[PaddleInference] Pass: add int8 flag for op (#36042)

* add_int_pass

* add_int8_flag_pass

* add_int8_flag_pass

* fix CMakeLists.txt

* fix test_trt_fc_fuse_quant_dequant_pass.py

* fix python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

* fix test_trt_fc_fuse_quant_dequant_pass.py

paddle/fluid/framework/ir/CMakeLists.txt

@@ -97,6 +97,7 @@ pass_library(multihead_matmul_fuse_pass inference)
 pass_library(adaptive_pool2d_convert_global_pass inference)
 pass_library(unsqueeze2_eltwise_fuse_pass inference)
 pass_library(layer_norm_fuse_pass inference)
+pass_library(add_support_int8_pass inference)
 pass_library(generate_pass DEPS pass_desc_proto)
 target_link_libraries(generate_pass pass_desc_proto)
 if(WITH_GPU OR WITH_ROCM)

paddle/fluid/framework/ir/add_support_int8_pass.cc

+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#include "paddle/fluid/framework/ir/add_support_int8_pass.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+#define GET_IR_NODE(node__) GET_IR_NODE_FROM_SUBGRAPH(node__, node__, pattern);
+#define GET_NODES        \
+  GET_IR_NODE(prev_op);  \
+  GET_IR_NODE(prev_out); \
+  GET_IR_NODE(quant_op); \
+  GET_IR_NODE(quant_out);
+
+void AddSupportInt8Pass::ApplyImpl(ir::Graph* graph) const {
+  const std::string pattern_name = "add_support_int8";
+  FusePassBase::Init(pattern_name, graph);
+
+  GraphPatternDetector gpd;
+
+  patterns::AddSupportInt8 pattern(gpd.mutable_pattern(), pattern_name);
+  pattern();
+  int found_count = 0;
+  auto handler = [&](const GraphPatternDetector::subgraph_t& subgraph,
+                     Graph* g) {
+    GET_NODES;
+    if (prev_op->Op()->HasAttr("out_threshold") &&
+        quant_op->Op()->HasAttr("out_threshold")) {
+      quant_op->Op()->SetAttr("support_int8", true);
+    }
+    found_count++;
+  };
+  gpd(graph, handler);
+  AddStatis(found_count);
+}
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle
+
+REGISTER_PASS(add_support_int8_pass, paddle::framework::ir::AddSupportInt8Pass);

paddle/fluid/framework/ir/add_support_int8_pass.h

+// Copyright (c) 2018 PaddlePaddle Authors. All Rights Reserved.
+//
+// Licensed under the Apache License, Version 2.0 (the "License");
+// you may not use this file except in compliance with the License.
+// You may obtain a copy of the License at
+//
+//     http://www.apache.org/licenses/LICENSE-2.0
+//
+// Unless required by applicable law or agreed to in writing, software
+// distributed under the License is distributed on an "AS IS" BASIS,
+// WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+// See the License for the specific language governing permissions and
+// limitations under the License.
+
+#pragma once
+#include "paddle/fluid/framework/ir/fuse_pass_base.h"
+#include "paddle/fluid/framework/ir/graph_pattern_detector.h"
+
+namespace paddle {
+namespace framework {
+namespace ir {
+
+class Graph;
+
+class AddSupportInt8Pass : public FusePassBase {
+ public:
+  AddSupportInt8Pass() {}
+  virtual ~AddSupportInt8Pass() {}
+
+ protected:
+  void ApplyImpl(ir::Graph* graph) const override;
+};
+
+}  // namespace ir
+}  // namespace framework
+}  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.cc

@@ -2986,6 +2986,29 @@ PDNode *patterns::LayerNorm::operator()() {
   return shift_out;
 }
 
+// Add support int8 flag
+PDNode *patterns::AddSupportInt8::operator()() {
+  auto prev_op =
+      pattern->NewNode(prev_op_repr())
+          ->assert_is_op()
+          ->assert_more([&](Node *node) {
+            return node->Op()->HasAttr("out_threshold") ? true : false;
+          });
+  auto prev_out = pattern->NewNode(prev_out_repr())->assert_is_var();
+  auto quant_op =
+      pattern->NewNode(quant_op_repr())
+          ->assert_is_op()
+          ->assert_more([&](Node *node) {
+            return node->Op()->HasAttr("out_threshold") ? true : false;
+          });
+  auto quant_out =
+      pattern->NewNode(quant_out_repr())->assert_is_var()->AsOutput();
+  prev_op->LinksTo({prev_out});
+  prev_out->LinksTo({quant_op});
+  quant_op->LinksTo({quant_out});
+  return quant_out;
+}
+
 }  // namespace ir
 }  // namespace framework
 }  // namespace paddle

paddle/fluid/framework/ir/graph_pattern_detector.h

@@ -1682,6 +1682,18 @@ struct LayerNorm : public PatternBase {
   PATTERN_DECL_NODE(shift_out);
 };
 
