlace : public PatternBase {

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass.cc

@@ -52,7 +52,7 @@ bool IsPermittedOutputName(const std::string& output_name) {
 }
 
 void AddQuantize(Graph* g, ir::Node* op, ir::Node* op_in,
-                 int* quantize_counter) {
+                 int& quantize_counter) {
   std::vector<std::string> input_names;
 
   // Find the name of the input linking op to op_in
@@ -87,10 +87,10 @@ void AddQuantize(Graph* g, ir::Node* op, ir::Node* op_in,
   IR_NODE_LINK_TO(op_in, quantize_op);
   IR_NODE_LINK_TO(quantize_op, quantize_out_node);
   IR_NODE_LINK_TO(quantize_out_node, op);
-  (*quantize_counter)++;
+  quantize_counter++;
 }
 
-void AddQuantizes(Graph* g, ir::Node* op, int* quantize_counter) {
+void AddQuantizes(Graph* g, ir::Node* op, int& quantize_counter) {
   auto inputs = op->inputs;
   PADDLE_ENFORCE_GE(inputs.size(), 1,
                     platform::errors::InvalidArgument(
@@ -127,7 +127,7 @@ void AddQuantizes(Graph* g, ir::Node* op, int* quantize_counter) {
     IR_NODE_LINK_TO(inputs[i], quantize_op);
     IR_NODE_LINK_TO(quantize_op, quantize_out_nodes[i]);
     IR_NODE_LINK_TO(quantize_out_nodes[i], op);
-    (*quantize_counter)++;
+    quantize_counter++;
   }
 
   op->Op()->SetInput("X", quantize_out_node_names);
@@ -136,7 +136,7 @@ void AddQuantizes(Graph* g, ir::Node* op, int* quantize_counter) {
 // Operators like Concat and Sum have a single input name X, which actually
 // consists of multiple inputs. Such operators require a different way to find
 // pattern and add quantize ops.
-void AddReoderBeforeDuplicatedInputs(ir::Graph* graph, int* quantize_counter) {
+void AddReoderBeforeDuplicatedInputs(ir::Graph* graph, int& quantize_counter) {
   GraphPatternDetector gpd;
   patterns::DuplicatedInputs duplicated_inputs{gpd.mutable_pattern(),
                                                "duplicated_inputs"};
@@ -151,7 +151,7 @@ void AddReoderBeforeDuplicatedInputs(ir::Graph* graph, int* quantize_counter) {
 
 // Adding quantize ops before all operators except Concat and Sum, which have
 // already been handled in AddReoderBeforeDuplicatedInputs
-void AddReoderBeforeSingleInputs(ir::Graph* graph, int* quantize_counter) {
+void AddReoderBeforeSingleInputs(ir::Graph* graph, int& quantize_counter) {
   GraphPatternDetector gpd;
   patterns::FirstBfloat16Ops bfloat16_ops{gpd.mutable_pattern(),
                                           "first_bfloat16_ops"};
@@ -169,25 +169,16 @@ void AddReoderBeforeSingleInputs(ir::Graph* graph, int* quantize_counter) {
 
 void CPUBFloat16Pass::SetInputDataType(ir::Graph* graph) const {
   int quantize_counter = 0;
-  AddReoderBeforeDuplicatedInputs(graph, &quantize_counter);
-  AddReoderBeforeSingleInputs(graph, &quantize_counter);
+  AddReoderBeforeDuplicatedInputs(graph, quantize_counter);
+  AddReoderBeforeSingleInputs(graph, quantize_counter);
   PrettyLogDetail("---    added %d quantize ops before bfloat16 op",
                   quantize_counter);
 }
 
-void CPUBFloat16Pass::SetOutputDataType(ir::Graph* graph) const {
-  GraphPatternDetector gpd;
-  patterns::LastBfloat16Ops bfloat16_ops{gpd.mutable_pattern(),
-                                         "last_bfloat16_ops"};
-  bfloat16_ops();
-  int dequantize_counter = 0;
-
-  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
-                     Graph* g) {
-    GET_IR_NODE_FROM_SUBGRAPH(op, op, bfloat16_ops);
-    GET_IR_NODE_FROM_SUBGRAPH(op_out, op_out, bfloat16_ops);
+void AddDequantize(Graph* g, ir::Node* op, ir::Node* op_out,
+                   int& dequantize_counter) {
+  if (op->Op()->Type() == "prior_box") return;
 
