提交 3ebebae3 编写于 作者: littletomatodonkey's avatar littletomatodonkey

replace zero_copy_run to run for memory leak

上级 48848658
...@@ -31,7 +31,8 @@ void DBDetector::LoadModel(const std::string &model_dir) { ...@@ -31,7 +31,8 @@ void DBDetector::LoadModel(const std::string &model_dir) {
} }
// false for zero copy tensor // false for zero copy tensor
config.SwitchUseFeedFetchOps(false); // true for commom tensor
config.SwitchUseFeedFetchOps(true);
// true for multiple input // true for multiple input
config.SwitchSpecifyInputNames(true); config.SwitchSpecifyInputNames(true);
...@@ -59,12 +60,13 @@ void DBDetector::Run(cv::Mat &img, ...@@ -59,12 +60,13 @@ void DBDetector::Run(cv::Mat &img,
std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f); std::vector<float> input(1 * 3 * resize_img.rows * resize_img.cols, 0.0f);
this->permute_op_.Run(&resize_img, input.data()); this->permute_op_.Run(&resize_img, input.data());
auto input_names = this->predictor_->GetInputNames(); // Inference.
auto input_t = this->predictor_->GetInputTensor(input_names[0]); paddle::PaddleTensor input_t;
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols}); input_t.shape = {1, 3, resize_img.rows, resize_img.cols};
input_t->copy_from_cpu(input.data()); input_t.data = paddle::PaddleBuf(input.data(), input.size() * sizeof(float));
input_t.dtype = PaddleDType::FLOAT32;
this->predictor_->ZeroCopyRun(); std::vector<paddle::PaddleTensor> outputs;
this->predictor_->Run({input_t}, &outputs, 1);
std::vector<float> out_data; std::vector<float> out_data;
auto output_names = this->predictor_->GetOutputNames(); auto output_names = this->predictor_->GetOutputNames();
......
...@@ -39,18 +39,21 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes, ...@@ -39,18 +39,21 @@ void CRNNRecognizer::Run(std::vector<std::vector<std::vector<int>>> boxes,
this->permute_op_.Run(&resize_img, input.data()); this->permute_op_.Run(&resize_img, input.data());
auto input_names = this->predictor_->GetInputNames(); // Inference.
auto input_t = this->predictor_->GetInputTensor(input_names[0]); paddle::PaddleTensor input_t;
input_t->Reshape({1, 3, resize_img.rows, resize_img.cols}); input_t.shape = {1, 3, resize_img.rows, resize_img.cols};
input_t->copy_from_cpu(input.data()); input_t.data =
paddle::PaddleBuf(input.data(), input.size() * sizeof(float));
this->predictor_->ZeroCopyRun(); input_t.dtype = PaddleDType::FLOAT32;
std::vector<paddle::PaddleTensor> outputs;
this->predictor_->Run({input_t}, &outputs, 1);
std::vector<int64_t> rec_idx; std::vector<int64_t> rec_idx;
auto output_names = this->predictor_->GetOutputNames(); auto output_names = this->predictor_->GetOutputNames();
auto output_t = this->predictor_->GetOutputTensor(output_names[0]); auto output_t = this->predictor_->GetOutputTensor(output_names[0]);
auto rec_idx_lod = output_t->lod(); auto rec_idx_lod = output_t->lod();
auto shape_out = output_t->shape(); auto shape_out = output_t->shape();
int out_num = std::accumulate(shape_out.begin(), shape_out.end(), 1, int out_num = std::accumulate(shape_out.begin(), shape_out.end(), 1,
std::multiplies<int>()); std::multiplies<int>());
...@@ -120,7 +123,8 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) { ...@@ -120,7 +123,8 @@ void CRNNRecognizer::LoadModel(const std::string &model_dir) {
} }
// false for zero copy tensor // false for zero copy tensor
config.SwitchUseFeedFetchOps(false); // true for commom tensor
config.SwitchUseFeedFetchOps(true);
// true for multiple input // true for multiple input
config.SwitchSpecifyInputNames(true); config.SwitchSpecifyInputNames(true);
......
