!15101 [MS][LITE] Move bias tensor quant params to propogator

From: @cjh9368
Reviewed-by: @hangangqiang,@zhanghaibo5
Signed-off-by: @hangangqiang

mindspore/lite/tools/converter/quantizer/quant_helper/conv_quant_param_propogator.cc

@@ -15,6 +15,7 @@
  */
 #include "tools/converter/quantizer/quant_helper/conv_quant_param_propogator.h"
 #include "mindspore/core/ir/dtype/type_id.h"
+
 namespace mindspore::lite {
 static constexpr size_t kBiasAdd = 3;
 
@@ -22,6 +23,36 @@ STATUS ConvQuantParamPropogator::PropogateQuantParams(mindspore::schema::MetaGra
                                                       const mindspore::schema::CNodeT &node) {
   if (node.inputIndex.size() == kBiasAdd) {
     auto &bias_tensor = graph->allTensors.at(node.inputIndex.at(kBiasAdd - 1));
+    if (bias_tensor->quantParams.empty() || !bias_tensor->quantParams.front()->inited) {
+      // check input and weight quant params
+      auto &input_tensor = graph->allTensors.at(node.inputIndex.at(0));
+      auto &weight_tensor = graph->allTensors.at(node.inputIndex.at(1));
+      if (input_tensor->quantParams.empty() || !input_tensor->quantParams.front()->inited) {
+        return RET_OK;
+      }
+
+      if (weight_tensor->quantParams.empty() || !weight_tensor->quantParams.front()->inited) {
+        return RET_OK;
+      }
+      auto &input_quant_param = input_tensor->quantParams.at(0);
+      auto &weight_quant_param = weight_tensor->quantParams.at(0);
+
+      if (bias_tensor->quantParams.empty()) {
+        auto tmp_quant_param = std::make_unique<schema::QuantParamT>();
+        bias_tensor->quantParams.emplace_back(std::move(tmp_quant_param));
+      }
+      auto &bias_quant_param = bias_tensor->quantParams.front();
+      bias_quant_param->min = 0.0;
+      bias_quant_param->max = 0.0;
+      bias_quant_param->dstDtype = kNumberTypeInt32;
+      bias_quant_param->inited = input_quant_param->inited && weight_quant_param->inited;
+      bias_quant_param->zeroPoint = 0;
+      if (bias_quant_param->inited) {
+        bias_quant_param->scale = input_quant_param->scale * weight_quant_param->scale;
+      }
+      bias_quant_param->roundType = 1;
+      bias_quant_param->multiplier = 1;
+    }
     for (auto &quantParam : bias_tensor->quantParams) {
       quantParam->dstDtype = TypeId::kNumberTypeInt32;
     }

mindspore/lite/tools/optimizer/fusion/matmul_add_fusion.cc

@@ -64,7 +64,8 @@ bool MatMulAddFusion::Run(const FuncGraphPtr &func_graph) {
     }
     auto matmul_cnode = cnode->input(index)->cast<CNodePtr>();
     auto bias_node = cnode->input(kAddInputSize - index);
-    if (!utils::isa<Parameter>(bias_node) || !bias_node->cast<ParameterPtr>()->default_param()) {
+    if (!utils::isa<ValueNode>(bias_node) &&
+        (!utils::isa<Parameter>(bias_node) || !bias_node->cast<ParameterPtr>()->default_param())) {
       continue;
     }
     matmul_cnode->add_input(bias_node);

mindspore/lite/tools/optimizer/graph/mindir_adjust_pass.cc

@@ -26,40 +26,6 @@ namespace mindspore {
 namespace opt {
 namespace {
 constexpr size_t kDoubleNum = 2;
-void FillDefaultInputQuantParamIfNeed(const PrimitivePtr &prim, const size_t &input_size) {
-  auto quant_tensor_info_ptr = prim->GetAttr("quant_params");
-  if (quant_tensor_info_ptr == nullptr) {
-    prim->AddAttr("quant_params", std::make_shared<lite::QuantParamHolder>());
-  }
-  auto quant_param_holder = prim->GetAttr("quant_params")->cast<lite::QuantParamHolderPtr>();
-  std::vector<schema::QuantParamT> quants;
-  schema::QuantParamT quant_param;
-  auto input_quant_params = quant_param_holder->input_quant_params();
-  if (input_quant_params.size() == kDoubleNum) {
-    quants.clear();
-    quant_param.min = 0.0;
-    quant_param.max = 0.0;
-    quant_param.dstDtype = kNumberTypeInt32;
-    quant_param.inited = input_quant_params.at(0).at(0).inited && input_quant_params.at(1).at(0).inited;
-    quant_param.inited = false;
-    quant_param.zeroPoint = 0;
-    if (quant_param.inited) {
-      quant_param.scale = input_quant_params.at(0).at(0).scale * input_quant_params.at(1).at(0).scale;
-    }
-    quant_param.roundType = 1;
-    quant_param.multiplier = 1;
-    quants.emplace_back(quant_param);
-    input_quant_params.emplace_back(quants);
-  }
-  // fill input_quant_param_ by not inited quant_parm
-  if (input_quant_params.size() < input_size) {
-    schema::QuantParamT tmpQuantParam;
-    quants.emplace_back(tmpQuantParam);
-    input_quant_params.insert(input_quant_params.end(), input_size - input_quant_params.size(), quants);
-  }
-  quant_param_holder->set_input_quant_params(input_quant_params);
-}
-
 int ConvertInputQuantParam(const PrimitivePtr &prim, bool narrow_range, int32_t numbits) {
   auto quant_tensor_info_ptr = prim->GetAttr("quant_params");
   if (quant_tensor_info_ptr == nullptr) {
@@ -212,7 +178,6 @@ int ConvertQuantParam(const PrimitivePtr &prim, const std::vector<AnfNodePtr> &i
     MS_LOG(ERROR) << "compute int quant param failed.";
     return status;
   }
-  FillDefaultInputQuantParamIfNeed(prim, inputs.size());
   status = ConvertOutputQuantParam(prim, narrow_range_param, num_bits_param);
   if (status != lite::RET_OK) {
     MS_LOG(ERROR) << "compute output quant param failed.";