updata doc for Parameter & fix codex

mindspore/ccsrc/debug/data_dump_parser.cc

@@ -216,8 +216,10 @@ std::string DataDumpParser::GetOpOverflowBinPath(uint32_t graph_id, uint32_t dev
   std::string bin_path = "/var/log/npu/ide_daemon/dump";
 
   const char *dump_data_path = std::getenv("DATA_DUMP_PATH");
-  bin_path.append(dump_data_path);
+  if (dump_data_path != nullptr) {
-  bin_path.append("_");
+    bin_path.append(dump_data_path);
+    bin_path.append("_");
+  }
   bin_path.append(std::to_string(device_id));
   bin_path.append("/");
   bin_path.append(net_name_);

mindspore/ccsrc/frontend/optimizer/irpass/switch_layer_defer_inline.h

@@ -36,6 +36,9 @@ class SwitchLayerDeferInline : public AnfVisitor {
     auto tuple = dyn_cast<abstract::AbstractTuple>(cnode->inputs()[2]->abstract());
     for (auto elem : tuple->elements()) {
       auto abstract = dyn_cast<abstract::FuncGraphAbstractClosure>(elem);
+      if (abstract == nullptr) {
+        return nullptr;
+      }
       *(abstract->func_graph()->switch_layer_input()) = true;
     }
     return nullptr;

mindspore/ccsrc/pipeline/jit/remove_value_node_dup.cc

@@ -173,6 +173,5 @@ bool MergeDuplicateGraphs(const FuncGraphManagerPtr manager) {
   }
   return true;
 }
-
 }  // namespace pipeline
 }  // namespace mindspore

mindspore/ccsrc/pipeline/jit/remove_value_node_dup.h

@@ -31,7 +31,6 @@ void TryToDoReplace(FuncGraphManager *manager, const AnfNodePtr &node, HashCache
 size_t HashOfGraph(const FuncGraphPtr &fg);
 bool IsCNodeGraph(const AnfNodePtr &node);
 bool MergeDuplicateGraphs(const FuncGraphManagerPtr manager);
-
 }  // namespace pipeline
 }  // namespace mindspore
 

mindspore/ccsrc/utils/convert_utils.cc

@@ -473,12 +473,12 @@ bool IsGraphOutputValueNodeOrParameter(const AnfNodePtr &output, const py::tuple
   }
   return false;
 }
-
+namespace {
 // Isomorphism
-static bool SameNode(const AnfNodePtr &node1, const AnfNodePtr &node2, FuncGraphPairMapEquiv *equiv_func_graph,
+bool SameNode(const AnfNodePtr &node1, const AnfNodePtr &node2, FuncGraphPairMapEquiv *equiv_func_graph,
-                     NodeMapEquiv *const equiv_node);
+              NodeMapEquiv *const equiv_node);
-static bool SameNodeShallow(const AnfNodePtr &node1, const AnfNodePtr &node2, FuncGraphPairMapEquiv *equiv_func_graph,
+bool SameNodeShallow(const AnfNodePtr &node1, const AnfNodePtr &node2, FuncGraphPairMapEquiv *equiv_func_graph,
-                            NodeMapEquiv *const equiv_node) {
+                     NodeMapEquiv *const equiv_node) {
   if (equiv_node == nullptr) {
     MS_LOG(ERROR) << "Invalid equiv_node";
     return false;
@@ -534,8 +534,8 @@ bool SameNode(const AnfNodePtr &node1, const AnfNodePtr &node2, FuncGraphPairMap
   return SameNodeShallow(node1, node2, equiv_func_graph, equiv_node);
 }
 
-static bool SameSubgraph(AnfNodePtr root1, AnfNodePtr root2, FuncGraphPairMapEquiv *equiv_func_graph,
+bool SameSubgraph(AnfNodePtr root1, AnfNodePtr root2, FuncGraphPairMapEquiv *equiv_func_graph,
-                         NodeMapEquiv *const equiv_node) {
+                  NodeMapEquiv *const equiv_node) {
   std::unordered_set<AnfNodePtr> done;
   std::stack<std::pair<AnfNodePtr, AnfNodePtr>> todo;
 
@@ -576,6 +576,7 @@ static bool SameSubgraph(AnfNodePtr root1, AnfNodePtr root2, FuncGraphPairMapEqu
   }
   return true;
 }
+}  // namespace
 
 bool Isomorphic(FuncGraphPtr fg1, FuncGraphPtr fg2, FuncGraphPairMapEquiv *equiv_func_graph,
                 NodeMapEquiv *const equiv_node) {

mindspore/common/parameter.py

@@ -40,19 +40,18 @@ class Parameter(MetaTensor):
     After initialized `Parameter` is a subtype of `Tensor`.
 
     In auto_parallel mode of  "semi_auto_parallel" and "auto_parallel", if init `Parameter` by
-    a `Initializer`, the type of Parameter will be a `MetaTensor` not a `Tensor`. `MetaTensor`
+    an `Initializer`, the type of Parameter will be `MetaTensor` not `Tensor`. `MetaTensor`
-    only save the shape type info of a tensor with no memory usage. The shape can be change while
+    only saves the shape and type info of a tensor with no memory usage. The shape can be changed while
     compile for auto-parallel. Call `init_data` will return a Tensor Parameter with initialized data.
 
     Note:
         Each parameter of Cell is represented by Parameter class.
 
     Args:
-        default_input (Union[Tensor, Initializer]): Parameter data, when `default_input` is` Initializer`,
+        default_input (Union[Tensor, Initializer, Number]): Parameter data, to be set initialized.
-            the data stored by Parameter is `MetaTensor`, otherwise it is `Tensor`.
         name (str): Name of the child parameter.
         requires_grad (bool): True if the parameter requires gradient. Default: True.
-        layerwise_parallel (bool): A kind of model parallel mode. When layerwise_parallel is true in paralle mode,
+        layerwise_parallel (bool): A kind of model parallel mode. When layerwise_parallel is true in parallel mode,
             broadcast and gradients communication would not be applied to parameters. Default: False.
 
     Example:

mindspore/core/ir/pattern_matcher.h

@@ -580,7 +580,6 @@ class PConstant : public PBase<PConstant<T> > {
       return nullptr;
     }
     auto value = node->cast<ValueNodePtr>()->value();
-
     if (!value->isa<tensor::Tensor>()) {
       return nullptr;
     }
@@ -747,7 +746,6 @@ class PConstant : public PBase<PConstant<T> > {
 
     std::vector<int> tensor_out_shape = tensor_3_abstract->shape()->shape();
     int data_out_size = std::accumulate(tensor_out_shape.begin(), tensor_out_shape.end(), 1, std::multiplies<int>());
-
     if ((tensor_ptr_1->DataSize() > 1) && (tensor_ptr_1->DataSize() != data_out_size)) {
       return nullptr;
     }