Support static graph code-gen for scalar and int_array (#48792)

* add suppport_tensor for code_gen to static graph

* support code-gen for int_array

* polish code

* fix bug of data_type

Author: zyfncg

paddle/fluid/operators/crop_tensor_op.cc

@@ -108,18 +108,23 @@ execute_process(
     --op_compat_yaml_path ${CMAKE_SOURCE_DIR}/paddle/phi/api/yaml/op_compat.yaml
     --output_op_path "${generated_op_path}.tmp" --output_arg_map_path
     "${generated_argument_mapping_path}.tmp"
+  RESULT_VARIABLE _result)
+if(${_result})
+  message(FATAL_ERROR "operator codegen failed, exiting.")
+endif()
+
+execute_process(
+  WORKING_DIRECTORY ${CMAKE_SOURCE_DIR}/paddle/fluid/operators/generator
   COMMAND
     ${PYTHON_EXECUTABLE} generate_sparse_op.py --ops_yaml_path
     ./parsed_ops/sparse_ops.parsed.yaml --backward_ops_yaml_path
     ./parsed_ops/sparse_backward.parsed.yaml --output_op_path
     "${generated_sparse_ops_path}.tmp" --output_arg_map_path
     "${generated_sparse_argument_mapping_path}.tmp"
-  RESULT_VARIABLE _results)
-foreach(_result in ${_results})
-  if(${_result})
-    message(FATAL_ERROR "operator codegen failed, exiting.")
-  endif()
-endforeach()
+  RESULT_VARIABLE _result)
+if(${_result})
+  message(FATAL_ERROR "sparse operator codegen failed, exiting.")
+endif()
 
 if(EXISTS "${generated_op_path}.tmp" AND EXISTS "${generated_op_path}")
   execute_process(COMMAND ${CMAKE_COMMAND} -E copy_if_different

paddle/fluid/operators/generator/CMakeLists.txt

@@ -114,17 +114,44 @@ def to_input_name(s):
     return match.group(2)
 
 
+def to_scalar_tensor_name(attr):
+    if 'tensor_name' in attr:
+        return attr['tensor_name']
+    return to_pascal_case(attr['name']) + 'Tensor'
+
+
+def to_int_array_tensor_name(attr):
+    if 'tensor_name' in attr:
+        return attr['tensor_name']
+    return to_pascal_case(attr['name']) + 'Tensor'
+
+
+def to_int_array_tensors_name(attr):
+    if 'tensors_name' in attr:
+        return attr['tensors_name']
+    return to_pascal_case(attr['name']) + 'TensorList'
+
+
 def cartesian_prod_attrs(attrs):
     items = []
     for attr in attrs:
         type_name = attr["typename"]
         name = attr["name"]
         if type_name == "Scalar":
-            items.append((name, "{}Tensor".format(name)))
+            items.append((name, to_scalar_tensor_name(attr)))
         elif type_name == "IntArray":
-            items.append(
-                (name, "{}Tensor".format(name), "{}TensorList".format(name))
-            )
+            if 'tensor_name' not in attr and 'manual_flag' in attr:
+                items.append((name, to_int_array_tensors_name(attr)))
+            elif 'tensors_name' not in attr and 'manual_flag' in attr:
+                items.append((name, to_int_array_tensor_name(attr)))
+            else:
+                items.append(
+                    (
+                        name,
+                        to_int_array_tensor_name(attr),
+                        to_int_array_tensors_name(attr),
+                    )
+                )
         else:
             items.append((name,))