Fix codex and codereview.

mindspore/ccsrc/pynative/pynative_execute.cc

@@ -110,7 +110,40 @@ py::object GetTupleObj(const py::object &obj) {
   return obj_tuple;
 }
 
-py::tuple ConvertInputs(const PrimitivePyPtr &prim, const py::list &args, py::tuple *out_args) {
+std::map<SignatureEnumDType, std::vector<size_t>> GetTypeIndex(const std::vector<SignatureEnumDType> &dtypes) {
+  std::map<SignatureEnumDType, std::vector<size_t>> type_indexes;
+  for (size_t i = 0; i < dtypes.size(); ++i) {
+    auto it = type_indexes.find(dtypes[i]);
+    if (it == type_indexes.end()) {
+      (void)type_indexes.insert(std::make_pair(dtypes[i], std::vector<size_t>{i}));
+    } else {
+      it->second.push_back(i);
+    }
+  }
+  return type_indexes;
+}
+
+std::map<SignatureEnumDType, size_t> GetDstType(const py::tuple &py_args,
+                                                const std::map<SignatureEnumDType, std::vector<size_t>> &type_indexes) {
+  std::map<SignatureEnumDType, size_t> dst_type;
+  for (auto it = type_indexes.begin(); it != type_indexes.end(); (void)++it) {
+    auto type = it->first;
+    auto indexes = it->second;
+    if (indexes.size() < 2) {
+      continue;
+    }
+    size_t m_index = indexes[0];
+    for (size_t i = 1; i < indexes.size(); ++i) {
+      if (py::isinstance<tensor::Tensor>(py_args[indexes[i]])) {
+        m_index = indexes[i];
+      }
+    }
+    (void)dst_type.insert(std::make_pair(type, m_index));
+  }
+  return dst_type;
+}
+
+py::tuple ConvertInputs(const PrimitivePyPtr &prim, const py::list &args, py::tuple *const out_args) {
   auto &py_args = *out_args;
   py::tuple input_mask(args.size());
   for (size_t i = 0; i < args.size(); ++i) {
@@ -129,30 +162,8 @@ py::tuple ConvertInputs(const PrimitivePyPtr &prim, const py::list &args, py::tu
   if (dtypes.size() == 0 || static_cast<int>(dtypes.size()) == empty_dtype_count) {
     return input_mask;
   }
-  std::map<SignatureEnumDType, std::vector<size_t>> type_indexs;
+  auto type_indexes = GetTypeIndex(dtypes);
-  for (size_t i = 0; i < dtypes.size(); ++i) {
+  auto dst_type = GetDstType(py_args, type_indexes);
-    auto it = type_indexs.find(dtypes[i]);
-    if (it == type_indexs.end()) {
-      (void)type_indexs.insert(std::make_pair(dtypes[i], std::vector<size_t>{i}));
-    } else {
-      it->second.push_back(i);
-    }
-  }
-  std::map<SignatureEnumDType, size_t> dst_type;
-  for (auto it = type_indexs.begin(); it != type_indexs.end(); (void)++it) {
-    auto type = it->first;
-    auto indexs = it->second;
-    if (indexs.size() < 2) {
-      continue;
-    }
-    size_t m_index = indexs[0];
-    for (size_t i = 1; i < indexs.size(); ++i) {
-      if (py::isinstance<tensor::Tensor>(py_args[indexs[i]])) {
-        m_index = indexs[i];
-      }
-    }
-    (void)dst_type.insert(std::make_pair(type, m_index));
-  }
   for (size_t i = 0; i < py_args.size(); ++i) {
     auto it = dst_type.find(dtypes[i]);
     if (it != dst_type.end() && it->second != i &&
@@ -542,28 +553,7 @@ AnfNodePtr PynativeExecutor::GetObjNode(const py::object &obj) {
   return curr_g_->NewCNode(tuple_get_item_inputs);
 }
 
