diff --git a/mindspore/lite/schema/model.fbs b/mindspore/lite/schema/model.fbs
index d2d7b806e87e28c403b2215dd8c346a7db5ce374..286077299d41bd75828d744c6923f0f61f8d1c37 100644
--- a/mindspore/lite/schema/model.fbs
+++ b/mindspore/lite/schema/model.fbs
@@ -179,6 +179,7 @@ union PrimitiveType {
     Conv2DGradInput,
     PoolingGrad,
     BNGrad,
+    BNGradInput,
     ApplyMomentum,
     BiasGrad,
     SoftmaxCrossEntropy,
diff --git a/mindspore/lite/schema/ops.fbs b/mindspore/lite/schema/ops.fbs
index 3ad035c0f7741e88fbd135bda8d2c9f40bf1fde3..2e13afa463605b2f5f099cc9c3299a9285308d9d 100644
--- a/mindspore/lite/schema/ops.fbs
+++ b/mindspore/lite/schema/ops.fbs
@@ -398,7 +398,10 @@ table BNGrad {
     eps : float;
     momentum: float;
 }
-
+table BNGradInput {
+    eps : float;
+    momentum: float;
+}
 table Scale {
     axis: int;
 }
diff --git a/mindspore/lite/src/ops/activation_grad.cc b/mindspore/lite/src/ops/activation_grad.cc
index 0554e53040169e2a82a63a2e594180038f6cc2ff..0efed3a6ab3f49c0741a70ef2badd0da38824c09 100644
--- a/mindspore/lite/src/ops/activation_grad.cc
+++ b/mindspore/lite/src/ops/activation_grad.cc
@@ -25,6 +25,36 @@ void ActivationGrad::SetType(int type) {
   this->primitive_->value.AsActivationGrad()->type = (schema::ActivationType)type;
 }
 void ActivationGrad::SetAlpha(float alpha) { this->primitive_->value.AsActivationGrad()->alpha = alpha; }
+int ActivationGrad::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_ActivationGrad;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_ActivationGrad) {
+    MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  auto attr = std::make_unique<schema::ActivationGradT>();
+  if (prim.name() == "ReLU") {
+    attr->type = schema::ActivationType_RELU;
+  } else if (prim.name() == "Sigmoid") {
+    attr->type = schema::ActivationType_SIGMOID;
+  } else if (prim.name() == "ReLU6") {
+    attr->type = schema::ActivationType_RELU6;
+  }
+  auto alpha = GetValue<float>(prim.GetAttr("alpha"));
+  attr->alpha = alpha;
+  this->primitive_->value.value = attr.release();
+  if (this->primitive_->value.value == nullptr) {
+    MS_LOG(ERROR) << "new primitiveT value failed";
+    return RET_ERROR;
+  }
+  return RET_OK;
+}
 #else
 int ActivationGrad::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
diff --git a/mindspore/lite/src/ops/activation_grad.h b/mindspore/lite/src/ops/activation_grad.h
index 463043bd7b49d8567b9442a06f786fca9ae59520..907c5c589e68b97d015aaa3ea1c21941e813cc82 100644
--- a/mindspore/lite/src/ops/activation_grad.h
+++ b/mindspore/lite/src/ops/activation_grad.h
@@ -20,6 +20,7 @@
 #include <vector>
 #include <set>
 #include <cmath>
+#include <memory>
 #include "ir/dtype/type_id.h"
 #include "src/ops/primitive_c.h"
 
@@ -33,6 +34,7 @@ class ActivationGrad : public PrimitiveC {
   explicit ActivationGrad(schema::PrimitiveT *primitive) : PrimitiveC(primitive) {}
   void SetType(int type);
   void SetAlpha(float alpha);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
   ActivationGrad() = default;
 
diff --git a/mindspore/lite/src/ops/bias_grad.cc b/mindspore/lite/src/ops/bias_grad.cc
index d571ed3d0911f0575e914c12f5bb4826fbd08066..c3c4ac899bc1095636845803f5c0ea2fa49f9d46 100644
--- a/mindspore/lite/src/ops/bias_grad.cc
+++ b/mindspore/lite/src/ops/bias_grad.cc
@@ -22,7 +22,34 @@ namespace lite {
 std::vector<int> BiasGrad::GetAxis() const { return this->primitive_->value.AsBiasGrad()->axis; }
 