...@@ -17,22 +17,25 @@ __dir__ = os.path.dirname(os.path.abspath(__file__)) ...@@ -17,22 +17,25 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__) sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__dir__, '../..'))) sys.path.append(os.path.abspath(os.path.join(__dir__, '../..')))
import cv2
import copy
import numpy as np
import math
import time
import sys
import paddle.fluid as fluid
import tools.infer.utility as utility import tools.infer.utility as utility
from ppocr.utils.utility import initial_logger from ppocr.utils.utility import initial_logger
logger = initial_logger() logger = initial_logger()
from ppocr.utils.utility import get_image_file_list, check_and_read_gif 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.sast_process import SASTProcessTest
from ppocr.data.det.east_process import EASTProcessTest from ppocr.data.det.east_process import EASTProcessTest
from ppocr.data.det.db_process import DBProcessTest from ppocr.data.det.db_process import DBProcessTest
from ppocr.postprocess.db_postprocess import DBPostProcess from ppocr.postprocess.db_postprocess import DBPostProcess
from ppocr.postprocess.east_postprocess import EASTPostPocess from ppocr.postprocess.east_postprocess import EASTPostPocess
from ppocr.postprocess.sast_postprocess import SASTPostProcess from ppocr.postprocess.sast_postprocess import SASTPostProcess
import copy
import numpy as np
import math
import time
import sys
class TextDetector(object): class TextDetector(object):
...@@ -135,8 +138,8 @@ class TextDetector(object): ...@@ -135,8 +138,8 @@ class TextDetector(object):
return None, 0 return None, 0
im = im.copy() im = im.copy()
starttime = time.time() starttime = time.time()
self.input_tensor.copy_from_cpu(im) im = fluid.core.PaddleTensor(im)
self.predictor.zero_copy_run() self.predictor.run([im])
outputs = [] outputs = []
for output_tensor in self.output_tensors: for output_tensor in self.output_tensors:
output = output_tensor.copy_to_cpu() output = output_tensor.copy_to_cpu()
......
...@@ -17,15 +17,18 @@ __dir__ = os.path.dirname(os.path.abspath(__file__)) ...@@ -17,15 +17,18 @@ __dir__ = os.path.dirname(os.path.abspath(__file__))
sys.path.append(__dir__) sys.path.append(__dir__)
sys.path.append(os.path.abspath(os.path.join(__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 cv2
import copy import copy
import numpy as np import numpy as np
import math import math
import time 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 from ppocr.utils.character import CharacterOps
...@@ -102,8 +105,8 @@ class TextRecognizer(object): ...@@ -102,8 +105,8 @@ class TextRecognizer(object):
norm_img_batch = np.concatenate(norm_img_batch) norm_img_batch = np.concatenate(norm_img_batch)
norm_img_batch = norm_img_batch.copy() norm_img_batch = norm_img_batch.copy()
starttime = time.time() starttime = time.time()
self.input_tensor.copy_from_cpu(norm_img_batch) norm_img_batch = fluid.core.PaddleTensor(norm_img_batch)
self.predictor.zero_copy_run() self.predictor.run([norm_img_batch])
if self.loss_type == "ctc": if self.loss_type == "ctc":
rec_idx_batch = self.output_tensors[0].copy_to_cpu() rec_idx_batch = self.output_tensors[0].copy_to_cpu()
......
...@@ -106,8 +106,7 @@ def create_predictor(args, mode): ...@@ -106,8 +106,7 @@ def create_predictor(args, mode):
config.disable_glog_info() config.disable_glog_info()
# use zero copy # use zero copy
config.delete_pass("conv_transpose_eltwiseadd_bn_fuse_pass") config.switch_use_feed_fetch_ops(True)
config.switch_use_feed_fetch_ops(False)
predictor = create_paddle_predictor(config) predictor = create_paddle_predictor(config)
input_names = predictor.get_input_names() input_names = predictor.get_input_names()
input_tensor = predictor.get_input_tensor(input_names[0]) input_tensor = predictor.get_input_tensor(input_names[0])
......
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