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Merge pull request #592 from littletomatodonkey/fix_predictor_run 

replace zero_copy_run to run for memory leak
This commit is contained in:
dyning 2020-08-24 15:45:18 +08:00 committed by GitHub
parent 488486587b ed52619f4b
commit 967115b8e9
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GPG Key ID: 4AEE18F83AFDEB23
10 changed files with 100 additions and 46 deletions
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4
deploy/cpp_infer/include/config.h
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@ -41,6 +41,8 @@ public:
this->use_mkldnn = bool(stoi(config_map_["use_mkldnn"]));
this->use_zero_copy_run = bool(stoi(config_map_["use_zero_copy_run"]));
this->max_side_len = stoi(config_map_["max_side_len"]);
this->det_db_thresh = stod(config_map_["det_db_thresh"]);
@ -68,6 +70,8 @@ public:
bool use_mkldnn = false;
bool use_zero_copy_run = false;
int max_side_len = 960;
double det_db_thresh = 0.3;

6
deploy/cpp_infer/include/ocr_det.h
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@ -39,8 +39,8 @@ public:
explicit DBDetector(const std::string &model_dir, const bool &use_gpu,
const int &gpu_id, const int &gpu_mem,
const int &cpu_math_library_num_threads,
const bool &use_mkldnn, const int &max_side_len,
const double &det_db_thresh,
const bool &use_mkldnn, const bool &use_zero_copy_run,
const int &max_side_len, const double &det_db_thresh,
const double &det_db_box_thresh,
const double &det_db_unclip_ratio,
const bool &visualize) {
@ -49,6 +49,7 @@ public:
this->gpu_mem_ = gpu_mem;
this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
this->use_mkldnn_ = use_mkldnn;
this->use_zero_copy_run_ = use_zero_copy_run;
this->max_side_len_ = max_side_len;
@ -75,6 +76,7 @@ private:
int gpu_mem_ = 4000;
int cpu_math_library_num_threads_ = 4;
bool use_mkldnn_ = false;
bool use_zero_copy_run_ = false;
int max_side_len_ = 960;

5
deploy/cpp_infer/include/ocr_rec.h
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@ -38,12 +38,14 @@ public:
explicit CRNNRecognizer(const std::string &model_dir, const bool &use_gpu,
const int &gpu_id, const int &gpu_mem,
const int &cpu_math_library_num_threads,
const bool &use_mkldnn, const string &label_path) {
const bool &use_mkldnn, const bool &use_zero_copy_run,
const string &label_path) {
this->use_gpu_ = use_gpu;
this->gpu_id_ = gpu_id;
this->gpu_mem_ = gpu_mem;
this->cpu_math_library_num_threads_ = cpu_math_library_num_threads;
this->use_mkldnn_ = use_mkldnn;
this->use_zero_copy_run_ = use_zero_copy_run;
this->label_list_ = Utility::ReadDict(label_path);
this->label_list_.push_back(" ");
@ -64,6 +66,7 @@ private:
int gpu_mem_ = 4000;
int cpu_math_library_num_threads_ = 4;
bool use_mkldnn_ = false;
bool use_zero_copy_run_ = false;
std::vector<std::string> label_list_;

13
deploy/cpp_infer/src/main.cpp
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@ -48,14 +48,15 @@ int main(int argc, char **argv) {
cv::Mat srcimg = cv::imread(img_path, cv::IMREAD_COLOR);
DBDetector det(config.det_model_dir, config.use_gpu, config.gpu_id,
config.gpu_mem, config.cpu_math_library_num_threads,
config.use_mkldnn, config.max_side_len, config.det_db_thresh,
config.det_db_box_thresh, config.det_db_unclip_ratio,
config.visualize);
DBDetector det(
config.det_model_dir, config.use_gpu, config.gpu_id, config.gpu_mem,
config.cpu_math_library_num_threads, config.use_mkldnn,
config.use_zero_copy_run, config.max_side_len, config.det_db_thresh,
config.det_db_box_thresh, config.det_db_unclip_ratio, config.visualize);
CRNNRecognizer rec(config.rec_model_dir, config.use_gpu, config.gpu_id,
config.gpu_mem, config.cpu_math_library_num_threads,
config.use_mkldnn, config.char_list_file);
config.use_mkldnn, config.use_zero_copy_run,
config.char_list_file);
auto start = std::chrono::system_clock::now();
std::vector<std::vector<std::vector<int>>> boxes;

