431 lines
14 KiB
Python
431 lines
14 KiB
Python
# Copyright (c) 2021 PaddlePaddle Authors. All Rights Reserved.
|
|
#
|
|
# Licensed under the Apache License, Version 2.0 (the "License");
|
|
# you may not use this file except in compliance with the License.
|
|
# You may obtain a copy of the License at
|
|
#
|
|
# http://www.apache.org/licenses/LICENSE-2.0
|
|
#
|
|
# Unless required by applicable law or agreed to in writing, software
|
|
# distributed under the License is distributed on an "AS IS" BASIS,
|
|
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
|
|
# See the License for the specific language governing permissions and
|
|
# limitations under the License.
|
|
|
|
import argparse
|
|
import re
|
|
|
|
import yaml
|
|
from api_base import BaseAPI
|
|
|
|
|
|
class BackwardAPI(BaseAPI):
|
|
def __init__(self, backward_item_yaml):
|
|
super().__init__(backward_item_yaml)
|
|
self.check_args(backward_item_yaml['forward'])
|
|
self.no_need_buffer = self.parse_no_need_buffer(backward_item_yaml)
|
|
|
|
def get_api_name(self, api_item_yaml):
|
|
return api_item_yaml['backward_op']
|
|
|
|
def parse_forward_config(self, forward_config):
|
|
# api_name (const Tensor& input, ... , int attr, ...) -> Tensor(out)
|
|
result = re.search(
|
|
r"(?P<op>[a-z][a-z0-9_]+)\s*(?P<args>\([^\)]+\))\s*->\s*(?P<outputs>.+)",
|
|
forward_config,
|
|
)
|
|
api = result.group('op')
|
|
(
|
|
_,
|
|
outputs,
|
|
_,
|
|
) = self.parse_output(self.api, result.group('outputs'))
|
|
outputs = [item.split('@')[0] for item in outputs]
|
|
fw_inputs, fw_attrs = self.parse_input_and_attr(
|
|
api, result.group('args')
|
|
)
|
|
|
|
return api, fw_inputs, fw_attrs, outputs
|
|
|
|
def parse_no_need_buffer(self, api_item_yaml):
|
|
no_need_buffer = []
|
|
if 'no_need_buffer' in api_item_yaml:
|
|
no_need_buffer = [
|
|
item.strip()
|
|
for item in api_item_yaml['no_need_buffer'].split(',')
|
|
]
|
|
return no_need_buffer
|
|
|
|
def check_args(self, forward_config):
|
|
# parse the forward and backward config
|
|
_, fw_inputs, fw_attrs, fw_outputs = self.parse_forward_config(
|
|
forward_config
|
|
)
|
|
|
|
# check the inputs of backward
|
|
for input in self.inputs['names']:
|
|
if input not in fw_inputs['names'] and input not in fw_outputs:
|
|
if input.endswith('_grad'):
|
|
original_name = input[:-5]
|
|
assert original_name in fw_outputs, (
|
|
f"{self.api} : Input Tensor error: the input tensor({input}) of backward should be an input or output or grad of output in forward api. \
|
|
Please check the forward of {self.api} in yaml."
|
|
)
|
|
|
|
# check the attributes of backward
|
|
for attr in self.attrs['names']:
|
|
assert (
|
|
attr in fw_attrs['names']
|
|
and self.attrs['attr_info'][attr][0]
|
|
== fw_attrs['attr_info'][attr][0]
|
|
) or self.attrs['attr_info'][attr][1] is not None, (
|
|
f"{self.api} : Attribute error: The attribute({attr}) of backward isn't consistent with forward api or doesn't have default value. \
|
|
Please check the args of {self.api} in yaml."
|
|
)
|
|
|
|
# check the output of backward
|
|
assert len(self.outputs['types']) <= len(fw_inputs['names']), (
|
|
f"{self.api} : Output error: The number of outputs should be less then the number of inputs of forward api. \
|
|
Please check the output of {self.api} in yaml."