 void BiasGrad::SetAxis(const std::vector<int> &axis) { this->primitive_->value.AsBiasGrad()->axis = axis; }
-
+int BiasGrad::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_BiasGrad;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_BiasGrad) {
+    MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  if (this->primitive_->value.value == nullptr) {
+    auto attr = new (std::nothrow) schema::BiasGradT();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT value failed";
+      return RET_ERROR;
+    }
+    attr->axis = GetValue<std::vector<int>>(prim.GetAttr("axis"));
+    this->primitive_->value.value = attr;
+    if (this->primitive_->value.value == nullptr) {
+      MS_LOG(ERROR) << "primitive value is nullptr";
+      return RET_ERROR;
+    }
+  }
+  return RET_OK;
+}
 #else
 int BiasGrad::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
diff --git a/mindspore/lite/src/ops/bias_grad.h b/mindspore/lite/src/ops/bias_grad.h
index 37532961744437d5f2b6b9a82eaa2136b5832c6b..a96fde9aeb6233a7e15f49062572eae75ee2d183 100644
--- a/mindspore/lite/src/ops/bias_grad.h
+++ b/mindspore/lite/src/ops/bias_grad.h
@@ -33,7 +33,7 @@ class BiasGrad : public PrimitiveC {
   BiasGrad() = default;
   explicit BiasGrad(schema::PrimitiveT *primitive) : PrimitiveC(primitive) {}
   void SetAxis(const std::vector<int> &axis);
-
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
   BiasGrad() = default;
 
diff --git a/mindspore/lite/src/ops/bn_grad.h b/mindspore/lite/src/ops/bn_grad.h
index e346593a53599448351b72952de393aa53001c70..0d09639bfef04ae8daf00cd60634535a31ca8eca 100644
--- a/mindspore/lite/src/ops/bn_grad.h
+++ b/mindspore/lite/src/ops/bn_grad.h
@@ -14,8 +14,8 @@
  * limitations under the License.
  */
 
-#ifndef LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_INPUT_H_
-#define LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_INPUT_H_
+#ifndef LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_H_
+#define LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_H_
 
