!3712 add anf pass

Merge pull request !3712 from zhengjun10/master

mindspore/lite/src/gllo/common/utils.cc

@@ -16,9 +16,10 @@
 #include <vector>
 #include <memory>
 #include "src/gllo/common/utils.h"
-#include "mindspore/lite/src/ir/primitive_t_value.h"
+#include "src/ir/primitive_t_value.h"
 #include "frontend/operator/ops.h"
 
+using PrimitiveTValuePtr = std::shared_ptr<mindspore::lite::PrimitiveTValue>;
 namespace mindspore {
 namespace opt {
 
@@ -74,7 +75,11 @@ bool AnfEqual(const BaseRef &a, const BaseRef &b) {
       }
     }
   }
-
+  if (a.m_ptr->isa<lite::PrimitiveTValue>()) {
+    auto a_value_node_ptr = a.m_ptr->cast<PrimitiveTValuePtr>();
+    auto b_value_node_ptr = b.m_ptr->cast<PrimitiveTValuePtr>();
+    return a_value_node_ptr->GetPrimitiveT()->value.type == b_value_node_ptr->GetPrimitiveT()->value.type;
+  }
   return a == b;
 }
 
@@ -203,5 +208,16 @@ void CheckInputSize(const CNodePtr &node, const int size) {
   }
 }
 
+schema::PrimitiveType GetCNodeType(const CNodePtr &node) {
+    auto value_primitive = node->input(0);
+    auto value_node = value_primitive->cast<ValueNodePtr>();
+    MS_ASSERT(value_node != nullptr);
+    auto value = value_node->value();
+    MS_ASSERT(value != nullptr);
+    auto primitive = value->cast<PrimitiveTValuePtr>();
+    MS_ASSERT(primitive != nullptr);
+    return primitive->GetPrimitiveT()->value.type;
+}
+
 }  // namespace opt
 }  // namespace mindspore

mindspore/lite/src/gllo/common/utils.h

@@ -21,6 +21,7 @@
 #include "ir/func_graph.h"
 #include "src/common/utils.h"
 #include "src/gllo/common/pattern_engine.h"
+#include "schema/inner/model_generated.h"
 
 namespace mindspore {
 namespace opt {
@@ -42,6 +43,8 @@ void CheckIfVarIsNull(const VarPtr &var);
 
 void CheckInputSize(const CNodePtr &node, const int size);
 
+schema::PrimitiveType GetCNodeType(const CNodePtr &node);
+
 }  // namespace opt
 }  // namespace mindspore
 #endif  // MINDSPORE_LITE_SRC_PASS_COMMON_UTILS_H_

mindspore/lite/src/gllo/fusion/conv_activation_fusion.cc

@@ -0,0 +1,64 @@
+/**
+ * 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
+ *conv_activation_fusion.h
+ * 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/gllo/fusion/conv_activation_fusion.h"
+#include <memory>
+#include "schema/inner/model_generated.h"
+#include "src/ir/primitive_t_value.h"
+#include "mindspore/ccsrc/utils/utils.h"
+#include "src/gllo/common/utils.h"
+
+namespace mindspore {
+namespace opt {
+const BaseRef ConvActivationFusion::DefinePattern() const {
+  VarPtr X = std::make_shared<Var>();
+  // conv2d inputs may be 2 or 3 inputs,match move to process
+  auto prim = new schema::PrimitiveT();
+  prim->value.type = primitive_type;
+  auto prim_value = std::make_shared<lite::PrimitiveTValue>(prim);
+
+  return VectorRef({prim_value, X});
+}
+
+const AnfNodePtr ConvActivationFusion::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
+                                               const EquivPtr &) const {
+  MS_LOG(DEBUG) << "conv activation pass process:" << schema::EnumNamesPrimitiveType()[primitive_type];
+  CheckIfFuncGraphIsNull(func_graph);
+
+  CheckIfAnfNodeIsNull(node);
+  auto act_node = node->cast<CNodePtr>();
+  CheckIfCNodeIsNull(act_node);
+  CheckInputSize(act_node, 2);
+
+  auto act_primitive = GetValueNode<std::shared_ptr<lite::PrimitiveTValue>>(act_node->input(0));
+  if (act_primitive->GetPrimitiveT()->value.AsActivation()->type != activation_type) {
+    return node;
+  }
+  AnfNodePtr pre_node = act_node->input(1);
+  CheckIfAnfNodeIsNull(pre_node);
+  if (pre_node != nullptr && pre_node->isa<CNode>()) {
+    auto conv_node = pre_node->cast<CNodePtr>();
+    auto node_type = GetCNodeType(conv_node);
+    if (node_type == schema::PrimitiveType_Conv2D || node_type == schema::PrimitiveType_DepthwiseConv2D) {
+      auto primitiveT_value = GetValueNode<std::shared_ptr<lite::PrimitiveTValue>>(conv_node->input(0));
+      primitiveT_value->GetPrimitiveT()->value.AsConv2D()->activationType = activation_type;
+      return pre_node;
+    }
+  }
+  return node;
+}
+}  // namespace opt
+}  // namespace mindspore