|
|
)
|
|
|
|
def get_declare_args(
|
|
self, inplace_flag=False, grad_flag=False, append_predefined_out=False
|
|
):
|
|
return self.get_define_args(
|
|
grad_flag=grad_flag, append_predefined_out=append_predefined_out
|
|
)
|
|
|
|
def get_define_args(
|
|
self, inplace_flag=False, grad_flag=False, append_predefined_out=False
|
|
):
|
|
out_type_map = {
|
|
'Tensor': 'Tensor*',
|
|
'std::vector<Tensor>': 'std::vector<Tensor*>',
|
|
}
|
|
inputs_and_attrs = super().get_define_args(
|
|
grad_flag=grad_flag, append_predefined_out=False
|
|
)
|
|
outs = []
|
|
for i, name in enumerate(self.outputs['names']):
|
|
outs.append(
|
|
out_type_map[self.outputs['types'][i]]
|
|
+ ' '
|
|
+ name.split('@')[0]
|
|
)
|
|
result = inputs_and_attrs + ', ' + ", ".join(outs)
|
|
return result
|
|
|
|
def gene_return_code(self):
|
|
return ""
|
|
|
|
def gene_api_declaration(
|
|
self, grad_flag=False, append_predefined_out=False
|
|
):
|
|
if not self.is_base_api and not self.is_only_composite_api:
|
|
invoke_func_name = self.invoke.split('(')[0]
|
|
if (not invoke_func_name.endswith("_grad")) and (
|
|
not invoke_func_name.endswith('_impl')
|
|
):
|
|
return ""
|
|
|
|
if self.is_only_composite_api:
|
|
return ""
|
|
|
|
api_func_name = self.get_api_func_name()
|
|
api_declaration = f"""
|
|
PADDLE_API void {api_func_name}({self.get_declare_args()});
|
|
"""
|
|
return api_declaration
|
|
|
|
def gene_kernel_backend_select(self):
|
|
all_no_need_buffer = True
|
|
for in_name in self.inputs['names']:
|
|
if in_name not in self.no_need_buffer:
|
|
all_no_need_buffer = False
|
|
|
|
if all_no_need_buffer:
|
|
return """
|
|
kernel_backend = ParseBackend(egr::Controller::Instance().GetExpectedPlace());
|
|
"""
|
|
else:
|
|
return super().gene_kernel_backend_select()
|
|
|
|
def get_return_type(self, inplace_flag=False):
|
|
return 'void'
|
|
|
|
def gene_output(
|
|
self,
|
|
out_dtype_list,
|
|
out_tensor_type_list=None,
|
|
code_indent='',
|
|
inplace_flag=False,
|
|
):
|
|
kernel_output = []
|
|
output_names = []
|
|
output_create = ""
|
|
|
|
if len(out_dtype_list) == 1:
|
|
kernel_output.append('kernel_out')
|
|
output_names.append('kernel_out')
|
|
inplace_assign = (
|
|
" = " + self.inplace_map[self.outputs['names'][0]]
|
|
if inplace_flag
|
|
and self.inplace_map is not None
|
|
and self.outputs['names'][0] in self.inplace_map
|
|
else ""
|
|
)
|
|
output_create = ""
|
|
set_out_func = (
|
|
'SetKernelOutput'
|
|
if out_tensor_type_list is None
|
|
or out_tensor_type_list[0] == 'dense'
|
|
else 'SetSelectedRowsKernelOutput'
|
|
)
|
|
if out_dtype_list[0] == 'std::vector<Tensor>':
|
|
assert self.outputs['out_size_expr'] is not None, (
|
|
f"{self.api}: The out size expr : '{{expr}}' should be set when output has Tensor[]. You can refer 'split' api."