 #include <vector>
 #include <set>
diff --git a/mindspore/lite/src/ops/bn_grad_input.cc b/mindspore/lite/src/ops/bn_grad_input.cc
new file mode 100644
index 0000000000000000000000000000000000000000..d243764979fbe2af644283dbf8a61dcca9ecea3e
--- /dev/null
+++ b/mindspore/lite/src/ops/bn_grad_input.cc
@@ -0,0 +1,75 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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 "src/ops/bn_grad_input.h"
+
+namespace mindspore {
+namespace lite {
+#ifdef PRIMITIVE_WRITEABLE
+float BNGradInput::GetEps() const { return this->primitive_->value.AsBNGradInput()->eps; }
+float BNGradInput::GetMomentum() const { return this->primitive_->value.AsBNGradInput()->momentum; }
+
+void BNGradInput::SetEps(float eps) { this->primitive_->value.AsBNGradInput()->eps = eps; }
+void BNGradInput::SetMomentum(float momentum) { this->primitive_->value.AsBNGradInput()->momentum = momentum; }
+int BNGradInput::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_BNGradInput;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_BNGradInput) {
+    MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  if (this->primitive_->value.value == nullptr) {
+    auto attr = new (std::nothrow) schema::BNGradInputT();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT value failed";
+      return RET_ERROR;
+    }
+    attr->eps = GetValue<float>(prim.GetAttr("eps"));
+    attr->momentum = GetValue<float>(prim.GetAttr("momentum"));
+    this->primitive_->value.value = attr;
+    if (this->primitive_->value.value == nullptr) {
+      MS_LOG(ERROR) << "primitive value is nullptr";
+      return RET_ERROR;
+    }
+  }
+  return RET_OK;
+}
+#else
+int BNGradInput::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
+  MS_ASSERT(nullptr != primitive);
+  MS_ASSERT(nullptr != fbb);
+  auto attr = primitive->value_as_BNGradInput();
+  if (attr == nullptr) {
+    MS_LOG(ERROR) << "value_as_BNGradInputInput return nullptr";
+    return RET_ERROR;
+  }
+  auto val_offset = schema::CreateBNGradInput(*fbb, attr->eps(), attr->momentum());
+  auto prim_offset = schema::CreatePrimitive(*fbb, schema::PrimitiveType_BNGradInput, val_offset.o);
+  fbb->Finish(prim_offset);
+  return RET_OK;
+}
+float BNGradInput::GetEps() const { return this->primitive_->value_as_BNGradInput()->eps(); }
+float BNGradInput::GetMomentum() const { return this->primitive_->value_as_BNGradInput()->momentum(); }
+
+#endif
+}  // namespace lite
+}  // namespace mindspore
diff --git a/mindspore/lite/src/ops/bn_grad_input.h b/mindspore/lite/src/ops/bn_grad_input.h
new file mode 100644
index 0000000000000000000000000000000000000000..52645f83f5019d16b916ba56f9d1308fff05e77e
--- /dev/null
+++ b/mindspore/lite/src/ops/bn_grad_input.h
@@ -0,0 +1,47 @@
+/**
+ * Copyright 2019-2020 Huawei Technologies Co., Ltd
+ *
+ * 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.
+ */
+
+#ifndef LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_INPUT_H_
+#define LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_INPUT_H_
+
+#include <vector>
+#include <set>
+#include <cmath>
+#include "ir/dtype/type_id.h"
+#include "src/ops/primitive_c.h"
+
+namespace mindspore {
+namespace lite {
+class BNGradInput : public PrimitiveC {
+ public:
+#ifdef PRIMITIVE_WRITEABLE
+  MS_DECLARE_PARENT(BNGradInput, PrimitiveC);
+  BNGradInput() = default;
+  explicit BNGradInput(schema::PrimitiveT *primitive) : PrimitiveC(primitive) {}
+  void SetEps(float eps);
+  void SetMomentum(float momentum);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
+#else
+  BNGradInput() = default;
+  int UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) override;
+#endif
+  float GetEps() const;
+  float GetMomentum() const;
+};
+}  // namespace lite
+}  // namespace mindspore
+
+#endif  // LITE_MINDSPORE_LITE_C_OPS_B_N_GRAD_INPUT_H_
diff --git a/mindspore/lite/src/ops/conv2d_grad_filter.cc b/mindspore/lite/src/ops/conv2d_grad_filter.cc
index 32866852944c312968c5fa73f94f32d8576cfba0..37d05fe3f333b43eaf4addff3c7541df71598acc 100644
--- a/mindspore/lite/src/ops/conv2d_grad_filter.cc
+++ b/mindspore/lite/src/ops/conv2d_grad_filter.cc
@@ -66,7 +66,133 @@ void Conv2DGradFilter::SetHasBias(bool has_bias) { this->primitive_->value.AsCon
 void Conv2DGradFilter::SetActivationType(int activation_type) {
   this->primitive_->value.AsConv2DGradFilter()->activationType = (schema::ActivationType)activation_type;
 }
+void Conv2DGradFilter::PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT *primitive, 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") {
+    attr->format = schema::Format_NCHW;
+  } else if (format == "NHWC") {
+    attr->format = schema::Format_NHWC;
+  } else {
+    attr->format = schema::Format_NUM_OF_FORMAT;
+  }
+  auto pad_list = GetValue<std::vector<int>>(prim.GetAttr("pad_list"));
+  attr->padUp = pad_list[0];
+  attr->padDown = pad_list[1];
+  attr->padLeft = pad_list[2];
+  attr->padRight = pad_list[3];
+
+  auto dilation = GetValue<std::vector<int>>(prim.GetAttr("dilation"));
+  attr->dilateH = dilation[0];
+  attr->dilateW = dilation[1];
+
+  auto kernel_size = GetValue<std::vector<int>>(prim.GetAttr("kernel_size"));
+  attr->kernelH = kernel_size[0];
+  attr->kernelW = kernel_size[1];
+
+  auto stride = GetValue<std::vector<int>>(prim.GetAttr("stride"));
+  attr->strideH = stride[2];
+  attr->strideW = stride[3];
+
+  auto pad_mode = GetValue<std::string>(prim.GetAttr("pad_mode"));
+  if (pad_mode == "valid") {
+    attr->padMode = schema::PadMode_VALID;
+  } else if (pad_mode == "same") {
+    attr->padMode = schema::PadMode_SAME;
+  } else {
+    attr->padMode = schema::PadMode_NOTSET;
+  }
+
+  if (prim.GetAttr("activation_name") != nullptr) {
+    std::string activate_name = GetValue<std::string>(prim.GetAttr("activation_name"));
+    attr->activationType = kActivationTypeMap[activate_name];
+  } else {
+    attr->activationType = schema::ActivationType_NO_ACTIVATION;
+  }
+
+  int channel_mutiplier = 1;
+  if (prim.GetAttr("channel_mutiplier") != nullptr) {
+    channel_mutiplier = GetValue<int>(prim.GetAttr("channel_multiplier"));
+  }
+  attr->channelMultiplier = channel_mutiplier;
+
+  primitive->value.type = schema::PrimitiveType_DepthwiseConv2D;
+  primitive->value.value = attr.release();
+}
+
+void Conv2DGradFilter::PopulaterConv2DSingleGroup(const Primitive &prim,
+  schema::PrimitiveT *primitive, const int &group) {
+  auto attr = std::make_unique<schema::Conv2DT>();
+  attr->group = group;
+  auto format = GetValue<std::string>(prim.GetAttr("data_format"));
+  if (format == "NCHW") {
+    attr->format = schema::Format_NCHW;
+  } else if (format == "NHWC") {
+    attr->format = schema::Format_NHWC;
+  } else {
+    attr->format = schema::Format_NUM_OF_FORMAT;
+  }
+  auto pad_list = GetValue<std::vector<int>>(prim.GetAttr("pad_list"));
+  attr->padUp = pad_list[0];
+  attr->padDown = pad_list[1];
+  attr->padLeft = pad_list[2];
+  attr->padRight = pad_list[3];
+
+  auto dilation = GetValue<std::vector<int>>(prim.GetAttr("dilation"));
+  attr->dilateH = dilation[0];
+  attr->dilateW = dilation[1];
 
