remove batch norm from StaticBuildBlackList (PaddlePaddle#57510)

* remove batch norm from StaticBuildBlackList

* turn off the flag

* fix batch_norm register kernel info

* remove dequantize_linear to phi

* fix build error

* add sig file

* update test and cmakelist

* fix test_split_program error in static_build mode

* move fuse_bn_add_act to phi

* fix error in test_cudnn_bn_add_relu

* fix shape error

* fix date

* close the static_build flag

paddle/fluid/framework/new_executor/interpreter/static_build.cc

@@ -54,7 +54,6 @@ std::set<std::string> OpsCanSkipedFakeAllocInStaticBuild = {
     "nop"};
 
 std::set<std::string> StaticBuildBlackList = {
-    "batch_norm" /*: to handle reserve_space output*/,
     "cinn_instruction_run" /*: to handle subgraph infermeta*/,
     "cinn_launch" /*: to handle subgraph infermeta*/,
     "run_program" /*: to handle scope output*/,
@@ -206,6 +205,14 @@ bool TensorShouldBeFakeInitialized(const OperatorBase& op,
     }
   }
 
+  if (op_type == "batch_norm" && parameter_name == "ReserveSpace") {
+    if (dynamic_cast<const OperatorWithKernel*>(&op)->kernel_type()->place_ ==
+        phi::CPUPlace()) {
+      VLOG(2) << "Skip fake initialization for: " << parameter_name;
+      return false;
+    }
+  }
+
   if (op_type == "coalesce_tensor" && parameter_name == "Output") {
     VLOG(2) << "Skip fake initialization for: " << parameter_name;
     return false;
@@ -250,6 +257,12 @@ bool TensorShouldBeFakeInitialized(const OperatorBase& op,
     }
   }
 
+  if ((op_type == "flatten" || op_type == "flatten_contiguous_range") &&
+      parameter_name == "XShape") {
+    VLOG(2) << "Skip fake initialization for: " << parameter_name;
+    return false;
+  }
+
   if (op_type == "segment_pool" && parameter_name == "SummedIds") {
     return op.Attr<std::string>("pooltype") == "MEAN" &&
            dynamic_cast<const OperatorWithKernel*>(&op)
@@ -856,6 +869,8 @@ void FakeInitializeOutputsForFunctionKernel(
             dtype = InferDTypeFromAttr(op, runtime_ctx, "dtype");
           } else if (op_type == "bincount" || op_type == "reduce_sum_grad") {
             dtype = GetInputDType(runtime_ctx, "X");
+          } else if (op_type == "dequantize_linear") {
+            dtype = GetInputDType(runtime_ctx, "Scale");
           } else if (op_type == "lamb") {
             bool multi_precision = op.Attr<bool>("multi_precision");
             dtype = GetInputDType(runtime_ctx, "Moment1");