!49811 fix ascend int8 clip & bn precision issue.

Merge pull request !49811 from yeyunpeng2020/master_ci

mindspore/lite/tools/converter/adapter/acl/src/acl_pass_impl.cc

@@ -48,6 +48,7 @@
 #include "tools/optimizer/common/pass_manager_extends.h"
 #include "tools/optimizer/graph/clip_convert_activation_pass.h"
 #include "tools/optimizer/fusion/transpose_fusion.h"
+#include "tools/optimizer/fusion/batchnorm_to_scale_fusion.h"
 #include "tools/converter/quantizer/full_quant_quantizer.h"
 #include "tools/converter/quantizer/insert_quant_node_manager.h"
 #include "tools/converter/parser/unify_format.h"
@@ -768,6 +769,8 @@ STATUS AclPassImpl::PreQuantization(const FuncGraphPtr &func_graph) {
   auto fusion_pm = std::make_shared<opt::LitePassManager>("anf fusion pass manager", false);
   CHECK_NULL_RETURN(fusion_pm);
   std::vector<opt::PassPtr> fusions{
+    std::make_shared<opt::ClipConvertActivationPass>(true),
+    std::make_shared<opt::BatchNormToScaleFusion>(),
     std::make_shared<opt::ConvBiasaddFusion>(),
     std::make_shared<opt::ConvBatchNormFusion>(param_->fmk_type),
     std::make_shared<opt::ConvScaleFusion>(param_->fmk_type),

mindspore/lite/tools/converter/quantizer/full_quant_quantizer.cc

@@ -514,7 +514,7 @@ void FullQuantQuantizer::InitAscendConfig() {
   init_param_.activation_symmetric_ = false;
   init_param_.weight_channel_symmetric_ = true;
   init_param_.weight_layer_symmetric_ = false;
-  support_int8_ops_ = {prim::kPrimConv2DFusion, prim::kPrimFullConnection};
+  support_int8_ops_ = {prim::kPrimConv2DFusion};
   per_channel_ops_ = {prim::kPrimConv2DFusion};
 }
 

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

@@ -80,15 +80,20 @@ bool ClipConvertActivationPass::Run(const FuncGraphPtr &graph) {
         max = *reinterpret_cast<float *>(max_tensor_info->data_c());
       }
     }
+    bool is_relu6 = min == 0 && max == kValueThreshold6;
+    bool is_relu = lite::FloatCompare(min) && lite::FloatCompare(max, FLT_MAX);
+    if (only_relu_ && !(is_relu6 || is_relu)) {
+      return false;
+    }
     auto manager = graph->manager();
     MS_ASSERT(manager != nullptr);
     auto primitive_c = std::make_shared<mindspore::ops::Activation>();
     MS_CHECK_TRUE_MSG(primitive_c != nullptr, false, "primitive_c is nullptr");
     primitive_c->Init(0, min, max, mindspore::HARD_TANH);
-    if (min == 0 && max == kValueThreshold6) {
+    if (is_relu6) {
       primitive_c->set_activation_type(mindspore::RELU6);
     }
-    if (lite::FloatCompare(min) && lite::FloatCompare(max, FLT_MAX)) {
+    if (is_relu) {
       primitive_c->set_activation_type(mindspore::RELU);
     }
     auto primitive = primitive_c->GetPrim();

mindspore/lite/tools/optimizer/graph/clip_convert_activation_pass.h

@@ -22,9 +22,14 @@
 namespace mindspore::opt {
 class ClipConvertActivationPass : public Pass {
  public:
-  ClipConvertActivationPass() : Pass("clip_convert_activation_pass") {}
+  explicit ClipConvertActivationPass(bool only_relu = false) : Pass("clip_convert_activation_pass") {
+    only_relu_ = only_relu;
+  }
   ~ClipConvertActivationPass() override = default;
   bool Run(const FuncGraphPtr &graph) override;
+
+ private:
+  bool only_relu_ = false;
 };
 }  // namespace mindspore::opt
 #endif  // MINDSPORE_LITE_TOOLS_OPTIMIZER_GRAPH_CLIP_CONVERT_ACTIVATION_PASS_H_