+// Add support int8 flag
+struct AddSupportInt8 : public PatternBase {
+  AddSupportInt8(PDPattern* pattern, const std::string& name_scope)
+      : PatternBase(pattern, name_scope, "Add_support_int8") {}
+
+  PDNode* operator()();
+  PATTERN_DECL_NODE(prev_op);
+  PATTERN_DECL_NODE(prev_out);
+  PATTERN_DECL_NODE(quant_op);
+  PATTERN_DECL_NODE(quant_out);
+};
+
 }  // namespace patterns
 
 // Link two ir::Nodes from each other.

paddle/fluid/inference/api/paddle_pass_builder.cc

@@ -96,8 +96,9 @@ const std::vector<std::string> kTRTSubgraphPasses({
       "map_matmul_to_mul_pass",                 //
       "fc_fuse_pass",                           //
       "conv_elementwise_add_fuse_pass",         //
-      "tensorrt_subgraph_pass",                 //
-      "conv_bn_fuse_pass",                      //
+      "add_support_int8_pass",
+      "tensorrt_subgraph_pass",  //
+      "conv_bn_fuse_pass",       //
 #if CUDNN_VERSION >= 7100  // To run conv_fusion, the version of cudnn must be
                            // guaranteed at least v7
 // cudnn8.0 has memory leak problem in conv + eltwise + act, so we

paddle/fluid/inference/tensorrt/op_teller.cc

@@ -59,6 +59,8 @@ struct SimpleOpTypeSetTeller : public Teller {
 #if CUDA_VERSION >= 10020
     teller_set.insert("reshape");
     teller_set.insert("reshape2");
+    int8_teller_set.insert("reshape");
+    int8_teller_set.insert("reshape2");
 #endif
   }
 
@@ -91,7 +93,9 @@ struct SimpleOpTypeSetTeller : public Teller {
                                                   "scale",
                                                   "elementwise_mul",
                                                   "conv2d_transpose",
-                                                  "hard_swish"};
+                                                  "hard_swish",
+                                                  "transpose",
+                                                  "transpose2"};
   std::unordered_set<std::string> teller_set{"mul",
                                              "matmul",
                                              "conv2d",

python/paddle/fluid/tests/unittests/ir/inference/test_trt_fc_fuse_quant_dequant_pass.py

@@ -86,15 +86,14 @@ class FCQuantDequantFusePassTRTDims3Cols2Test(QuantDequantTest):
             self.data = fluid.data(
                 name='data', shape=[1, 28, 28], dtype='float32')
             self.label = fluid.data(name='label', shape=[1, 1], dtype='int64')
-            label_shape = fluid.layers.reshape(self.label, shape=[1, 1, 1])
             fc_out = fluid.layers.fc(input=self.data,
                                      size=28,
                                      num_flatten_dims=2,
                                      bias_attr=False,
                                      act=None)
-            c_out = fluid.layers.reshape(fc_out, shape=[1, 1, 784])
+            c_out = fluid.layers.reshape(fc_out, shape=[0, 784])
             result = fluid.layers.relu(c_out)
-            loss = fluid.layers.cross_entropy(input=result, label=label_shape)
+            loss = fluid.layers.cross_entropy(input=result, label=self.label)
             avg_loss = fluid.layers.mean(loss)
             return avg_loss, result
 
@@ -119,11 +118,11 @@ class FCQuantDequantFusePassTRTDims3Cols2Test(QuantDequantTest):
         self.dynamic_shape_params = FCQuantDequantFusePassTRTDims3Cols2Test.DynamicShapeParam(
             {
                 'data': [1, 28, 28],
-                'reshape2_1.tmp_0': [1, 1, 784]
+                'reshape2_0.tmp_0': [1, 784]
             }, {'data': [4, 28, 28],
-                'reshape2_1.tmp_0': [4, 1, 784]},
-            {'data': [1, 28, 28],
-             'reshape2_1.tmp_0': [1, 1, 784]}, False)
+                'reshape2_0.tmp_0':
+                [4, 784]}, {'data': [1, 28, 28],
+                            'reshape2_0.tmp_0': [1, 784]}, False)
         self.activation_quantize_type = 'moving_average_abs_max'
         self.weight_quantize_type = 'channel_wise_abs_max'