+  auto kernel_size = GetValue<std::vector<int>>(prim.GetAttr("kernel_size"));
+  attr->kernelH = kernel_size[0];
+  attr->kernelW = kernel_size[1];
+
+  auto stride = GetValue<std::vector<int>>(prim.GetAttr("stride"));
+  attr->strideH = stride[2];
+  attr->strideW = stride[3];
+
+  attr->channelOut = GetValue<int>(prim.GetAttr("out_channel"));
+
+  auto pad_mode = GetValue<std::string>(prim.GetAttr("pad_mode"));
+  if (pad_mode == "valid") {
+    attr->padMode = schema::PadMode_VALID;
+  } else if (pad_mode == "same") {
+    attr->padMode = schema::PadMode_SAME;
+  } else {
+    attr->padMode = schema::PadMode_NOTSET;
+  }
+
+  if (prim.GetAttr("activation_name") != nullptr) {
+    std::string activate_name = GetValue<std::string>(prim.GetAttr("activation_name"));
+    attr->activationType = kActivationTypeMap[activate_name];
+  } else {
+    attr->activationType = schema::ActivationType_NO_ACTIVATION;
+  }
+
+  primitive->value.type = schema::PrimitiveType_Conv2D;
+  primitive->value.value = attr.release();
+}
+int Conv2DGradFilter::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_Conv2DGradFilter;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_Conv2DGradFilter) {
+    MS_LOG(ERROR) << "primitive_ type is error:" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  int group = GetValue<int>(prim.GetAttr("group"));
+  if (group > 1) {
+    PopulaterConv2DMultiGroup(prim, this->primitive_, group, inputs);
+  } else {
+    PopulaterConv2DSingleGroup(prim, this->primitive_, group);
+  }
+  return RET_OK;
+}
 #else
 int Conv2DGradFilter::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
diff --git a/mindspore/lite/src/ops/conv2d_grad_filter.h b/mindspore/lite/src/ops/conv2d_grad_filter.h
index 96c189d3be0bb858c98681835006db05f725dac8..46917b5413a3ec15fc17e3eb45c9c35185f1f1b9 100644
--- a/mindspore/lite/src/ops/conv2d_grad_filter.h
+++ b/mindspore/lite/src/ops/conv2d_grad_filter.h
@@ -20,6 +20,8 @@
 #include <vector>
 #include <set>
 #include <cmath>
+#include <memory>
+#include <string>
 #include "ir/dtype/type_id.h"
 #include "src/ops/primitive_c.h"
 