25
deploy/cpp_infer/src/ocr_det.cpp
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@ -31,7 +31,8 @@ void DBDetector::LoadModel(const std::string &model_dir) {
}
// false for zero copy tensor
config.SwitchUseFeedFetchOps(false);
// true for commom tensor
config.SwitchUseFeedFetchOps(!this->use_zero_copy_run_);
// true for multiple input
config.SwitchSpecifyInputNames(true);
@ -59,12 +60,22 @@ void DBDetector::Run(cv::Mat &img,
std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
this->permute_op_.Run(&resize_img, input.data());
auto input_names = this->predictor_->GetInputNames();
auto input_t = this->predictor_->GetInputTensor(input_names[0]);
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
input_t->copy_from_cpu(input.data());
this->predictor_->ZeroCopyRun();
// Inference.
if (this->use_zero_copy_run_) {
auto input_names = this->predictor_->GetInputNames();
auto input_t = this->predictor_->GetInputTensor(input_names[0]);
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
input_t->copy_from_cpu(input.data());
this->predictor_->ZeroCopyRun();
} else {
paddle::PaddleTensor input_t;
input_t.shape = {1, 3, resize_img.rows, resize_img.cols};
input_t.data =
paddle::PaddleBuf(input.data(), input.size() * sizeof(float));
input_t.dtype = PaddleDType::FLOAT32;
std::vector<paddle::PaddleTensor> outputs;
this->predictor_->Run({input_t}, &outputs, 1);
}
std::vector<float> out_data;
auto output_names = this->predictor_->GetOutputNames();

26
deploy/cpp_infer/src/ocr_rec.cpp
View File

@ -39,18 +39,29 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
this->permute_op_.Run(&resize_img, input.data());
auto input_names = this->predictor_->GetInputNames();
auto input_t = this->predictor_->GetInputTensor(input_names[0]);
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
input_t->copy_from_cpu(input.data());
this->predictor_->ZeroCopyRun();
// Inference.
if (this->use_zero_copy_run_) {
auto input_names = this->predictor_->GetInputNames();
auto input_t = this->predictor_->GetInputTensor(input_names[0]);
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols});
input_t->copy_from_cpu(input.data());
this->predictor_->ZeroCopyRun();
} else {
paddle::PaddleTensor input_t;
input_t.shape = {1, 3, resize_img.rows, resize_img.cols};
input_t.data =
paddle::PaddleBuf(input.data(), input.size() * sizeof(float));
input_t.dtype = PaddleDType::FLOAT32;
std::vector<paddle::PaddleTensor> outputs;
this->predictor_->Run({input_t}, &outputs, 1);
}
std::vector<int64_t> rec_idx;
auto output_names = this->predictor_->GetOutputNames();
auto output_t = this->predictor_->GetOutputTensor(output_names[0]);
auto rec_idx_lod = output_t->lod();
auto shape_out = output_t->shape();
int out_num = std::accumulate(shape_out.begin(), shape_out.end(), 1,
std::multiplies<int>());
@ -120,7 +131,8 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
}
// false for zero copy tensor
config.SwitchUseFeedFetchOps(false);
// true for commom tensor
config.SwitchUseFeedFetchOps(!this->use_zero_copy_run_);
// true for multiple input
config.SwitchSpecifyInputNames(true);

1
deploy/cpp_infer/tools/config.txt
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@ -4,6 +4,7 @@ gpu_id 0
gpu_mem 4000
cpu_math_library_num_threads 10
use_mkldnn 0
use_zero_copy_run 1
# det config
max_side_len 960