|
|
)
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} auto kernel_out = {set_out_func}(&{self.outputs['names'][0]});"""
|
|
)
|
|
|
|
else:
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} auto kernel_out = {set_out_func}({self.outputs['names'][0]});"""
|
|
)
|
|
|
|
elif len(out_dtype_list) > 1:
|
|
output_create = ""
|
|
for i, out_type_item in enumerate(out_dtype_list):
|
|
kernel_output.append(f'kernel_out_{i}')
|
|
output_names.append(f'kernel_out_{i}')
|
|
set_out_func = (
|
|
'SetKernelOutput'
|
|
if out_tensor_type_list is None
|
|
or out_tensor_type_list[i] == 'dense'
|
|
else 'SetSelectedRowsKernelOutput'
|
|
)
|
|
if out_type_item == 'Tensor':
|
|
if (
|
|
inplace_flag
|
|
and self.inplace_map is not None
|
|
and self.outputs['names'][i] in self.inplace_map
|
|
):
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} *{self.outputs['names'][i]} = {self.inplace_map[self.outputs['names'][i]]};"""
|
|
)
|
|
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} auto kernel_out_{i} = {set_out_func}({self.outputs['names'][i]});"""
|
|
)
|
|
|
|
else:
|
|
if (
|
|
inplace_flag
|
|
and self.inplace_map is not None
|
|
and self.outputs['names'][i] in self.inplace_map
|
|
):
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} *{self.outputs['names'][i]} = {self.inplace_map[self.outputs['names'][i]]};"""
|
|
)
|
|
|
|
assert self.outputs['out_size_expr'][i] is not None, (
|
|
f"{self.api}: The out size expr : '{{expr}}' should be set when output has Tensor[]. You can refer 'split' api."
|
|
)
|
|
output_create = (
|
|
output_create
|
|
+ f"""
|
|
{code_indent} auto kernel_out_{i} = {set_out_func}(&{self.outputs['names'][i]});"""
|
|
)
|
|
|
|
else:
|
|
raise ValueError(
|
|
f"{self.api} : Output error: the output should not be empty."
|
|
)
|
|
|
|
return kernel_output, output_names, output_create
|
|
|
|
def gene_invoke_code(self, invoke_code, params_code):
|
|
invoke_func_name = invoke_code.split('(')[0].strip()
|
|
if invoke_func_name.endswith('_grad') or invoke_func_name.endswith(
|
|
'_impl'
|
|
):
|
|
return f"""
|
|
PADDLE_API {self.get_return_type()} {self.api}({params_code}) {{
|
|
{invoke_code};
|
|
}}"""
|
|
|
|
else:
|
|
return ""
|
|
|
|
|
|
def header_include():
|
|
return """
|
|
#include <tuple>
|
|
|
|
#include "paddle/phi/api/include/tensor.h"
|
|
#include "paddle/phi/common/scalar.h"
|
|
#include "paddle/phi/common/int_array.h"
|
|
#include "paddle/utils/optional.h"
|
|
"""
|
|
|
|
|
|
def source_include(header_file_path, fw_header_file_path):
|
|
return f"""
|
|
#include "{header_file_path}"
|
|
#include <memory>
|
|
|
|
#include "glog/logging.h"
|
|
#include "paddle/common/flags.h"
|
|
|
|
#include "paddle/phi/api/lib/api_custom_impl.h"
|
|
#include "paddle/phi/api/lib/api_gen_utils.h"
|
|
#include "paddle/phi/api/lib/data_transform.h"
|
|
#include "paddle/phi/api/lib/kernel_dispatch.h"
|
|
#include "paddle/phi/common/type_traits.h"
|
|
#include "paddle/phi/core/kernel_registry.h"
|
|
#include "{fw_header_file_path}"
|
|
#include "paddle/phi/infermeta/backward.h"
|
|
#include "paddle/phi/infermeta/unary.h"
|
|
#include "paddle/phi/infermeta/fusion.h"
|
|
|
|
#include "paddle/phi/api/profiler/event_tracing.h"
|
|