mindspore/lite/src/gllo/fusion/conv_activation_fusion.h

@@ -0,0 +1,38 @@
+/**
+ * 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
+ *conv_activation_fusion.h
+ * 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_LITE_SRC_PASS_FUSION_CONV_ACTIVATION_FUSION_H_
+#define MINDSPORE_LITE_SRC_PASS_FUSION_CONV_ACTIVATION_FUSION_H_
+
+#include "src/gllo/common/optimizer.h"
+
+namespace mindspore {
+namespace opt {
+class ConvActivationFusion : public PatternProcessPass {
+ public:
+  explicit ConvActivationFusion(bool multigraph = true,
+                                schema::PrimitiveType primitive = schema::PrimitiveType_LeakyReLU,
+                                schema::ActivationType activation = schema::ActivationType_LEAKY_RELU) : primitive_type(
+      primitive), activation_type(activation), PatternProcessPass("conv_activation_fusion", multigraph) {}
+  ~ConvActivationFusion() override = default;
+  const BaseRef DefinePattern() const override;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+  schema::PrimitiveType primitive_type;
+  schema::ActivationType activation_type;
+};
+}  // namespace opt
+}  // namespace mindspore
+#endif  // MINDSPORE_LITE_SRC_PASS_FUSION_CONV_ACTIVATION_FUSION_H_

mindspore/lite/src/gllo/fusion/conv_biasadd_fusion.cc

@@ -15,8 +15,8 @@
  */
 #include "src/gllo/fusion/conv_biasadd_fusion.h"
 #include <memory>
-#include "mindspore/lite/schema/inner/model_generated.h"
+#include "schema/inner/model_generated.h"
-#include "mindspore/lite/src/ir/primitive_t_value.h"
+#include "src/ir/primitive_t_value.h"
 #include "mindspore/ccsrc/utils/utils.h"
 #include "src/gllo/common/utils.h"
 