-    if (op->Op()->Type() != "prior_box") {
   // Find the name of the output linking op to op_out
   std::vector<std::string> output_names;
   for (auto name : op->Op()->OutputNames())
@@ -207,22 +198,105 @@ void CPUBFloat16Pass::SetOutputDataType(ir::Graph* graph) const {
   deq_desc.SetOutput("Output", std::vector<std::string>({op_out->Name()}));
   deq_desc.SetAttr("Scale", 1.0f);
   deq_desc.SetAttr("Shift", 0.0f);
-      auto dequantize_op =
-          g->CreateOpNode(&deq_desc);  // OpDesc will be copied.
+  auto dequantize_op = g->CreateOpNode(&deq_desc);  // OpDesc will be copied.
 
   for (auto name = output_names.begin(); name < output_names.end(); name++)
-        op->Op()->SetOutput(
-            *name, std::vector<std::string>({dequantize_in_node->Name()}));
+    op->Op()->SetOutput(*name,
+                        std::vector<std::string>({dequantize_in_node->Name()}));
 
   UnlinkNodes(op, op_out);
   IR_NODE_LINK_TO(op, dequantize_in_node);
   IR_NODE_LINK_TO(dequantize_in_node, dequantize_op);
   IR_NODE_LINK_TO(dequantize_op, op_out);
 
+  dequantize_counter++;
+}
+
+void AddDequantizes(Graph* g, ir::Node* op, int& dequantize_counter) {
+  auto outputs = op->outputs;
+  PADDLE_ENFORCE_GE(outputs.size(), 1,
+                    platform::errors::InvalidArgument(
+                        "OP(%s)'s outputs(%d) must be equal or greater than 1.",
+                        op->Name(), outputs.size()));
+  PADDLE_ENFORCE_EQ(op->inputs.size(), 1,
+                    platform::errors::InvalidArgument(
+                        "OP(%s)'s inputs(%d) must be equal to 1.", op->Name(),
+                        op->inputs.size()));
+
+  OpDesc deq_desc;
+  deq_desc.SetType("dequantize");
+
+  std::vector<Node*> dequantize_in_nodes(outputs.size());
+  std::vector<std::string> dequantize_in_node_names(outputs.size());
+
+  for (size_t i = 0; i < outputs.size(); i++) {
+    VarDesc dequantize_in_desc(patterns::PDNodeName("dequantize", "in"));
+    dequantize_in_nodes[i] = g->CreateVarNode(&dequantize_in_desc);
+    dequantize_in_node_names[i] = dequantize_in_nodes[i]->Name();
+
+    deq_desc.SetInput("Input",
+                      std::vector<std::string>({dequantize_in_node_names[i]}));
+    deq_desc.SetOutput("Output",
+                       std::vector<std::string>({outputs[i]->Name()}));
+
+    deq_desc.SetAttr("Scale", 1.f);
+    deq_desc.SetAttr("Shift", 0.0f);
+    deq_desc.SetAttr("bfloat16", true);
+    deq_desc.SetAttr("output_format", op->Op()->HasAttr("data_layout")
+                                          ? op->Op()->GetAttr("data_layout")
+                                          : std::string("NCHW"));
+    auto dequantize_op = g->CreateOpNode(&deq_desc);  // OpDesc will be copied.
+
+    UnlinkNodes(op, outputs[i]);
+    IR_NODE_LINK_TO(op, dequantize_in_nodes[i]);
+    IR_NODE_LINK_TO(dequantize_in_nodes[i], dequantize_op);
+    IR_NODE_LINK_TO(dequantize_op, outputs[i]);
+
     dequantize_counter++;
   }
+
+  op->Op()->SetOutput("Out", dequantize_in_node_names);
+}
+
+// Operators like split have a single output name Out, which actually
+// consists of multiple outputs. Such operators require a different way to find
+// pattern and add dequantize ops.
+void AddReoderAfterDuplicatedOutputs(ir::Graph* graph,
+                                     int& dequantize_counter) {
+  GraphPatternDetector gpd;
+  patterns::DuplicatedOutputs duplicated_outputs{gpd.mutable_pattern(),
+                                                 "duplicated_outputs"};
+  duplicated_outputs();
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, duplicated_outputs);
+    AddDequantizes(g, op, dequantize_counter);
   };
   gpd(graph, handler);
+}
+
+// Adding dequantize ops after all operators except split, which has
+// already been handled in AddReoderAfterDuplicatedOutputs
+void AddReoderAfterSingleOutputs(ir::Graph* graph, int& dequantize_counter) {
+  GraphPatternDetector gpd;
+  patterns::LastBfloat16Ops bfloat16_ops{gpd.mutable_pattern(),
+                                         "last_bfloat16_ops"};
+  bfloat16_ops();
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_IR_NODE_FROM_SUBGRAPH(op_out, op_out, bfloat16_ops);
+    GET_IR_NODE_FROM_SUBGRAPH(op, op, bfloat16_ops);
+    if (op->Op()->Type() != "split") {
+      AddDequantize(g, op, op_out, dequantize_counter);
+    }
+  };
+  gpd(graph, handler);
+}
+
+void CPUBFloat16Pass::SetOutputDataType(ir::Graph* graph) const {
+  int dequantize_counter = 0;
+  AddReoderAfterDuplicatedOutputs(graph, dequantize_counter);
+  AddReoderAfterSingleOutputs(graph, dequantize_counter);
   PrettyLogDetail("---    added %d dequantize ops after bfloat16 op",
                   dequantize_counter);
 }

