Merge pull request #16526 from NHZlX/refine_trt_anakin

refine subgraph trt and anakin

paddle/fluid/framework/ir/CMakeLists.txt

@@ -68,21 +68,12 @@ pass_library(transpose_flatten_concat_fuse_pass inference)
 pass_library(identity_scale_op_clean_pass base)
 pass_library(sync_batch_norm_pass base)
 pass_library(runtime_context_cache_pass base)
-pass_library(simplify_anakin_detection_pattern_pass inference)
-pass_library(anakin_fillconstant_elementwisemul_fuse inference)
+pass_library(quant_conv2d_dequant_fuse_pass inference)
+pass_library(fillconstant_elementwisemul_fuse inference)
 
-# There may be many transpose-flatten structures in a model, and the output of
-# these structures will be used as inputs to the concat Op. This pattern will
-# be detected by our pass. The index here represents the number of structures in the
-# pattern. We use index 3 ~ 6, because these quantities of structures are
-# common in the models.
-foreach (index RANGE 2 6)
-   file(APPEND ${pass_file} "USE_PASS(transpose_flatten${index}_concat_fuse_pass);\n")
-endforeach()
-
-foreach (index RANGE 2 6)
-   file(APPEND ${pass_file} "USE_PASS(simplify_anakin_detection_pattern_pass${index});\n")
-endforeach()
+if(ANAKIN_FOUND)
+pass_library(simplify_anakin_priorbox_detection_out_pass inference)
+endif()
 
 if(WITH_MKLDNN)
     pass_library(mkldnn_placement_pass base mkldnn)

paddle/fluid/framework/ir/anakin_fillconstant_elementwisemul_fuse.cc → paddle/fluid/framework/ir/fillconstant_elementwisemul_fuse.cc

@@ -15,7 +15,7 @@
 #include <memory>
 #include <string>
 
-#include "paddle/fluid/framework/ir/anakin_fillconstant_elementwisemul_fuse.h"
+#include "paddle/fluid/framework/ir/fillconstant_elementwisemul_fuse.h"
 #include "paddle/fluid/framework/ir/graph_viz_pass.h"
 
 namespace paddle {
@@ -29,8 +29,8 @@ namespace ir {
   GET_IR_NODE(elementwise_mul);   \
   GET_IR_NODE(elementwise_mul_out);
 
-void AnakinFillconstantElementwisemulFuse::ApplyImpl(ir::Graph* graph) const {
-  const std::string pattern_name = "anakin_fillconstant_elementwisemul_fuse";
+void FillconstantElementwisemulFuse::ApplyImpl(ir::Graph* graph) const {
+  const std::string pattern_name = "fillconstant_elementwisemul_fuse";
   FusePassBase::Init(pattern_name, graph);
 
   GraphPatternDetector gpd;
@@ -39,8 +39,8 @@ void AnakinFillconstantElementwisemulFuse::ApplyImpl(ir::Graph* graph) const {
                 ->assert_is_op_input("elementwise_mul", "X")
                 ->AsInput();
 
-  patterns::AnakinFillConstantElementWiseMulFuse pattern(gpd.mutable_pattern(),
-                                                         pattern_name);
+  patterns::FillConstantElementWiseMulFuse pattern(gpd.mutable_pattern(),
+                                                   pattern_name);
   pattern(x);
 
   auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
@@ -79,5 +79,5 @@ void AnakinFillconstantElementwisemulFuse::ApplyImpl(ir::Graph* graph) const {
 }  // namespace framework
 }  // namespace paddle
 
-REGISTER_PASS(anakin_fillconstant_elementwisemul_fuse,
-              paddle::framework::ir::AnakinFillconstantElementwisemulFuse);
+REGISTER_PASS(fillconstant_elementwisemul_fuse,
+              paddle::framework::ir::FillconstantElementwisemulFuse);

paddle/fluid/framework/ir/anakin_fillconstant_elementwisemul_fuse.h → paddle/fluid/framework/ir/fillconstant_elementwisemul_fuse.h

@@ -21,9 +21,9 @@ namespace paddle {
 namespace framework {
 namespace ir {
 
-class AnakinFillconstantElementwisemulFuse : public FusePassBase {
+class FillconstantElementwisemulFuse : public FusePassBase {
  public:
-  virtual ~AnakinFillconstantElementwisemulFuse() {}
+  virtual ~FillconstantElementwisemulFuse() {}
 
  protected:
   void ApplyImpl(ir::Graph* graph) const override;

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -1471,7 +1471,8 @@ PDNode *patterns::TransposeFlattenConcat::operator()(
 }
 