-py::tuple RunOp(const py::args &args) {
+py::tuple RunOp(const OpExecInfoPtr &op_exec_info, const py::args &args) {
-  MS_LOG(DEBUG) << "RunOp start" << args.size();
-  py::object result;
-  // returns a null py::tuple on error
-  py::tuple err_ret(0);
-  PynativeStatusCode status = PYNATIVE_UNKNOWN_STATE;
-
-  OpExecInfoPtr op_exec_info = GenerateOpExecInfo(args);
-  MS_EXCEPTION_IF_NULL(op_exec_info);
-  if (op_exec_info->abstract != nullptr) {
-    py::dict output = abstract::ConvertAbstractToPython(op_exec_info->abstract);
-    if (!output["value"].is_none()) {
-      py::tuple value_ret(1);
-      value_ret[0] = output["value"];
-      return value_ret;
-    }
-    if (py::hasattr(op_exec_info->py_primitive->GetPyObj(), "const_value")) {
-      py::tuple value_ret(1);
-      value_ret[0] = "";
-      return value_ret;
-    }
-  }
   MS_LOG(INFO) << "RunOp start, op name is: " << op_exec_info->op_name;
   mindspore::parse::python_adapter::set_python_env_flag(true);
   MsBackendPolicy backend_policy;
@@ -584,7 +574,10 @@ py::tuple RunOp(const py::args &args) {
   if (vm_operators.find(op_exec_info->op_name) != vm_operators.end()) {
     backend_policy = kMsBackendVmOnly;
   }
-  result = RunOpWithBackendPolicy(backend_policy, op_exec_info, &status);
+  PynativeStatusCode status = PYNATIVE_UNKNOWN_STATE;
+  // returns a null py::tuple on error
+  py::tuple err_ret(0);
+  py::object result = RunOpWithBackendPolicy(backend_policy, op_exec_info, &status);
   if (status != PYNATIVE_SUCCESS) {
     MS_LOG(ERROR) << "Failed to run " << op_exec_info->op_name;
     return err_ret;
@@ -599,6 +592,26 @@ py::tuple RunOp(const py::args &args) {
   return result;
 }
 
+py::tuple RunOp(const py::args &args) {
+  MS_LOG(DEBUG) << "RunOp start" << args.size();
+  OpExecInfoPtr op_exec_info = GenerateOpExecInfo(args);
+  MS_EXCEPTION_IF_NULL(op_exec_info);
+  if (op_exec_info->abstract != nullptr) {
+    py::dict output = abstract::ConvertAbstractToPython(op_exec_info->abstract);
+    if (!output["value"].is_none()) {
+      py::tuple value_ret(1);
+      value_ret[0] = output["value"];
+      return value_ret;
+    }
+    if (py::hasattr(op_exec_info->py_primitive->GetPyObj(), "const_value")) {
+      py::tuple value_ret(1);
+      value_ret[0] = "";
+      return value_ret;
+    }
+  }
+  return RunOp(op_exec_info, args);
+}
+
 void ClearPyNativeSession() { session = nullptr; }
 
 PynativeExecutor::~PynativeExecutor() { ClearRes(); }
@@ -732,7 +745,11 @@ void PynativeExecutor::EndGraph(const py::object &cell, const py::object &out, c
       return;
     }
   }
+  EndGraphByOutId(out_id, cell, out, args);
+}
 
+void PynativeExecutor::EndGraphByOutId(const std::string &out_id, const py::object &cell, const py::object &out,
+                                       const py::args &args) {
   AnfNodePtr output_node;
   if (graph_info_map_[curr_g_].param_map.count(out_id)) {
     output_node = graph_info_map_[curr_g_].param_map[out_id];
@@ -776,27 +793,7 @@ void PynativeExecutor::EndGraph(const py::object &cell, const py::object &out, c
   }
 }
 
-void PynativeExecutor::GradNet(const GradOperationPtr &grad, const py::object &cell, const py::object &weights,
+std::vector<AnfNodePtr> PynativeExecutor::GetWeightsArgs(const py::object &weights) {
-                               const py::args &args) {
-  MS_LOG(INFO) << "GradNet start" << args.size();
-
-  std::size_t size = args.size();
-  auto cell_id = GetId(cell);
-  if (graph_map_.count(cell_id) != 0) {
-    MS_LOG(DEBUG) << "GradNet already compiled";
-    return;
-  }
-  MS_LOG(DEBUG) << "GradNet first compiled";
-  std::vector<AnfNodePtr> new_params;
-  for (size_t i = 0; i < size; i++) {
-    ParameterPtr p = std::make_shared<Parameter>(df_builder_);
-    new_params.push_back(p);
-  }
-  MS_LOG(DEBUG) << "GradNet start weight size" << df_builder_->parameters().size();
-  new_params.insert(new_params.end(), df_builder_->parameters().begin(), df_builder_->parameters().end());
-  df_builder_->set_parameters(new_params);
-  resource_->manager()->SetParameters(df_builder_, new_params);
-
   std::vector<AnfNodePtr> w_args;
   if (py::hasattr(weights, "__parameter_tuple__")) {
     auto tuple = weights.cast<py::tuple>();
@@ -821,12 +818,12 @@ void PynativeExecutor::GradNet(const GradOperationPtr &grad, const py::object &c
   } else {
     MS_LOG(EXCEPTION) << "training not paramter_tuple";
   }
-  MS_EXCEPTION_IF_NULL(resource_->func_graph());
+  return w_args;
-  auto g = GradGraph(resource_->func_graph(), grad, w_args, size);
+}
-  resource_->set_func_graph(g);
 
