Merge pull request PaddlePaddle#37 from Charles-hit/static_composite_gen

[static code gen] support composite grad maker code gen

paddle/fluid/operators/generator/CMakeLists.txt

@@ -148,15 +148,16 @@ if(${_result})
   message(FATAL_ERROR "sparse operator codegen failed, exiting.")
 endif()
 
-# set(generated_static_files
-#     "${generated_op_path}"
-#     "${generated_static_op_path}"
-#     "${generated_sparse_ops_path}"
-#     "${generated_argument_mapping_path}"
-#     "${generated_static_argument_mapping_path}"
-#     "${generated_sparse_argument_mapping_path}")
+set(generated_static_files
+    "${generated_op_path}"
+    "${generated_static_op_path}"
+    "${generated_sparse_ops_path}"
+    "${generated_argument_mapping_path}"
+    "${generated_static_argument_mapping_path}"
+    "${generated_sparse_argument_mapping_path}")
 
 set(generated_static_files
+    "${generated_op_path}"
     "${generated_static_op_path}"
     "${generated_sparse_ops_path}"
     "${generated_argument_mapping_path}"

paddle/fluid/operators/generator/filters.py

@@ -132,6 +132,17 @@ def to_int_array_tensors_name(attr):
     return to_pascal_case(attr['name']) + 'TensorList'
 
 
+def to_composite_grad_opmaker_name(backward_op_name):
+    words = backward_op_name.split("_")
+    for i in range(len(words)):
+        words[i] = words[i].strip()
+        words[i] = words[i].capitalize()
+    composite_grad_opmaker_name = words[0] + "Composite"
+    composite_grad_opmaker_name += "".join(word for word in words[1:])
+    composite_grad_opmaker_name += "OpMaker"
+    return composite_grad_opmaker_name
+
+
 def cartesian_prod_attrs(attrs):
     items = []
     for attr in attrs:

paddle/fluid/operators/generator/generate_op.py

@@ -19,6 +19,7 @@
 import yaml
 from filters import (
     cartesian_prod_mapping,
+    to_composite_grad_opmaker_name,
     to_input_name,
     to_int_array_tensor_name,
     to_int_array_tensors_name,
@@ -32,6 +33,7 @@
 from parse_utils import to_named_dict
 from tests import (
     is_base_op,
+    is_composite_op,
     is_initializer_list,
     is_scalar,
     is_vec,
@@ -57,7 +59,9 @@
 env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
+env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
 env.tests["base_op"] = is_base_op
+env.tests["composite_op"] = is_composite_op
 env.tests["vec"] = is_vec
 env.tests["scalar"] = is_scalar
 env.tests["initializer_list"] = is_initializer_list
@@ -153,6 +157,27 @@ def process_int_array(op_item, int_array_configs):
                         ]
 
 
+def parse_composite_info(ops, backward_ops, backward_op_dict):
+    for op in ops:
+        if "backward" in op:
+            op["phi_backward"] = op["backward"]
+    for backward_op in backward_ops:
+        if "backward" in backward_op:
+            backward_op["phi_backward"] = backward_op["backward"]
+    for backward_op_name, op_dict in backward_op_dict.items():
+        if "composite" not in op_dict:
+            continue
+        op_dict["composite"]["phi_inputs"] = []
+        op_dict["composite"]["phi_attrs"] = []
+        op_dict["composite"]["phi_outputs"] = []
+        for input in op_dict["inputs"]:
+            op_dict["composite"]["phi_inputs"].append(input['name'])
+        for attr in op_dict["attrs"]:
+            op_dict["composite"]["phi_attrs"].append(attr['name'])
+        for output in op_dict["outputs"]:
+            op_dict["composite"]["phi_outputs"].append(output['name'])
+
+
 # replace name of op and params for OpMaker
 def replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict):
     def get_phi_and_fluid_op_name(op_item):
@@ -178,6 +203,37 @@ def update_grad_args_name(op_args, args_alias_map):
                 )
                 item['name'] = args_alias_map[item['name'][:-5]] + '_grad'
 
+    def add_fluid_info_in_composite(composite_map, args_alias_map):
+        fluid_input_list = []
+        fluid_attr_list = []
+        fluid_output_list = []
+        # add fluid op inputs
+        for input in composite_map["phi_inputs"]:
+            if input in args_alias_map:
+                fluid_input_list.append(args_alias_map[input])
+            else:
+                fluid_input_list.append(input)
+        # add fluid op attrs
+        for attr in composite_map["phi_attrs"]:
+            if attr in args_alias_map:
+                fluid_attr_list.append(args_alias_map[attr])
+            else:
+                fluid_attr_list.append(attr)
+        # add fluid op outputs
+        for output in composite_map["phi_outputs"]:
+            if output in args_alias_map:
+                fluid_output_list.append(args_alias_map[output])
+            else:
+                fluid_output_list.append(output)
+
+        composite_map.update(
+            {
+                "fluid_inputs": fluid_input_list,
+                "fluid_attrs": fluid_attr_list,
+                "fluid_outputs": fluid_output_list,
+            }
+        )
+
     def get_param_list_alias(param_list, args_map):
         return [
             args_map[param] if param in args_map else param
@@ -307,6 +363,15 @@ def update_grad_op_compat_name(grad_op_item, args_name_map):
                 continue
 