 PDNode *patterns::AnakinDetectionPattern::operator()(
-    std::vector<PDNode *> conv_in, int times) {
+    std::vector<PDNode *> conv_in, int times, std::string priorbox_type,
+    bool is_reshape) {
   // The times represents the repeat times of the
   // {prior_box, prior_box_loc_out, flatten, prior_box_var_out, reshape}
   const int kNumFields = 7;
@@ -1486,37 +1487,38 @@ PDNode *patterns::AnakinDetectionPattern::operator()(
   const int kMultiClassSecondInputNmsOffset = times + 1;
 
   std::vector<PDNode *> nodes;
+  std::string op_after_priorbox = is_reshape ? "reshape2" : "flatten2";
 
   for (int i = 0; i < times; i++) {
     nodes.push_back(
         pattern->NewNode(GetNodeName("prior_box" + std::to_string(i)))
-            ->assert_is_op("density_prior_box"));
+            ->assert_is_op(priorbox_type));
     nodes.push_back(pattern->NewNode(GetNodeName("box_out" + std::to_string(i)))
-                        ->assert_is_op_output("density_prior_box", "Boxes")
-                        ->assert_is_op_input("reshape2", "X")
+                        ->assert_is_op_output(priorbox_type, "Boxes")
+                        ->assert_is_op_input(op_after_priorbox, "X")
                         ->AsIntermediate());
     nodes.push_back(
         pattern->NewNode(GetNodeName("reshape1" + std::to_string(i)))
-            ->assert_is_op("reshape2"));
+            ->assert_is_op(op_after_priorbox));
 
     nodes.push_back(
         pattern->NewNode(GetNodeName("reshape1_out" + std::to_string(i)))
-            ->assert_is_op_output("reshape2")
+            ->assert_is_op_output(op_after_priorbox)
             ->assert_is_op_nth_input("concat", "X", i)
             ->AsIntermediate());
 
     nodes.push_back(
         pattern->NewNode(GetNodeName("box_var_out" + std::to_string(i)))
-            ->assert_is_op_output("density_prior_box", "Variances")
-            ->assert_is_op_input("reshape2", "X")
+            ->assert_is_op_output(priorbox_type, "Variances")
+            ->assert_is_op_input(op_after_priorbox, "X")
             ->AsIntermediate());
     nodes.push_back(
         pattern->NewNode(GetNodeName("reshape2" + std::to_string(i)))
-            ->assert_is_op("reshape2"));
+            ->assert_is_op(op_after_priorbox));
 
     nodes.push_back(
         pattern->NewNode(GetNodeName("reshape2_out" + std::to_string(i)))
-            ->assert_is_op_output("reshape2")
+            ->assert_is_op_output(op_after_priorbox)
             ->assert_is_op_nth_input("concat", "X", i)
             ->AsIntermediate());
   }
@@ -1612,7 +1614,7 @@ PDNode *patterns::AnakinDetectionPattern::operator()(
   return multiclass_nms_out;
 }
 
-PDNode *patterns::AnakinFillConstantElementWiseMulFuse::operator()(
+PDNode *patterns::FillConstantElementWiseMulFuse::operator()(
     PDNode *elementwise_op_input) {
   auto fill_constant =
       pattern->NewNode(fill_constant_repr())->assert_is_op("fill_constant");
@@ -1635,6 +1637,76 @@ PDNode *patterns::AnakinFillConstantElementWiseMulFuse::operator()(
   return elementwise_mul_out;
 }
 