#include "paddle/phi/api/profiler/supplement_tracing.h"
|
|
|
|
PD_DECLARE_bool(conv2d_disable_cudnn);
|
|
COMMON_DECLARE_int32(low_precision_op_list);
|
|
COMMON_DECLARE_bool(benchmark);
|
|
"""
|
|
|
|
|
|
def backward_api_namespace():
|
|
return (
|
|
"""
|
|
namespace paddle {
|
|
namespace experimental {
|
|
|
|
""",
|
|
"""
|
|
|
|
} // namespace experimental
|
|
} // namespace paddle
|
|
""",
|
|
)
|
|
|
|
|
|
def generate_backward_api(
|
|
backward_yaml_path,
|
|
is_fused_backward_yaml,
|
|
header_file_path,
|
|
source_file_path,
|
|
):
|
|
bw_apis = []
|
|
for each_api_yaml in backward_yaml_path:
|
|
with open(each_api_yaml, 'r') as f:
|
|
api_list = yaml.load(f, Loader=yaml.FullLoader)
|
|
if api_list:
|
|
bw_apis.extend(api_list)
|
|
|
|
header_file = open(header_file_path, 'w')
|
|
source_file = open(source_file_path, 'w')
|
|
|
|
namespace = backward_api_namespace()
|
|
|
|
header_file.write("#pragma once\n")
|
|
header_file.write(header_include())
|
|
header_file.write(namespace[0])
|
|
|
|
include_header_file = (
|
|
"paddle/phi/api/backward/fused_backward_api_base.h"
|
|
if is_fused_backward_yaml
|
|
else "paddle/phi/api/backward/backward_api_base.h"
|
|
)
|
|
include_fw_header_file = (
|
|
"paddle/phi/api/include/fused_api.h"
|
|
if is_fused_backward_yaml
|
|
else "paddle/phi/api/include/api.h"
|
|
)
|
|
source_file.write(
|
|
source_include(include_header_file, include_fw_header_file)
|
|
)
|
|
source_file.write(namespace[0])
|
|
# not all fused ops support dygraph
|
|
if is_fused_backward_yaml is True:
|
|
new_bw_apis = [
|
|
bw_api
|
|
for bw_api in bw_apis
|
|
if "support_dygraph_mode" in bw_api
|
|
and bw_api["support_dygraph_mode"] is True
|
|
]
|
|
bw_apis = new_bw_apis
|
|
|
|
for bw_api in bw_apis:
|
|
bw_api = BackwardAPI(bw_api)
|
|
header_file.write(bw_api.gene_api_declaration())
|
|
source_file.write(bw_api.gene_api_code())
|
|
|
|
header_file.write(namespace[1])
|
|
source_file.write(namespace[1])
|
|
|
|
header_file.close()
|
|
source_file.close()
|
|
|
|
|
|
def main():
|
|
parser = argparse.ArgumentParser(
|
|
description='Generate PaddlePaddle C++ backward API files'
|
|
)
|
|
parser.add_argument(
|
|
'--backward_yaml_path',
|
|
help='path to backward yaml file',
|
|
nargs='+',
|
|
default=['paddle/phi/ops/yaml/backward.yaml'],
|
|
)
|
|
|
|
parser.add_argument(
|
|
'--is_fused_backward_yaml',
|
|
help='flag of fused backward yaml',
|
|
action='store_true',
|
|
)
|
|
|
|
parser.add_argument(
|
|
'--backward_header_path',
|
|
help='output of generated backward header code file',
|
|
default='paddle/phi/api/backward/backward_api_base.h',
|
|
)
|
|
|
|
parser.add_argument(
|
|
'--backward_source_path',
|
|
help='output of generated backward source code file',
|
|
default='paddle/phi/api/lib/backward_api_base.cc',
|
|
)
|
|
|
|
options = parser.parse_args()
|
|
|
|
backward_yaml_path = options.backward_yaml_path
|
|
is_fused_backward_yaml = options.is_fused_backward_yaml
|
|
header_file_path = options.backward_header_path
|
|
source_file_path = options.backward_source_path
|
|
|
|
generate_backward_api(
|
|
backward_yaml_path,
|
|
is_fused_backward_yaml,
|
|
header_file_path,
|
|
source_file_path,
|
|
)
|
|
|
|
|
|
if __name__ == '__main__':
|
|
main()
|