auto tune step two tune process

mindspore/_extends/parallel_compile/tbe_compiler/compiler.py

@@ -26,6 +26,7 @@ build_in_impl_path = get_built_in_impl_path()
 # op function list
 op_build = "compile"
 
+
 def _initialize(impl_path):
     """Initialize"""
     if impl_path == "":
@@ -37,6 +38,7 @@ def _initialize(impl_path):
 
     sys.path.insert(0, op_module_name)
 
+
 def _replace_range(args):
     for arg in args:
         if not arg.__contains__('range'):
@@ -47,6 +49,7 @@ def _replace_range(args):
                 if value < 0:
                     range_item[index] = None
 
+
 def build_op(build_type, json_str):
     """
     call op functions with function name and input args json_str
@@ -89,9 +92,9 @@ def build_op(build_type, json_str):
             op_module = __import__(op_name)
         else:
             if is_dynamic_shape:
-                op_module = __import__("impl.dynamic."+op_name, globals(), locals(), [op_name], 0)
+                op_module = __import__("impl.dynamic." + op_name, globals(), locals(), [op_name], 0)
             else:
-                op_module = __import__("impl."+op_name, globals(), locals(), [op_name], 0)
+                op_module = __import__("impl." + op_name, globals(), locals(), [op_name], 0)
         # get function
         if build_type == op_build:
             if custom_flag:
@@ -149,6 +152,7 @@ def compile_with_json(json_str):
         ret = build_op(op_build, json_str)
     return ret
 
+
 if __name__ == "__main__":
     in_args = sys.stdin.readline()
     result = compile_with_json(in_args)

mindspore/_extends/parallel_compile/tbe_compiler/tbe_common.py

@@ -15,6 +15,7 @@
 """tbe common"""
 import os
 
+
 class TBEException(Exception):
     """tbe exception class"""
 
@@ -64,6 +65,7 @@ def _check_arg_info(item):
     if 'param_type' not in item or not item['param_type']:
         raise ValueError("Json string Errors, key:param_type not found.")
 
+
 def get_input_output(io_info, args):
     """
     Parse args.
@@ -100,6 +102,7 @@ def get_input_output(io_info, args):
         if len(item) > 1:
             args.append(arg)
 
+
 def get_attr(attr_info, args):
     """
     Parse args.
@@ -118,6 +121,7 @@ def get_attr(attr_info, args):
             if item["name"] != "isRef":
                 args.append(item['value'])
 
+
 def get_args(op_info, arg_type):
     """
     Parse args.

mindspore/ccsrc/backend/kernel_compiler/kernel_fusion.cc

@@ -80,8 +80,8 @@ std::map<int64_t, KernelModPtr> KernelFusion(const std::vector<FusionScopeInfo>
     size_t hash_id = GenFusionJsonHash(fusion_op);
     auto json_name =
       fusion_kernel_name.append("_").append(std::to_string(hash_id)).append("_").append(std::to_string(device_id));
-    fusion_op["graph_id"] = fusion_scope_iter.graph_id;
     fusion_op["fusion_op_name"] = json_name;
+    fusion_op["full_name"] = fusion_scope_iter.full_name;
     // get io size
     std::vector<size_t> input_size_list;
     std::vector<size_t> output_size_list;

mindspore/ccsrc/backend/kernel_compiler/kernel_fusion.h

@@ -19,6 +19,7 @@
 #include <utility>
 #include <vector>
 #include <map>
+#include <string>
 #include "backend/kernel_compiler/kernel.h"
 namespace mindspore {
 namespace kernel {
@@ -26,15 +27,15 @@ namespace kernel {
  * @brief fuse op and return a callable mod
  */
 struct FusionScopeInfo {
-  FusionScopeInfo(int64_t id, uint32_t g_id, std::vector<AnfNodePtr> in, std::vector<AnfNodePtr> comp,
+  FusionScopeInfo(int64_t id, std::string f_name, std::vector<AnfNodePtr> in, std::vector<AnfNodePtr> comp,
                   std::vector<AnfNodePtr> out)
       : scope_id(id),
-        graph_id(g_id),
+        full_name(f_name),
         input_nodes(std::move(in)),
         compute_nodes(std::move(comp)),
         output_nodes(std::move(out)) {}
   int64_t scope_id{};
-  uint32_t graph_id{};
+  std::string full_name{};
   std::vector<AnfNodePtr> input_nodes;
   std::vector<AnfNodePtr> compute_nodes;
   std::vector<AnfNodePtr> output_nodes;