@@ -48,6 +50,10 @@ class Conv2DGradFilter : public PrimitiveC {
   void SetDilateH(int dilate_h);
   void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
+  void PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group,
+                                 const std::vector<AnfNodePtr> &inputs);
+  void PopulaterConv2DSingleGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group);
 #else
   Conv2DGradFilter() = default;
 
diff --git a/mindspore/lite/src/ops/conv2d_grad_input.cc b/mindspore/lite/src/ops/conv2d_grad_input.cc
index 1c078b9cd67c3212ffa432f2116c39eeafec1c73..85a5156e973ef467143976b68c5e665a0c1327ca 100644
--- a/mindspore/lite/src/ops/conv2d_grad_input.cc
+++ b/mindspore/lite/src/ops/conv2d_grad_input.cc
@@ -64,7 +64,133 @@ void Conv2DGradInput::SetHasBias(bool has_bias) { this->primitive_->value.AsConv
 void Conv2DGradInput::SetActivationType(int activation_type) {
   this->primitive_->value.AsConv2DGradInput()->activationType = (schema::ActivationType)activation_type;
 }
+void Conv2DGradInput::PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT *primitive, 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") {
+    attr->format = schema::Format_NCHW;
+  } else if (format == "NHWC") {
+    attr->format = schema::Format_NHWC;
+  } else {
+    attr->format = schema::Format_NUM_OF_FORMAT;
+  }
+  auto pad_list = GetValue<std::vector<int>>(prim.GetAttr("pad_list"));
+  attr->padUp = pad_list[0];
+  attr->padDown = pad_list[1];
+  attr->padLeft = pad_list[2];
+  attr->padRight = pad_list[3];
+
+  auto dilation = GetValue<std::vector<int>>(prim.GetAttr("dilation"));
+  attr->dilateH = dilation[0];
+  attr->dilateW = dilation[1];
+
+  auto kernel_size = GetValue<std::vector<int>>(prim.GetAttr("kernel_size"));
+  attr->kernelH = kernel_size[0];
+  attr->kernelW = kernel_size[1];
+
+  auto stride = GetValue<std::vector<int>>(prim.GetAttr("stride"));
+  attr->strideH = stride[2];
+  attr->strideW = stride[3];
+
+  auto pad_mode = GetValue<std::string>(prim.GetAttr("pad_mode"));
+  if (pad_mode == "valid") {
+    attr->padMode = schema::PadMode_VALID;
+  } else if (pad_mode == "same") {
+    attr->padMode = schema::PadMode_SAME;
+  } else {
+    attr->padMode = schema::PadMode_NOTSET;
+  }
+
+  if (prim.GetAttr("activation_name") != nullptr) {
+    std::string activate_name = GetValue<std::string>(prim.GetAttr("activation_name"));
+    attr->activationType = kActivationTypeMap[activate_name];
+  } else {
+    attr->activationType = schema::ActivationType_NO_ACTIVATION;
+  }
+
+  int channel_mutiplier = 1;
+  if (prim.GetAttr("channel_mutiplier") != nullptr) {
+    channel_mutiplier = GetValue<int>(prim.GetAttr("channel_multiplier"));
+  }
+  attr->channelMultiplier = channel_mutiplier;
+
+  primitive->value.type = schema::PrimitiveType_DepthwiseConv2D;
+  primitive->value.value = attr.release();
+}
+
+void Conv2DGradInput::PopulaterConv2DSingleGroup(const Primitive &prim,
+  schema::PrimitiveT *primitive, const int &group) {
+  auto attr = std::make_unique<schema::Conv2DT>();
+  attr->group = group;
+  auto format = GetValue<std::string>(prim.GetAttr("data_format"));
+  if (format == "NCHW") {
+    attr->format = schema::Format_NCHW;
+  } else if (format == "NHWC") {
+    attr->format = schema::Format_NHWC;
+  } else {
+    attr->format = schema::Format_NUM_OF_FORMAT;
+  }
+  auto pad_list = GetValue<std::vector<int>>(prim.GetAttr("pad_list"));
+  attr->padUp = pad_list[0];
+  attr->padDown = pad_list[1];
+  attr->padLeft = pad_list[2];
+  attr->padRight = pad_list[3];
+
+  auto dilation = GetValue<std::vector<int>>(prim.GetAttr("dilation"));
+  attr->dilateH = dilation[0];
+  attr->dilateW = dilation[1];
 