+void patterns::QuantDequantOpFuse::operator()(PDNode *quant_op_input,
+                                              const std::string &op_type,
+                                              const std::string &weight_name,
+                                              int times) {
+  const int kNumFields = 5;
+  const int kQuantizedWeightOffset = 0;
+  const int kQuantizedOpOffset = 1;
+  const int kQuantizedOpOutOffset = 2;
+  const int kDequantOpOffset = 3;
+  const int kDequantOpOutOffset = 4;
+  // the quant op always be one.
+  auto quant_op_in_scale =
+      pattern->NewNode(GetNodeName("quant_op_in_scale"))
+          ->assert_is_op_input("fake_quantize_range_abs_max", "InScale")
+          ->AsInput();
+  auto quant_op = pattern->NewNode(GetNodeName("quant_op"))
+                      ->assert_is_op("fake_quantize_range_abs_max");
+
+  auto quant_op_out_scale =
+      pattern->NewNode(GetNodeName("quant_op_out_scale"))
+          ->assert_is_op_output("fake_quantize_range_abs_max", "OutScale")
+          ->assert_is_op_input("fake_dequantize_max_abs", "Scale")
+          ->AsIntermediate();
+
+  auto quant_op_out =
+      pattern->NewNode(GetNodeName("quant_op_out"))
+          ->assert_is_op_output("fake_quantize_range_abs_max", "Out")
+          ->assert_is_op_input(op_type)
+          ->AsIntermediate();
+
+  // there are 'times' quantized and dequant op
+  std::vector<PDNode *> nodes;
+  for (int i = 0; i < times; i++) {
+    nodes.push_back(
+        pattern->NewNode(GetNodeName("quantized_op_weight") + std::to_string(i))
+            ->assert_is_op_input(op_type, weight_name)
+            ->AsInput());
+    nodes.push_back(
+        pattern->NewNode(GetNodeName("quantized_op") + std::to_string(i))
+            ->assert_is_op(op_type));
+
+    nodes.push_back(
+        pattern->NewNode(GetNodeName("quantized_op_out") + std::to_string(i))
+            ->assert_is_op_output(op_type)
+            ->assert_is_op_input("fake_dequantize_max_abs", "X")
+            ->AsIntermediate());
+
+    nodes.push_back(
+        pattern->NewNode(GetNodeName("dequant_op") + std::to_string(i))
+            ->assert_is_op("fake_dequantize_max_abs"));
+    nodes.push_back(
+        pattern->NewNode(GetNodeName("dequant_op_out") + std::to_string(i))
+            ->assert_is_op_output("fake_dequantize_max_abs", "Out")
+            ->AsOutput());
+  }
+
+  quant_op->LinksFrom({quant_op_input, quant_op_in_scale});
+  quant_op_out->LinksFrom({quant_op});
+  for (int i = 0; i < times; i++) {
+    nodes[i * kNumFields + kQuantizedOpOffset]->LinksFrom(
+        {quant_op_out, nodes[i * kNumFields + kQuantizedWeightOffset]});
+    nodes[i * kNumFields + kQuantizedOpOutOffset]->LinksFrom(
+        {nodes[i * kNumFields + kQuantizedOpOffset]});
+    nodes[i * kNumFields + kDequantOpOffset]->LinksFrom(
+        {nodes[i * kNumFields + kQuantizedOpOutOffset], quant_op_out_scale});
+    nodes[i * kNumFields + kDequantOpOutOffset]->LinksFrom(
+        {nodes[i * kNumFields + kDequantOpOffset]});
+  }
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -848,7 +848,8 @@ struct AnakinDetectionPattern : public PatternBase {
   AnakinDetectionPattern(PDPattern* pattern, const std::string& name_scope)
       : PatternBase(pattern, name_scope, "anakin_detect_pattern") {}
 
-  PDNode* operator()(std::vector<PDNode*> conv_inputs, int times);
+  PDNode* operator()(std::vector<PDNode*> conv_inputs, int times,
+                     std::string priorbox_type, bool is_reshape);
 
   std::string GetNodeName(const std::string& op_type) {
     return PDNodeName(name_scope_, repr_, id_, op_type);
@@ -859,9 +860,9 @@ struct AnakinDetectionPattern : public PatternBase {
   }
 };
 
-struct AnakinFillConstantElementWiseMulFuse : public PatternBase {
-  AnakinFillConstantElementWiseMulFuse(PDPattern* pattern,
-                                       const std::string& name_scope)
+struct FillConstantElementWiseMulFuse : public PatternBase {
+  FillConstantElementWiseMulFuse(PDPattern* pattern,
+                                 const std::string& name_scope)
       : PatternBase(pattern, name_scope,
                     "anakin_fillconstant_elementwisemul_fuse") {}
 
@@ -874,6 +875,22 @@ struct AnakinFillConstantElementWiseMulFuse : public PatternBase {
   PATTERN_DECL_NODE(elementwise_mul_out);
 };
 
+struct QuantDequantOpFuse : public PatternBase {
+  QuantDequantOpFuse(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "quant_dequant_fuse") {}
+
+  void operator()(PDNode* quant_op_input, const std::string& op_name,
+                  const std::string& weight_name, int times = 1);
+
+  std::string GetNodeName(const std::string& op_type) {
+    return PDNodeName(name_scope_, repr_, id_, op_type);
+  }
+
+  PDNode* GetPDNode(const std::string& op_type) {
+    return pattern->RetrieveNode(GetNodeName(op_type));
+  }
+};
+
 }  // namespace patterns
 
 // Link two ir::Nodes from each other.