mindspore/lite/src/gllo/fusion/conv_scale_fusion.cc

@@ -0,0 +1,126 @@
+/**
+ * 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
+ *conv_activation_fusion.h
+ * 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/gllo/fusion/conv_scale_fusion.h"
+#include <memory>
+#include "schema/inner/model_generated.h"
+#include "src/ir/primitive_t_value.h"
+#include "src/param_value_lite.h"
+#include "mindspore/ccsrc/utils/utils.h"
+#include "src/gllo/common/utils.h"
+#include "include/errorcode.h"
+
+namespace mindspore {
+namespace opt {
+const BaseRef ConvScaleFusion::DefinePattern() const {
+  VarPtr X = std::make_shared<Var>();
+  // conv2d inputs may be 2 or 3 inputs,match move to process
+  auto prim = new schema::PrimitiveT();
+  prim->value.type = schema::PrimitiveType_Scale;
+  auto prim_value = std::make_shared<lite::PrimitiveTValue>(prim);
+
+  return VectorRef({prim_value, X});
+}
+
+const AnfNodePtr ConvScaleFusion::Process(const FuncGraphPtr &func_graph, const AnfNodePtr &node,
+                                          const EquivPtr &) const {
+  MS_LOG(DEBUG) << "conv activation pass process";
+  CheckIfFuncGraphIsNull(func_graph);
+
+  CheckIfAnfNodeIsNull(node);
+  auto scale_node = node->cast<CNodePtr>();
+  CheckIfCNodeIsNull(scale_node);
+  CheckInputSize(scale_node, 2);
+
+  AnfNodePtr pre_node = scale_node->input(1);
+  CheckIfAnfNodeIsNull(pre_node);
+  if (pre_node != nullptr && pre_node->isa<CNode>()) {
+    auto conv_node = pre_node->cast<CNodePtr>();
+    auto node_type = GetCNodeType(conv_node);
+    if (node_type == schema::PrimitiveType_Conv2D || node_type == schema::PrimitiveType_DepthwiseConv2D) {
+      return DoFusion(conv_node, scale_node);
+    }
+  }
+  return node;
+}
+const AnfNodePtr ConvScaleFusion::DoFusion(const CNodePtr &conv_node, const CNodePtr &scale_node) const {
+  if (scale_node->inputs().size() == 3) {
+    GetTransParam(scale_node->input(2), nullptr);
+  } else if (scale_node->inputs().size() == 4) {
+    // todo add bias fusion zhengjun10
+    GetTransParam(scale_node->input(2), scale_node->input(3));
+  } else {
+    MS_LOG(ERROR) << "scale inputs size is error:" << scale_node->DebugString();
+    return nullptr;
+  }
+
+  AnfNodePtr conv_weight_node;
+  if (conv_node->inputs().size() == 3) {
+     conv_weight_node = conv_node->input(2);
+  } else {
+    MS_LOG(ERROR) << "scale inputs size is error:" << scale_node->DebugString();
+    return nullptr;
+  }
+  auto conv_weight_param = conv_weight_node->cast<ParameterPtr>()->default_param();
+  auto weight_value = std::dynamic_pointer_cast<ParamValueLite>(conv_weight_param);
+  auto old_conv_weight = reinterpret_cast<const float *>(weight_value->tensor_addr());
+
+  auto new_conv_weight = new(std::nothrow) float[weight_value->tensor_shape_size()];
+  CalNewWeightTensor(old_conv_weight, new_conv_weight, weight_value->tensor_shape_size());
+  weight_value->set_tensor_addr(new_conv_weight);
+  return conv_node;
+}
+
+const lite::STATUS ConvScaleFusion::GetTransParam(const AnfNodePtr &scale_weight_node,
+                                                  const AnfNodePtr &scale_bias_node) const {
+  if (!scale_weight_node->isa<Parameter>()) {
+    MS_LOG(EXCEPTION) << "scale weight node not paramter node";
+  }
+  if (scale_bias_node != nullptr && !scale_bias_node->isa<Parameter>()) {
+    MS_LOG(EXCEPTION) << "scale bias node not paramter node";
+  }
+  auto scale_weight_param = scale_weight_node->cast<ParameterPtr>()->default_param();
+  auto weight_value = std::dynamic_pointer_cast<ParamValueLite>(scale_weight_param);
+  auto weight_data = reinterpret_cast<const float *>(weight_value->tensor_addr());
+
+  if (0 != memcpy_s(trans_scale, kernel_nums * sizeof(float), weight_data, kernel_nums * sizeof(float))) {
+    MS_LOG(ERROR) << "memcpy_s transScale failed";
+    return lite::RET_ERROR;
+  }
+  return lite::RET_OK;
+}
+
+const lite::STATUS ConvScaleFusion::CalNewWeightTensor(const float *oldWeightTensor, float *newWeightTensor,
+                                                       const size_t tensor_shape_size) const {
+  MS_ASSERT(oldWeightTensor != nullptr);
+  if (0 != memset_s(newWeightTensor, tensor_shape_size * sizeof(float), 0, tensor_shape_size * sizeof(float))) {
+    MS_LOG(ERROR) << "memset newWeightData failed";
+    return lite::RET_ERROR;
+  }
+  if (kernel_nums == 0) {
+    MS_LOG(ERROR) << "kernel nums is 0";
+    return lite::RET_ERROR;
+  }
+  auto kernel_size = tensor_shape_size / kernel_nums;
+  for (size_t i = 0; i < kernel_nums; i++) {
+    for (size_t j = 0; j < kernel_size; j++) {
+      newWeightTensor[i * kernel_size + j] = oldWeightTensor[i * kernel_size + j] * trans_scale[i];
+    }
+  }
+  return lite::RET_OK;
+}
+}  // namespace opt
+}  // namespace mindspore