+  auto kernel_size = GetValue<std::vector<int>>(prim.GetAttr("kernel_size"));
+  attr->kernelH = kernel_size[0];
+  attr->kernelW = kernel_size[1];
+
+  auto stride = GetValue<std::vector<int>>(prim.GetAttr("stride"));
+  attr->strideH = stride[2];
+  attr->strideW = stride[3];
+
+  attr->channelOut = GetValue<int>(prim.GetAttr("out_channel"));
+
+  auto pad_mode = GetValue<std::string>(prim.GetAttr("pad_mode"));
+  if (pad_mode == "valid") {
+    attr->padMode = schema::PadMode_VALID;
+  } else if (pad_mode == "same") {
+    attr->padMode = schema::PadMode_SAME;
+  } else {
+    attr->padMode = schema::PadMode_NOTSET;
+  }
+
+  if (prim.GetAttr("activation_name") != nullptr) {
+    std::string activate_name = GetValue<std::string>(prim.GetAttr("activation_name"));
+    attr->activationType = kActivationTypeMap[activate_name];
+  } else {
+    attr->activationType = schema::ActivationType_NO_ACTIVATION;
+  }
+
+  primitive->value.type = schema::PrimitiveType_Conv2D;
+  primitive->value.value = attr.release();
+}
+int Conv2DGradInput::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_Conv2DGradInput;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_Conv2DGradInput) {
+    MS_LOG(ERROR) << "primitive_ type is error:" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  int group = GetValue<int>(prim.GetAttr("group"));
+  if (group > 1) {
+    PopulaterConv2DMultiGroup(prim, this->primitive_, group, inputs);
+  } else {
+    PopulaterConv2DSingleGroup(prim, this->primitive_, group);
+  }
+  return RET_OK;
+}
 #else
 int Conv2DGradInput::UnPackToFlatBuilder(const schema::Primitive *primitive, flatbuffers::FlatBufferBuilder *fbb) {
   MS_ASSERT(nullptr != primitive);
diff --git a/mindspore/lite/src/ops/conv2d_grad_input.h b/mindspore/lite/src/ops/conv2d_grad_input.h
index d6dab8522b0c0036bdf8b373819a1d10b38d56ba..4656addee34a59a940d362451e0bfd2e1ff76719 100644
--- a/mindspore/lite/src/ops/conv2d_grad_input.h
+++ b/mindspore/lite/src/ops/conv2d_grad_input.h
@@ -20,6 +20,8 @@
 #include <vector>
 #include <set>
 #include <cmath>
+#include <memory>
+#include <string>
 #include "ir/dtype/type_id.h"
 #include "src/ops/primitive_c.h"
 
@@ -48,6 +50,10 @@ class Conv2DGradInput : public PrimitiveC {
   void SetDilateH(int dilate_h);
   void SetHasBias(bool has_bias);
   void SetActivationType(int activation_type);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
+  void PopulaterConv2DMultiGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group,
+                                 const std::vector<AnfNodePtr> &inputs);
+  void PopulaterConv2DSingleGroup(const Primitive &prim, schema::PrimitiveT *primitive, const int &group);
 #else
   Conv2DGradInput() = default;
 