             backward_op_list = op_args['backward'].split(',')
+            # add fluid args name in composite map
+            for backward_op in backward_op_list:
+                if (
+                    "composite"
+                    in backward_op_dict[backward_op.split('(')[0].strip()]
+                ):
+                    add_fluid_info_in_composite(
+                        backward_op_dict[backward_op]["composite"], args_map
+                    )
             _, bw_op_name = get_phi_and_fluid_op_name(backward_op_list[0])
             forward_op_item['backward'] = bw_op_name
             backward_op_item['op_name'] = bw_op_name
@@ -406,12 +471,10 @@ def main(
         ops = yaml.safe_load(f)
         ops = [restruct_io(op) for op in ops]
     forward_op_dict = to_named_dict(ops)
-
     with open(backward_yaml_path, "rt") as f:
         backward_ops = yaml.safe_load(f)
         backward_ops = [restruct_io(op) for op in backward_ops]
     backward_op_dict = to_named_dict(backward_ops)
-
     with open(op_version_yaml_path, "rt") as f:
         op_versions = yaml.safe_load(f)
     # add op version info into op
@@ -426,6 +489,8 @@ def main(
     for bw_op in backward_ops:
         bw_op['op_name'] = bw_op['name']
 
+    parse_composite_info(ops, backward_ops, backward_op_dict)
+
     replace_compat_name(op_fluid_map_list, forward_op_dict, backward_op_dict)
 
     # prepare for invoke case
@@ -442,21 +507,21 @@ def main(
     op_dict = {}
     op_dict.update(forward_op_dict)
     op_dict.update(backward_op_dict)
-
     if len(ops) == 0 and len(backward_ops) == 0:
         if os.path.isfile(output_op_path):
             os.remove(output_op_path)
         if os.path.isfile(output_arg_map_path):
             os.remove(output_arg_map_path)
         return
-
     op_template = env.get_template('op.c.j2')
     with open(output_op_path, "wt") as f:
         msg = op_template.render(
-            ops=ops, backward_ops=backward_ops, op_dict=op_dict
+            ops=ops,
+            backward_ops=backward_ops,
+            op_dict=op_dict,
+            composite_gen_flag=True,
         )
         f.write(msg)
-
     ks_template = env.get_template('ks.c.j2')
     with open(output_arg_map_path, 'wt') as f:
         msg = ks_template.render(ops=ops, backward_ops=backward_ops)

paddle/fluid/operators/generator/generate_sparse_op.py

@@ -19,6 +19,7 @@
 import yaml
 from filters import (
     cartesian_prod_mapping,
+    to_composite_grad_opmaker_name,
     to_input_name,
     to_int_array_tensor_name,
     to_int_array_tensors_name,
@@ -58,6 +59,7 @@
 env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
+env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
 env.tests["base_op"] = is_base_op
 env.tests["vec"] = is_vec
 env.tests["scalar"] = is_scalar
@@ -134,7 +136,10 @@ def main(op_yaml_path, backward_yaml_path, output_op_path, output_arg_map_path):
     op_template = env.get_template('sparse_op.c.j2')
     with open(output_op_path, "wt") as f:
         msg = op_template.render(
-            ops=ops, backward_ops=backward_ops, op_dict=op_dict
+            ops=ops,
+            backward_ops=backward_ops,
+            op_dict=op_dict,
+            composite_gen_flag=False,
         )
         f.write(msg)
 

paddle/fluid/operators/generator/generate_static_op.py

@@ -19,6 +19,7 @@
 import yaml
 from filters import (
     cartesian_prod_mapping,
+    to_composite_grad_opmaker_name,
     to_input_name,
     to_int_array_tensor_name,
     to_int_array_tensors_name,
@@ -58,6 +59,7 @@
 env.filters["to_input_name"] = to_input_name
 env.filters["to_opmaker_name_cstr"] = to_opmaker_name_cstr
 env.filters["cartesian_prod_mapping"] = cartesian_prod_mapping
+env.filters["to_composite_grad_opmaker_name"] = to_composite_grad_opmaker_name
 env.tests["base_op"] = is_base_op
 env.tests["vec"] = is_vec
 env.tests["scalar"] = is_scalar
@@ -111,7 +113,10 @@ def main(
     op_template = env.get_template('op.c.j2')
     with open(output_op_path, "wt") as f:
         msg = op_template.render(
-            ops=ops, backward_ops=[], op_dict=forward_op_dict
+            ops=ops,
+            backward_ops=[],
+            op_dict=forward_op_dict,
+            composite_gen_flag=False,
         )
         f.write(msg)
 

paddle/fluid/operators/generator/parse_utils.py

@@ -289,6 +289,26 @@ def parse_forward(op_name: str, forward_config: str) -> Dict[str, Any]:
     return forward_cfg
 