mindspore/ccsrc/backend/kernel_compiler/tbe/tbe_kernel_build.cc

@@ -123,7 +123,6 @@ bool TbeKernelJsonCreator::GenTbeSingleKernelJson(const std::shared_ptr<mindspor
   nlohmann::json op_info_json;
   op_info_json[kJIsDynamicShape] = tbe::TbeDynamicShapeUtil::GetDynamicShapeAttr(anf_node->cast<CNodePtr>());
   auto func_name = op_info_ptr->kernel_name();
-  op_info_json["graph_id"] = AnfAlgo::GetGraphId(anf_node.get());
   op_info_json[kJName] = func_name;
   op_info_json[kJModuleName] = std::string("impl.") + func_name;
   op_info_json[kJPyModulePath] = kPyPath;
@@ -163,7 +162,6 @@ bool TbeKernelJsonCreator::GenTbeSingleKernelJson(const std::shared_ptr<mindspor
   op_info_json["Type"] = op_name;
   op_info_json[kJKernelName] = json_name_;
   op_info_json[kGenModel] = kSingle;
-  op_info_json[kJFullName] = anf_node->fullname_with_scope();
 
   // create attr_desc
   nlohmann::json attr_desc;

mindspore/ccsrc/backend/optimizer/ascend/buffer_fusion/fusion_base_pass.h

@@ -43,7 +43,7 @@ const int8_t MULTI_ELTWISE_SIZE = 4;
 using FusedNodeRecord = std::vector<std::unordered_set<AnfNodePtr>>;
 
 struct BufferFusionInfo_t {
-  uint32_t graph_id;
+  std::string full_name;
   std::vector<AnfNodePtr> anf_nodes;
   std::vector<AnfNodePtr> inputs_list;
   std::vector<AnfNodePtr> outputs_list;

mindspore/ccsrc/backend/optimizer/ascend/buffer_fusion/ub_pattern_fusion.cc

@@ -387,7 +387,6 @@ void RemoveCircle(const session::KernelGraph &kernel_graph,
 void UbPatternFusion::GetBufferFusionInfo(session::KernelGraph *kernel_graph,
                                           std::unordered_map<int64_t, BufferFusionInfo_t> *buffer_fusion_infos) const {
   MS_EXCEPTION_IF_NULL(buffer_fusion_infos);
-  auto graph_id = kernel_graph->graph_id();
   GetFusionScopeComputeNodeList(kernel_graph, buffer_fusion_infos);
   GetFusionScopeInputNodeList(*kernel_graph, buffer_fusion_infos);
   GetFusionScopeOutputNodeList(kernel_graph, buffer_fusion_infos);
@@ -397,7 +396,11 @@ void UbPatternFusion::GetBufferFusionInfo(session::KernelGraph *kernel_graph,
   for (auto &buffer_fusion_info : *buffer_fusion_infos) {
     buffer_fusion_info.second.kernel_build_info =
       CreateFusionOpKernelInfo(buffer_fusion_info.second.inputs_list, buffer_fusion_info.second.outputs_list);
-    buffer_fusion_info.second.graph_id = graph_id;
+    // just for full_name_with_scope for every buffer_fusion_info.
+    auto fusion_node = CreateFusionOp(buffer_fusion_info.second.inputs_list, buffer_fusion_info.second.outputs_list,
+                                      buffer_fusion_info.second.anf_nodes, kernel_graph);
+    MS_EXCEPTION_IF_NULL(fusion_node);
+    buffer_fusion_info.second.full_name = fusion_node->fullname_with_scope();
   }
 }
 
@@ -412,7 +415,7 @@ bool UbPatternFusion::FuseBufferFusionPattern(session::KernelGraph *kernel_graph
     buffer_fusion_infos.begin(), buffer_fusion_infos.end(), std::back_inserter(fusion_scope_infos),
     [](const std::pair<int64_t, BufferFusionInfo_t> &buffer_fusion_info) -> mindspore::kernel::FusionScopeInfo {
       return mindspore::kernel::FusionScopeInfo(
-        buffer_fusion_info.first, buffer_fusion_info.second.graph_id, buffer_fusion_info.second.inputs_list,
+        buffer_fusion_info.first, buffer_fusion_info.second.full_name, buffer_fusion_info.second.inputs_list,
         buffer_fusion_info.second.anf_nodes, buffer_fusion_info.second.outputs_list);
     });
   auto kernel_mods = mindspore::kernel::KernelFusion(fusion_scope_infos);
@@ -447,6 +450,7 @@ bool UbPatternFusion::ReplaceFusionOp(std::unordered_map<int64_t, BufferFusionIn
   TraceGuard guard(std::make_shared<TraceOpt>(buffer_fusion_info.anf_nodes[0]->debug_info()));
   auto buffer_fusion = CreateFusionOp(buffer_fusion_info.inputs_list, buffer_fusion_info.outputs_list,
                                       buffer_fusion_info.anf_nodes, kernel_graph);
+  buffer_fusion->set_fullname_with_scope(buffer_fusion_info.full_name);
   AnfAlgo::SetSelectKernelBuildInfo(buffer_fusion_info.kernel_build_info, buffer_fusion.get());
   // Set abstract of fusion_op node
   std::vector<TypeId> types;