diff --git a/mindspore/lite/src/ops/pooling_grad.cc b/mindspore/lite/src/ops/pooling_grad.cc
index 17bc053c49e0e7f61320c70debd33e4f1b5dfa6e..7eba1875a11e5eac5c9ba11f1640d8699edfee03 100644
--- a/mindspore/lite/src/ops/pooling_grad.cc
+++ b/mindspore/lite/src/ops/pooling_grad.cc
@@ -52,7 +52,64 @@ void PoolingGrad::SetPadRight(int pad_right) { this->primitive_->value.AsPooling
 void PoolingGrad::SetRoundMode(int round_mode) {
   this->primitive_->value.AsPoolingGrad()->roundMode = (schema::RoundMode)round_mode;
 }
+int PoolingGrad::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_PoolingGrad;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_PoolingGrad) {
+    MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  if (this->primitive_->value.value == nullptr) {
+    auto attr = new (std::nothrow) schema::PoolingGradT();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT value failed";
+      return RET_ERROR;
+    }
+
+    auto format = GetValue<std::string>(prim.GetAttr("data_format"));
+    if (format == "NCHW") {
+      attr->format = schema::Format_NCHW;
+    } else if (format == "NHWC") {
+      attr->format = schema::Format_NHWC;
+    } else {
+      attr->format = schema::Format_NUM_OF_FORMAT;
+    }
+    if (prim.instance_name() == "MaxPool") {
+      attr->poolingMode = schema::PoolMode_MAX_POOLING;
+    } else if (prim.instance_name() == "MeanPool") {
+      attr->poolingMode = schema::PoolMode_MEAN_POOLING;
+    }
 
+    auto pad_mode = GetValue<std::string>(prim.GetAttr("padding"));
+    if (pad_mode == "VALID") {
+      attr->padMode = schema::PadMode_VALID;
+    } else if (pad_mode == "SAME") {
+      attr->padMode = schema::PadMode_SAME;
+    } else {
+      attr->padMode = schema::PadMode_NOTSET;
+    }
+
+    auto kernel_size = GetValue<std::vector<int>>(prim.GetAttr("ksize"));
+    attr->windowH = kernel_size[2];
+    attr->windowW = kernel_size[3];
+
+    auto stride = GetValue<std::vector<int>>(prim.GetAttr("strides"));
+    attr->strideH = stride[2];
+    attr->strideW = stride[3];
+    this->primitive_->value.value = attr;
+    if (this->primitive_->value.value == nullptr) {
+      MS_LOG(ERROR) << "primitive value is nullptr";
+      return RET_ERROR;
+    }
+  }
+  return RET_OK;
+}
 #else
 
 int PoolingGrad::GetFormat() const { return this->primitive_->value_as_PoolingGrad()->format(); }
diff --git a/mindspore/lite/src/ops/pooling_grad.h b/mindspore/lite/src/ops/pooling_grad.h
index dbafdb9254405394ef5d30eda060e238ebba6b79..1fe47eb327aa604a00d1f869f32830e7c6c46ab5 100644
--- a/mindspore/lite/src/ops/pooling_grad.h
+++ b/mindspore/lite/src/ops/pooling_grad.h
@@ -20,6 +20,7 @@
 #include <vector>
 #include <set>
 #include <cmath>
+#include <string>
 #include "ir/dtype/type_id.h"
 #include "src/ops/primitive_c.h"
 
@@ -44,6 +45,7 @@ class PoolingGrad : public PrimitiveC {
   void SetPadLeft(int pad_left);
   void SetPadRight(int pad_right);
   void SetRoundMode(int round_mode);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
   PoolingGrad() = default;
 
diff --git a/mindspore/lite/src/ops/power_grad.cc b/mindspore/lite/src/ops/power_grad.cc
index ba10623dece228e35a20bdb0159b0ae9826c41a1..5529e1055a0b3695e65eded0c9d802677eabfca8 100644
--- a/mindspore/lite/src/ops/power_grad.cc
+++ b/mindspore/lite/src/ops/power_grad.cc
@@ -26,7 +26,36 @@ float PowerGrad::GetShift() const { return this->primitive_->value.AsPowerGrad()
 void PowerGrad::SetPower(float power) { this->primitive_->value.AsPowerGrad()->power = power; }
 void PowerGrad::SetScale(float scale) { this->primitive_->value.AsPowerGrad()->scale = scale; }
 void PowerGrad::SetShift(float shift) { this->primitive_->value.AsPowerGrad()->shift = shift; }
-
+int PowerGrad::UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) {
+  if (this->primitive_ == nullptr) {
+    this->primitive_ = new (std::nothrow) schema::PrimitiveT;
+    if (this->primitive_ == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT failed";
+      return RET_ERROR;
+    }
+    this->primitive_->value.type = schema::PrimitiveType_PowerGrad;
+  }
+  if (this->primitive_->value.type != schema::PrimitiveType_PowerGrad) {
+    MS_LOG(ERROR) << "Primitive type is error :" << this->primitive_->value.type;
+    return RET_ERROR;
+  }
+  if (this->primitive_->value.value == nullptr) {
+    auto attr = new (std::nothrow) schema::PowerGradT();
+    if (attr == nullptr) {
+      MS_LOG(ERROR) << "new primitiveT value failed";
+      return RET_ERROR;
+    }
+    attr->power = GetValue<float>(prim.GetAttr("power"));
+    attr->scale = GetValue<float>(prim.GetAttr("scale"));
+    attr->shift = GetValue<float>(prim.GetAttr("shift"));
+    this->primitive_->value.value = attr;
+    if (this->primitive_->value.value == nullptr) {
+      MS_LOG(ERROR) << "primitive value is nullptr";
+      return RET_ERROR;
+    }
+  }
+  return RET_OK;
+}
 #else
 