mindspore/lite/src/gllo/fusion/conv_scale_fusion.h

@@ -0,0 +1,40 @@
+/**
+ * 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
+ *conv_activation_fusion.h
+ * 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_LITE_SRC_PASS_FUSION_CONV_SCALE_FUSION_H_
+#define MINDSPORE_LITE_SRC_PASS_FUSION_CONV_SCALE_FUSION_H_
+
+#include "src/gllo/common/optimizer.h"
+
+namespace mindspore {
+namespace opt {
+class ConvScaleFusion : public PatternProcessPass {
+ public:
+  explicit ConvScaleFusion(bool multigraph = true) : PatternProcessPass("conv_scale_fusion", multigraph) {}
+  ~ConvScaleFusion() override = default;
+  const BaseRef DefinePattern() const override;
+  const AnfNodePtr Process(const FuncGraphPtr &, const AnfNodePtr &, const EquivPtr &) const override;
+  const AnfNodePtr DoFusion(const CNodePtr &, const CNodePtr &) const;
+  const lite::STATUS GetTransParam(const AnfNodePtr &, const AnfNodePtr &) const;
+  const lite::STATUS CalNewWeightTensor(const float *, float *, const size_t) const;
+ private:
+  float *trans_scale = nullptr;
+  int kernel_nums = 0;
+};
+}  // namespace opt
+}  // namespace mindspore
+#endif  // MINDSPORE_LITE_SRC_PASS_FUSION_CONV_SCALE_FUSION_H_
+

mindspore/lite/test/CMakeLists.txt

@@ -193,6 +193,8 @@ if(BUILD_CONVERTER)
             ${LITE_DIR}/src/gllo/common/visit.cc
             ${LITE_DIR}/src/gllo/common/utils.cc
             ${LITE_DIR}/src/gllo/fusion/conv_biasadd_fusion.cc
+            ${LITE_DIR}/src/gllo/fusion/conv_activation_fusion.cc
+            ${LITE_DIR}/src/gllo/fusion/conv_scale_fusion.cc
             )
 endif()
 ### train

mindspore/lite/tools/converter/CMakeLists.txt

@@ -78,6 +78,8 @@ file(GLOB_RECURSE CONVERTER_SRC RELATIVE ${CMAKE_CURRENT_SOURCE_DIR}
         ${CMAKE_CURRENT_SOURCE_DIR}/../../src/gllo/common/visit.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/../../src/gllo/common/utils.cc
         ${CMAKE_CURRENT_SOURCE_DIR}/../../src/gllo/fusion/conv_biasadd_fusion.cc
+        ${CMAKE_CURRENT_SOURCE_DIR}/../../src/gllo/fusion/conv_activation_fusion.cc
+        ${CMAKE_CURRENT_SOURCE_DIR}/../../src/gllo/fusion/conv_scale_fusion.cc
         )
 
 add_subdirectory(parser/caffe)