diff --git a/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.cc b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.cc
new file mode 100644
index 0000000000000000000000000000000000000000..a5b2a92bb74c9e2a24dda6a97e0dce0f7ecd7b92
--- /dev/null
+++ b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.cc
@@ -0,0 +1,88 @@
+/**
+ * Copyright 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 "backend/optimizer/gpu/replace_bn_grad_cast2_fusion.h"
+
+#include <memory>
+#include <vector>
+#include <string>
+
+#include "backend/session/anf_runtime_algorithm.h"
+#include "ir/primitive.h"
+#include "utils/utils.h"
+#include "backend/optimizer/common/helper.h"
+
+namespace mindspore {
+namespace opt {
+const BaseRef ReplaceBNGradCast2Fusion::DefinePattern() const {
+  VectorRef fbn2g = VectorRef({prim::kPrimFusedBatchNormGrad, dy_, x_, scale_, mean_, var_});
+  VectorRef tupleget = VectorRef({prim::kPrimTupleGetItem, fbn2g, index_});
+  VectorRef out_cast = VectorRef({prim::kPrimCast, tupleget});
+  return out_cast;
+}
+
+const AnfNodePtr ReplaceBNGradCast2Fusion::Process(const FuncGraphPtr &graph, const AnfNodePtr &node,
+                                                   const EquivPtr &equiv) const {
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_EXCEPTION_IF_NULL(node);
+  MS_EXCEPTION_IF_NULL(equiv);
+  auto tuple = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(node), 0);
+  auto index_node = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 1);
+  MS_EXCEPTION_IF_NULL(index_node);
+  auto value_node = index_node->cast<ValueNodePtr>();
+  MS_EXCEPTION_IF_NULL(value_node);
+  int item_idx = GetValue<int>(value_node->value());
+  if (item_idx != 0) {
+    return nullptr;
+  }
+  auto fbn2g = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 0);
+
+  auto dy_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 0);
+  auto x_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 1);
+
+  auto scale = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 2);
+  auto mean = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 3);
+  auto var = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 4);
+
+  MS_EXCEPTION_IF_NULL(fbn2g);
+  MS_EXCEPTION_IF_NULL(dy_);
+  MS_EXCEPTION_IF_NULL(scale);
+  MS_EXCEPTION_IF_NULL(x_);
+  MS_EXCEPTION_IF_NULL(mean);
+  MS_EXCEPTION_IF_NULL(var);
+
+  auto manager = graph->manager();
+  MS_EXCEPTION_IF_NULL(manager);
+  manager->Replace(utils::cast<CNodePtr>(node), utils::cast<CNodePtr>(tuple));
+  std::vector<TypeId> outputs_type;
+  std::vector<std::vector<size_t>> outputs_shape;
+  auto output_num = AnfAlgo::GetOutputTensorNum(fbn2g);
+  for (size_t i = 0; i < output_num; i++) {
+    outputs_type.push_back(AnfAlgo::GetOutputInferDataType(fbn2g, i));
+    outputs_shape.push_back(AnfAlgo::GetOutputInferShape(fbn2g, i));
+  }
+  outputs_type[0] = AnfAlgo::GetPrevNodeOutputInferDataType(fbn2g, 0);
+  AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, fbn2g.get());
+
+  outputs_type.clear();
+  outputs_shape.clear();
+  outputs_type.push_back(AnfAlgo::GetPrevNodeOutputInferDataType(fbn2g, 0));
+  outputs_shape.push_back(AnfAlgo::GetOutputInferShape(tuple, 0));
+  AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, tuple.get());
+
+  return tuple;
+}
+}  // namespace opt
+}  // namespace mindspore
diff --git a/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.h b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.h
new file mode 100644
index 0000000000000000000000000000000000000000..fcb56be7123ba58acf8cd15349b13a4ebeb566ab
--- /dev/null
+++ b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast2_fusion.h
@@ -0,0 +1,54 @@
+/**
+ * Copyright 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 MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_
+#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_
+
+#include <memory>
+#include "backend/optimizer/common/optimizer.h"
+
+namespace mindspore {
+namespace opt {
+class ReplaceBNGradCast2Fusion : public PatternProcessPass {
+ public:
+  explicit ReplaceBNGradCast2Fusion(bool multigraph = true) : PatternProcessPass("replace_grad_cast2", multigraph) {
+    dy_ = std::make_shared<Var>();
+    x_ = std::make_shared<Var>();
+    scale_ = std::make_shared<Var>();
+    mean_ = std::make_shared<Var>();
+    var_ = std::make_shared<Var>();
+    dx_ = std::make_shared<Var>();
+    bn_scale_ = std::make_shared<Var>();
+    bn_bias_ = std::make_shared<Var>();
+    index_ = std::make_shared<Var>();
+  }
+  ~ReplaceBNGradCast2Fusion() override = default;
+  const BaseRef DefinePattern() const override;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+
+ private:
+  VarPtr dy_;
+  VarPtr x_;
+  VarPtr scale_;
+  VarPtr mean_;
+  VarPtr var_;
+  VarPtr dx_;
+  VarPtr bn_scale_;
+  VarPtr bn_bias_;
+  VarPtr index_;
+};
+}  // namespace opt
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST2_FUSION_H_
diff --git a/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.cc b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.cc