 float PowerGrad::GetPower() const { return this->primitive_->value_as_PowerGrad()->power(); }
diff --git a/mindspore/lite/src/ops/power_grad.h b/mindspore/lite/src/ops/power_grad.h
index a3fbd79986f67e696563925da7694487f24b9dde..4c98e37f10b4e9f6e89bb8c50f01c3388808ef46 100644
--- a/mindspore/lite/src/ops/power_grad.h
+++ b/mindspore/lite/src/ops/power_grad.h
@@ -34,6 +34,7 @@ class PowerGrad : public PrimitiveC {
   void SetPower(float power);
   void SetScale(float scale);
   void SetShift(float shift);
+  int UnPackAttr(const Primitive &prim, const std::vector<AnfNodePtr> &inputs) override;
 #else
   PowerGrad() = default;
 
diff --git a/mindspore/lite/src/ops/primitive_c.cc b/mindspore/lite/src/ops/primitive_c.cc
index 961cd6cf1846a7b8f5d4e43d507a5b544b112d15..fa52d02c6881f32123cedb9f105f8849e17907b4 100644
--- a/mindspore/lite/src/ops/primitive_c.cc
+++ b/mindspore/lite/src/ops/primitive_c.cc
@@ -383,6 +383,20 @@ std::shared_ptr<PrimitiveC> PrimitiveC::UnPackFromPrimitive(const Primitive &pri
     return NewPrimitiveC<ApplyMomentum>(prim, inputs, quantType);
   } else if (op_type == "BatchNormGrad") {
     return NewPrimitiveC<BNGrad>(prim, inputs, quantType);
+  } else if (op_type == "Conv2DGradInput") {
+    return NewPrimitiveC<Conv2DGradInput>(prim, inputs, quantType);
+  } else if (op_type == "Conv2DGradFilter") {
+    return NewPrimitiveC<Conv2DGradFilter>(prim, inputs, quantType);
+  } else if (op_type == "BiasGrad") {
+    return NewPrimitiveC<BiasGrad>(prim, inputs, quantType);
+  } else if (op_type == "ActivationGrad") {
+    return NewPrimitiveC<ActivationGrad>(prim, inputs, quantType);
+  } else if (op_type == "PoolingGrad") {
+    return NewPrimitiveC<PoolingGrad>(prim, inputs, quantType);
+  } else if (op_type == "BNGradInput") {
+    return NewPrimitiveC<BNGradInput>(prim, inputs, quantType);
+  } else if (op_type == "PowerGrad") {
+    return NewPrimitiveC<PowerGrad>(prim, inputs, quantType);
 #endif
   } else {
     MS_LOG(ERROR) << "Unsupported primitive type in UnPackFromPrimitive : " << op_type;
@@ -620,6 +634,10 @@ PrimitiveC *PrimitiveC::UnPackFromSchemaPrimitiveT(mindspore::schema::PrimitiveT
       return new ArithmeticGrad(primitive);
     case schema::PrimitiveType_DivGrad:
       return new ArithmeticGrad(primitive);
+    case schema::PrimitiveType_PowerGrad:
+      return new PowerGrad(primitive);
+    case schema::PrimitiveType_BNGradInput:
+      return new BNGradInput(primitive);
 #endif
 
     default: