diff --git a/mindspore/lite/tools/anf_exporter/anf_exporter.cc b/mindspore/lite/tools/anf_exporter/anf_exporter.cc
index 68bf5ff4b716588b027a63d1ce0de3ff3cb2e881..b4541097ff26aeab82aa1363fd463ea87ac16bc8 100644
--- a/mindspore/lite/tools/anf_exporter/anf_exporter.cc
+++ b/mindspore/lite/tools/anf_exporter/anf_exporter.cc
@@ -387,7 +387,8 @@ void AnfExporter::SetOpOutputNode(const CNodePtr &cnode, const std::unique_ptr<s
       }
       meta_graphT->allTensors.emplace_back(msTensor);
       if (IsPrimitiveCNode(cnode, schema::PrimitiveType_Conv2D)
-          || IsPrimitiveCNode(cnode, schema::PrimitiveType_DepthwiseConv2D)) {
+          || IsPrimitiveCNode(cnode, schema::PrimitiveType_DepthwiseConv2D)
+          || IsPrimitiveCNode(cnode, schema::PrimitiveType_FusedBatchNorm)) {
         break;
       }
     }
diff --git a/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.cc b/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.cc
index ac38c7967136fc2abd4360d60ef2d2caecd64462..523c73501b51532fcefc392a3da33aae33ce8740 100644
--- a/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.cc
+++ b/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.cc
@@ -29,7 +29,7 @@
 namespace mindspore::lite {
 void AnfConvPopulater::PopulaterConv2DMultiGroup(const PrimitivePtr &prim,
                                                  const std::unique_ptr<schema::PrimitiveT> &primitive,
-                                                 const int &group) {
+                                                 const int &group, const std::vector<AnfNodePtr> &inputs) {
   auto attr = std::make_unique<schema::DepthwiseConv2DT>();
   auto format = GetValue<std::string>(prim->GetAttr("data_format"));
   if (format == "NCHW") {
@@ -66,6 +66,28 @@ void AnfConvPopulater::PopulaterConv2DMultiGroup(const PrimitivePtr &prim,
     attr->padMode = schema::PadMode_NOTSET;
   }
 
+  int channel_mutiplier = 1;
+  if (prim->GetAttr("channel_mutiplier") != nullptr) {
+    channel_mutiplier = GetValue<int>(prim->GetAttr("channel_multiplier"));
+  }
+  attr->channelMultiplier = channel_mutiplier;
+
+  MS_ASSERT(inputs.size() == kAnfPopulaterTwo);
+  auto inputNode = inputs[kAnfPopulaterOne];
+  MS_ASSERT(inputNode != nullptr);
+  if (inputNode->isa<Parameter>()) {
+    auto paramNode = inputNode->cast<ParameterPtr>();
+    auto abstractBase = paramNode->abstract();
+    MS_ASSERT(abstractBase != nullptr);
+    if (utils::isa<abstract::AbstractTensorPtr>(abstractBase)) {
+      auto abstractTensor = utils::cast<abstract::AbstractTensorPtr>(abstractBase);
+      MS_ASSERT(abstractTensor != nullptr);
+      if (abstractTensor->format() == schema::Format_NCHW) {
+        abstractTensor->set_format(schema::Format_KCHW);
+      }
+    }
+  }
+
   primitive->value.type = schema::PrimitiveType_DepthwiseConv2D;
   primitive->value.value = attr.release();
 }
@@ -214,7 +236,7 @@ int AnfConvPopulater::Populate(const PrimitivePtr &prim, PrimitiveTValue *primit
 