-  // get the parameters items and add the value to args_spec
+abstract::AbstractBasePtrList PynativeExecutor::GetArgsSpec(const py::args &args) {
   abstract::AbstractBasePtrList args_spec;
+  std::size_t size = args.size();
   for (std::size_t i = 0; i < size; i++) {
     ValuePtr converted = nullptr;
     bool succ = parse::ConvertData(args[i], &converted);
@@ -852,6 +849,38 @@ void PynativeExecutor::GradNet(const GradOperationPtr &grad, const py::object &c
       param_node->set_abstract(ptr);
     }
   }
+
+  return args_spec;
+}
+
+void PynativeExecutor::GradNet(const GradOperationPtr &grad, const py::object &cell, const py::object &weights,
+                               const py::args &args) {
+  MS_LOG(INFO) << "GradNet start" << args.size();
+
+  std::size_t size = args.size();
+  auto cell_id = GetId(cell);
+  if (graph_map_.count(cell_id) != 0) {
+    MS_LOG(DEBUG) << "GradNet already compiled";
+    return;
+  }
+  MS_LOG(DEBUG) << "GradNet first compiled";
+  std::vector<AnfNodePtr> new_params;
+  for (size_t i = 0; i < size; i++) {
+    ParameterPtr p = std::make_shared<Parameter>(df_builder_);
+    new_params.push_back(p);
+  }
+  MS_LOG(DEBUG) << "GradNet start weight size" << df_builder_->parameters().size();
+  new_params.insert(new_params.end(), df_builder_->parameters().begin(), df_builder_->parameters().end());
+  df_builder_->set_parameters(new_params);
+  resource_->manager()->SetParameters(df_builder_, new_params);
+
+  std::vector<AnfNodePtr> w_args = GetWeightsArgs(weights);
+  MS_EXCEPTION_IF_NULL(resource_->func_graph());
+  auto g = GradGraph(resource_->func_graph(), grad, w_args, size);
+  resource_->set_func_graph(g);
+
+  // get the parameters items and add the value to args_spec
+  abstract::AbstractBasePtrList args_spec = GetArgsSpec(args);
   MS_LOG(DEBUG) << "Args_spec size" << args_spec.size();
 
   resource_->set_args_spec(args_spec);

mindspore/ccsrc/pynative/pynative_execute.h

@@ -44,7 +44,7 @@ py::object RunOpInVM(const OpExecInfoPtr &op_exec_info, PynativeStatusCode *stat
 
 py::tuple RunOp(const py::args &args);
 
-py::tuple ConvertInputs(const PrimitivePyPtr &prim, const py::list &py_args, py::tuple *out_args);
+py::tuple ConvertInputs(const PrimitivePyPtr &prim, const py::list &py_args, py::tuple *const out_args);
 
 void ClearPyNativeSession();
 
@@ -67,6 +67,9 @@ class PynativeExecutor : public std::enable_shared_from_this<PynativeExecutor> {
   }
   void NewGraph(const py::object &cell, const py::args &args);
   void EndGraph(const py::object &cell, const py::object &out, const py::args &args);
+  void EndGraphByOutId(const std::string &out_id, const py::object &cell, const py::object &out, const py::args &args);
+  std::vector<AnfNodePtr> GetWeightsArgs(const py::object &weights);
+  abstract::AbstractBasePtrList GetArgsSpec(const py::args &args);
   void GradNet(const GradOperationPtr &grad, const py::object &cell, const py::object &weights, const py::args &args);
   void Clear(const std::string &flag = "");
   void Clean();