36
tools/infer/predict_det.py
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@ -17,28 +17,32 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
import tools.infer.utility as utility
from ppocr.utils.utility import initial_logger
logger = initial_logger()
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
import cv2
from ppocr.data.det.sast_process import SASTProcessTest
from ppocr.data.det.east_process import EASTProcessTest
from ppocr.data.det.db_process import DBProcessTest
from ppocr.postprocess.db_postprocess import DBPostProcess
from ppocr.postprocess.east_postprocess import EASTPostPocess
from ppocr.postprocess.sast_postprocess import SASTPostProcess
import copy
import numpy as np
import math
import time
import sys
import paddle.fluid as fluid
import tools.infer.utility as utility
from ppocr.utils.utility import initial_logger
logger = initial_logger()
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
from ppocr.data.det.sast_process import SASTProcessTest
from ppocr.data.det.east_process import EASTProcessTest
from ppocr.data.det.db_process import DBProcessTest
from ppocr.postprocess.db_postprocess import DBPostProcess
from ppocr.postprocess.east_postprocess import EASTPostPocess
from ppocr.postprocess.sast_postprocess import SASTPostProcess
class TextDetector(object):
def __init__(self, args):
max_side_len = args.det_max_side_len
self.det_algorithm = args.det_algorithm
self.use_zero_copy_run = args.use_zero_copy_run
preprocess_params = {'max_side_len': max_side_len}
postprocess_params = {}
if self.det_algorithm == "DB":
@ -127,7 +131,7 @@ class TextDetector(object):
dt_boxes_new.append(box)
dt_boxes = np.array(dt_boxes_new)
return dt_boxes
def __call__(self, img):
ori_im = img.copy()
im, ratio_list = self.preprocess_op(img)
@ -135,8 +139,12 @@ class TextDetector(object):
return None, 0
im = im.copy()
starttime = time.time()
self.input_tensor.copy_from_cpu(im)
self.predictor.zero_copy_run()
if self.use_zero_copy_run:
self.input_tensor.copy_from_cpu(im)
self.predictor.zero_copy_run()
else:
im = fluid.core.PaddleTensor(im)
self.predictor.run([im])
outputs = []
for output_tensor in self.output_tensors:
output = output_tensor.copy_to_cpu()
@ -152,7 +160,7 @@ class TextDetector(object):
outs_dict['f_tvo'] = outputs[3]
else:
outs_dict['maps'] = outputs[0]
dt_boxes_list = self.postprocess_op(outs_dict, [ratio_list])
dt_boxes = dt_boxes_list[0]
if self.det_algorithm == "SAST" and self.det_sast_polygon:

20
tools/infer/predict_rec.py
View File

@ -17,15 +17,18 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
import tools.infer.utility as utility
from ppocr.utils.utility import initial_logger
logger = initial_logger()
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
import cv2
import copy
import numpy as np
import math
import time
import paddle.fluid as fluid
import tools.infer.utility as utility
from ppocr.utils.utility import initial_logger
logger = initial_logger()
from ppocr.utils.utility import get_image_file_list, check_and_read_gif
from ppocr.utils.character import CharacterOps
@ -37,6 +40,7 @@ class TextRecognizer(object):
self.character_type = args.rec_char_type
self.rec_batch_num = args.rec_batch_num
self.rec_algorithm = args.rec_algorithm
self.use_zero_copy_run = args.use_zero_copy_run
char_ops_params = {
"character_type": args.rec_char_type,
"character_dict_path": args.rec_char_dict_path,
@ -102,8 +106,12 @@ class TextRecognizer(object):
norm_img_batch = np.concatenate(norm_img_batch)
norm_img_batch = norm_img_batch.copy()
starttime = time.time()
self.input_tensor.copy_from_cpu(norm_img_batch)
self.predictor.zero_copy_run()
if self.use_zero_copy_run:
self.input_tensor.copy_from_cpu(norm_img_batch)
self.predictor.zero_copy_run()
else:
norm_img_batch = fluid.core.PaddleTensor(norm_img_batch)
self.predictor.run([norm_img_batch])
if self.loss_type == "ctc":
rec_idx_batch = self.output_tensors[0].copy_to_cpu()

10
tools/infer/utility.py
View File

@ -71,6 +71,7 @@ def parse_args():
default="./ppocr/utils/ppocr_keys_v1.txt")
parser.add_argument("--use_space_char", type=bool, default=True)
parser.add_argument("--enable_mkldnn", type=bool, default=False)
parser.add_argument("--use_zero_copy_run", type=bool, default=False)
return parser.parse_args()
@ -105,9 +106,12 @@ def create_predictor(args, mode):
#config.enable_memory_optim()
config.disable_glog_info()
# use zero copy
config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass")
config.switch_use_feed_fetch_ops(False)
if args.use_zero_copy_run:
config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass")
config.switch_use_feed_fetch_ops(False)
else:
config.switch_use_feed_fetch_ops(True)
predictor = create_paddle_predictor(config)
input_names = predictor.get_input_names()
input_tensor = predictor.get_input_tensor(input_names[0])