new file mode 100644
index 0000000000000000000000000000000000000000..9dba16bf860a57f7cb89513b38a0f16b94784bd2
--- /dev/null
+++ b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.cc
@@ -0,0 +1,91 @@
+/**
+ * Copyright 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 "backend/optimizer/gpu/replace_bn_grad_cast_fusion.h"
+
+#include <memory>
+#include <vector>
+#include <string>
+
+#include "backend/session/anf_runtime_algorithm.h"
+#include "ir/primitive.h"
+#include "utils/utils.h"
+#include "backend/optimizer/common/helper.h"
+
+namespace mindspore {
+namespace opt {
+const BaseRef ReplaceBNGradCastFusion::DefinePattern() const {
+  VectorRef dy_cast = VectorRef({prim::kPrimCast, dy_});
+  VectorRef fbn2g = VectorRef({prim::kPrimFusedBatchNormGrad, dy_cast, x_, scale_, mean_, var_});
+  VectorRef tupleget = VectorRef({prim::kPrimTupleGetItem, fbn2g, index_});
+  VectorRef out_cast = VectorRef({prim::kPrimCast, tupleget});
+  return out_cast;
+}
+
+const AnfNodePtr ReplaceBNGradCastFusion::Process(const FuncGraphPtr &graph, const AnfNodePtr &node,
+                                                  const EquivPtr &equiv) const {
+  MS_EXCEPTION_IF_NULL(graph);
+  MS_EXCEPTION_IF_NULL(node);
+  MS_EXCEPTION_IF_NULL(equiv);
+
+  auto tuple = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(node), 0);
+  auto index_node = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 1);
+  MS_EXCEPTION_IF_NULL(index_node);
+  auto value_node = index_node->cast<ValueNodePtr>();
+  MS_EXCEPTION_IF_NULL(value_node);
+  int item_idx = GetValue<int>(value_node->value());
+  if (item_idx != 0) {
+    return nullptr;
+  }
+  auto fbn2g = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(tuple), 0);
+
+  auto dy_after = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 0);
+  auto dy_before = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(dy_after), 0);
+  auto x_ = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 1);
+
+  auto scale = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 2);
+  auto mean = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 3);
+  auto var = AnfAlgo::GetInputNode(utils::cast<CNodePtr>(fbn2g), 4);
+
+  MS_EXCEPTION_IF_NULL(fbn2g);
+  MS_EXCEPTION_IF_NULL(dy_after);
+  MS_EXCEPTION_IF_NULL(dy_before);
+  MS_EXCEPTION_IF_NULL(scale);
+  MS_EXCEPTION_IF_NULL(x_);
+  MS_EXCEPTION_IF_NULL(mean);
+  MS_EXCEPTION_IF_NULL(var);
+
+  auto manager = graph->manager();
+  MS_EXCEPTION_IF_NULL(manager);
+  manager->Replace(utils::cast<CNodePtr>(dy_after), utils::cast<CNodePtr>(dy_before));
+  manager->Replace(utils::cast<CNodePtr>(node), utils::cast<CNodePtr>(tuple));
+  std::vector<TypeId> outputs_type;
+  std::vector<std::vector<size_t>> outputs_shape;
+  auto output_num = AnfAlgo::GetOutputTensorNum(fbn2g);
+  for (size_t i = 0; i < output_num; i++) {
+    outputs_type.push_back(AnfAlgo::GetOutputInferDataType(fbn2g, i));
+    outputs_shape.push_back(AnfAlgo::GetOutputInferShape(fbn2g, i));
+  }
+  outputs_type[0] = kNumberTypeFloat16;
+  AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, fbn2g.get());
+  outputs_type.clear();
+  outputs_shape.clear();
+  outputs_type.push_back(kNumberTypeFloat16);
+  outputs_shape.push_back(AnfAlgo::GetOutputInferShape(tuple, 0));
+  AnfAlgo::SetOutputInferTypeAndShape(outputs_type, outputs_shape, tuple.get());
+  return tuple;
+}
+}  // namespace opt
+}  // namespace mindspore
diff --git a/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.h b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.h
new file mode 100644
index 0000000000000000000000000000000000000000..b937aa25bf65089673fb1633c32a11922438dbed
--- /dev/null
+++ b/mindspore/ccsrc/backend/optimizer/gpu/replace_bn_grad_cast_fusion.h
@@ -0,0 +1,54 @@
+/**
+ * Copyright 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 MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_
+#define MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_
+
+#include <memory>
+#include "backend/optimizer/common/optimizer.h"
+
+namespace mindspore {
+namespace opt {
+class ReplaceBNGradCastFusion : public PatternProcessPass {
+ public:
+  explicit ReplaceBNGradCastFusion(bool multigraph = true) : PatternProcessPass("replace_bn_grad_cast", multigraph) {
+    dy_ = std::make_shared<Var>();
+    x_ = std::make_shared<Var>();
+    scale_ = std::make_shared<Var>();
+    mean_ = std::make_shared<Var>();
+    var_ = std::make_shared<Var>();
+    dx_ = std::make_shared<Var>();
+    bn_scale_ = std::make_shared<Var>();
+    bn_bias_ = std::make_shared<Var>();
+    index_ = std::make_shared<Var>();
+  }
+  ~ReplaceBNGradCastFusion() override = default;
+  const BaseRef DefinePattern() const override;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+
+ private:
+  VarPtr dy_;
+  VarPtr x_;
+  VarPtr scale_;
+  VarPtr mean_;
+  VarPtr var_;
+  VarPtr dx_;
+  VarPtr bn_scale_;
+  VarPtr bn_bias_;
+  VarPtr index_;
+};
+}  // namespace opt
+}  // namespace mindspore
+#endif  // MINDSPORE_CCSRC_BACKEND_OPTIMIZER_GPU_REPLACE_BN_GRAD_CAST_FUSION_H_