paddle/fluid/framework/ir/mkldnn/cpu_bfloat16_pass_tester.cc

@@ -45,7 +45,7 @@ void SetOp(ProgramDesc* prog, const std::string& type, const std::string& name,
     op->SetInput("Input", {inputs[0]});
     op->SetOutput("Out", {outputs[0]});
     op->SetAttr("mkldnn_data_type", mkldnn_data_type);
-  } else if (type == "concat" || type == "sum") {
+  } else if (type == "concat" || type == "sum" || type == "split") {
     op->SetInput("X", inputs);
     op->SetOutput("Out", outputs);
     op->SetAttr("mkldnn_data_type", mkldnn_data_type);
@@ -117,6 +117,7 @@ TEST(CpuBfloat16Pass, convolution) {
   bool use_mkldnn = true;
   int quant_op = 3;
   int dequant_op = 3;
+  // each added op consists of 2 nodes
   int added_nodes = quant_op * 2 + dequant_op * 2;
   MainTest(BuildProgramDescConv(use_mkldnn), quant_op, dequant_op, added_nodes);
 }
@@ -140,6 +141,7 @@ TEST(CpuBfloat16Pass, double_input_ops) {
   bool use_mkldnn = true;
   int quant_op = 4;
   int dequant_op = 3;
+  // each added op consists of 2 nodes
   int added_nodes = quant_op * 2 + dequant_op * 2;
   MainTest(BuildProgramDescDoubleInput(use_mkldnn), quant_op, dequant_op,
            added_nodes);
@@ -164,11 +166,35 @@ TEST(CpuBfloat16Pass, duplicated_input_ops) {
   bool use_mkldnn = true;
   int quant_op = 5;
   int dequant_op = 3;
+  // each added op consists of 2 nodes
   int added_nodes = quant_op * 2 + dequant_op * 2;
   MainTest(BuildProgramDescDuplicatedInput(use_mkldnn), quant_op, dequant_op,
            added_nodes);
 }
 
+ProgramDesc BuildProgramDescDuplicatedOutput(bool use_mkldnn) {
+  ProgramDesc prog;
+  for (auto& v : variable_names) {
+    prog.MutableBlock(0)->Var(v);
+  }
+  SetOp(&prog, "dropout", "Dropout", {"a"}, {"b"}, use_mkldnn, "float32");
+  SetOp(&prog, "split", "Split", {"b"}, {"c", "d"}, use_mkldnn, "bfloat16");
+  SetOp(&prog, "transpose2", "Transpose", {"c"}, {"e"}, use_mkldnn, "float32");
+  SetOp(&prog, "reshape2", "Reshape", {"d"}, {"f"}, use_mkldnn, "bfloat16");
+
+  return prog;
+}
+
+TEST(CpuBfloat16Pass, duplicated_output_ops) {
+  bool use_mkldnn = true;
+  int quant_op = 2;
+  int dequant_op = 3;
+  // each added op consists of 2 nodes
+  int added_nodes = quant_op * 2 + dequant_op * 2;
+  MainTest(BuildProgramDescDuplicatedOutput(use_mkldnn), quant_op, dequant_op,
+           added_nodes);
+}
+
 ProgramDesc BuildProgramDescDoubleOutputs(bool use_mkldnn) {
   ProgramDesc prog;
   for (auto& v : variable_names) {
@@ -190,6 +216,7 @@ TEST(CpuBfloat16Pass, double_outputs_ops) {
   bool use_mkldnn = true;
   int quant_op = 3;
   int dequant_op = 3;
+  // each added op consists of 2 nodes
   int added_nodes = quant_op * 2 + dequant_op * 2;
   MainTest(BuildProgramDescDoubleOutputs(use_mkldnn), quant_op, dequant_op,
            added_nodes);

paddle/phi/kernels/cpu/split_kernel.cc

@@ -70,4 +70,5 @@ PD_REGISTER_KERNEL(split,
                    int64_t,
                    int,
                    bool,
-                   phi::dtype::float16) {}
+                   phi::dtype::float16,
+                   phi::dtype::bfloat16) {}