   int group = GetValue<int>(prim->GetAttr("group"));
   if (group > 1) {
-    PopulaterConv2DMultiGroup(prim, primitive, group);
+    PopulaterConv2DMultiGroup(prim, primitive, group, inputs);
   } else {
     PopulaterConv2DSingleGroup(prim, primitive, group);
   }
diff --git a/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.h b/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.h
index 678897fe92eced506d9aa9dba17ef35b2e19d792..7386b24afe20eb74c3defaa08499d49cb4ec109f 100644
--- a/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.h
+++ b/mindspore/lite/tools/anf_importer/anf_populater/anf_conv_populater.h
@@ -35,7 +35,7 @@ class AnfConvPopulater : public AnfNodePopulater {
  private:
   void PopulaterConv2DMultiGroup(
       const PrimitivePtr &prim,
-      const std::unique_ptr<schema::PrimitiveT> &primitive, const int &group);
+      const std::unique_ptr<schema::PrimitiveT> &primitive, const int &group, const std::vector<AnfNodePtr> &inputs);
   void PopulaterConv2DSingleGroup(
       const PrimitivePtr &prim,
       const std::unique_ptr<schema::PrimitiveT> &primitive, const int &group);
diff --git a/mindspore/lite/tools/anf_importer/import_from_protobuf.cc b/mindspore/lite/tools/anf_importer/import_from_protobuf.cc
index 3b5b8c40b0e6831daeb720c4b14e91dfa260f570..9b7991d8d6667a79ed2a61a5184430eeb2f3fb52 100644
--- a/mindspore/lite/tools/anf_importer/import_from_protobuf.cc
+++ b/mindspore/lite/tools/anf_importer/import_from_protobuf.cc
@@ -1129,7 +1129,12 @@ bool AnfImporterFromProtobuf::BuildReturnForFuncGraph(const FuncGraphPtr &output
     auto abstract_tensor = std::make_shared<abstract::AbstractTensor>(type_ptr, output_shape);
 
     inputs.clear();
-    inputs.push_back(NewValueNode(prim::kPrimReturn));
+    auto primReturn = std::make_unique<schema::PrimitiveT>();
+    MS_ASSERT(primReturn != nullptr);
+    primReturn->value.type = schema::PrimitiveType_Return;
+    std::shared_ptr<PrimitiveTValue> primitiveTReturnValuePtr = std::make_shared<PrimitiveTValue>(primReturn.release());
+    MS_ASSERT(primitiveTReturnValuePtr != nullptr);
+    inputs.push_back(NewValueNode(primitiveTReturnValuePtr));
     inputs.push_back(cnode_ptr);
     auto return_node = outputFuncGraph->NewCNode(inputs);
     MS_EXCEPTION_IF_NULL(return_node);
diff --git a/mindspore/lite/tools/converter/legacy_optimizer/graph/weight_format_hardcode_pass.cc b/mindspore/lite/tools/converter/legacy_optimizer/graph/weight_format_hardcode_pass.cc
index b8aa778b906815ad590bd4f0686128e491f2db52..5c25e73a6f5a1444375149c86ebe3d7b9e8a0c05 100644
--- a/mindspore/lite/tools/converter/legacy_optimizer/graph/weight_format_hardcode_pass.cc
+++ b/mindspore/lite/tools/converter/legacy_optimizer/graph/weight_format_hardcode_pass.cc
@@ -18,6 +18,7 @@
 #include "tools/common/converter_op_utils.h"
 #include "utils/log_adapter.h"
 #include "src/common/utils.h"
+#include "tools/common/node_util.h"
 
 namespace mindspore {
 namespace lite {
@@ -166,6 +167,9 @@ STATUS WeightFormatHardCodePass::HardCodeMS(const std::unique_ptr<CNodeT> &node,
       if (opType == PrimitiveType_Conv2D) {
         weightTensor->format = Format_KCHW;
       } else if (opType == PrimitiveType_DepthwiseConv2D) {
+        if (weightTensor->format == Format_KCHW) {
+          TransFilterFormat<float>(weightTensor.get(), kKCHW2CKHW);
+        }
         weightTensor->format = Format_CKHW;
       } else {
         MS_LOG(ERROR) << "Unsupported opType: " << EnumNamePrimitiveType(opType) << ", node: " << node->name;