 
+def parse_composite(
+    op_name: str,
+    composite_config: str,
+) -> Dict[str, Any]:
+    # composite_config: func(args1, args2,.....)
+    fname = r'(.*?)'
+    wspace = r'\s*'
+    fargs = r'(.*?)'
+    pattern = fr'{fname}{wspace}\({wspace}{fargs}{wspace}\)'
+
+    m = re.search(pattern, composite_config)
+    func_name = m.group(1)
+    func_args = m.group(2)
+
+    composite_dict = {}
+    composite_dict["func_name"] = func_name
+    composite_dict["func_args"] = func_args
+    return composite_dict
+
+
 def check_op_config(op_entry, op_name):
     base_key_set = (
         'op',
@@ -332,9 +352,9 @@ def parse_op_entry(op_entry: Dict[str, Any], name_field="op"):
     op_name = op_entry[name_field]
     inputs, attrs = parse_input_and_attr(op_name, op_entry["args"])
     outputs = parse_outputs(op_name, op_entry["output"])
-
+    if "composite" in op_entry:
+        composite_dict = parse_composite(op_name, op_entry["composite"])
     check_op_config(op_entry, op_name)
-
     # validate default value of DataType and DataLayout
     for attr in attrs:
         if "default_value" in attr:
@@ -442,6 +462,10 @@ def parse_op_entry(op_entry: Dict[str, Any], name_field="op"):
         invoke = parse_invoke(op_name, op_entry["invoke"])
         op["invoke"] = invoke
 
+    # has composite ?
+    if "composite" in op_entry:
+        op.update({"composite": composite_dict})
+
     # backward
     if "backward" in op_entry:
         backward = op_entry["backward"]

paddle/fluid/operators/generator/templates/op.c.j2

@@ -1,17 +1,20 @@
-{% from "operator_utils.c.j2" import op_maker, backward_op_maker, backward_op_reused_maker, operator, register_op_with_components, register_op_version %}
+{% from "operator_utils.c.j2" import op_maker, backward_op_maker, backward_op_reused_maker, operator, register_op_with_components, register_op_version, composite_grad_op_maker %}
 // this file is generated by paddle/phi/api/yaml/generator/generate_op.py, do not edit.
 #include <string>
+#include "paddle/fluid/framework/convert_utils.h"
 #include "paddle/fluid/framework/infershape_utils.h"
 #include "paddle/fluid/framework/op_registry.h"
 #include "paddle/fluid/framework/op_version_registry.h"
-#include "paddle/fluid/framework/convert_utils.h"
+#include "paddle/fluid/prim/api/manual/backward/composite_backward_api.h"
+#include "paddle/fluid/prim/utils/static/composite_grad_desc_maker.h"
+#include "paddle/fluid/prim/utils/static/desc_tensor.h"
 #include "paddle/phi/core/infermeta_utils.h"
-#include "paddle/phi/infermeta/nullary.h"
-#include "paddle/phi/infermeta/unary.h"
+#include "paddle/phi/infermeta/backward.h"
 #include "paddle/phi/infermeta/binary.h"
-#include "paddle/phi/infermeta/ternary.h"
 #include "paddle/phi/infermeta/multiary.h"
-#include "paddle/phi/infermeta/backward.h"
+#include "paddle/phi/infermeta/nullary.h"
+#include "paddle/phi/infermeta/ternary.h"
+#include "paddle/phi/infermeta/unary.h"
 
 namespace paddle {
 namespace operators {
@@ -36,14 +39,19 @@ using paddle::framework::GradVarName;
   {% else %}
 {{backward_op_reused_maker(op, op_dict[op["forward"]["name"]], op["invoke"])}}
   {% endif %}
+  {% if composite_gen_flag == True %}
+    {% if op is composite_op %}
+{{composite_grad_op_maker(op_dict[op["name"]])}}
+    {% endif %}
+  {% endif %}  
 {% endfor %}
 }  // namespace operators
 }  // namespace paddle
 
 namespace ops = paddle::operators;
 {% for op in ops + backward_ops %}
 {% if op is base_op %}
-{{register_op_with_components(op)}}
+{{register_op_with_components(op, op_dict)}}
 {{register_op_version(op)}}
 {% endif %}
 {% endfor %}