116 lines
3.8 KiB
Python
Executable File
116 lines
3.8 KiB
Python
Executable File
# Copyright (c) 2020 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.
|
|
|
|
from __future__ import absolute_import
|
|
from __future__ import division
|
|
from __future__ import print_function
|
|
|
|
import os
|
|
import sys
|
|
|
|
__dir__ = os.path.dirname(os.path.abspath(__file__))
|
|
sys.path.append(__dir__)
|
|
sys.path.append(os.path.abspath(os.path.join(__dir__, '..')))
|
|
|
|
import yaml
|
|
import paddle
|
|
import paddle.distributed as dist
|
|
|
|
paddle.seed(2)
|
|
|
|
from ppocr.data import build_dataloader
|
|
from ppocr.modeling.architectures import build_model
|
|
from ppocr.losses import build_loss
|
|
from ppocr.optimizer import build_optimizer
|
|
from ppocr.postprocess import build_post_process
|
|
from ppocr.metrics import build_metric
|
|
from ppocr.utils.save_load import init_model
|
|
import tools.program as program
|
|
|
|
dist.get_world_size()
|
|
|
|
|
|
def main(config, device, logger, vdl_writer):
|
|
# init dist environment
|
|
if config['Global']['distributed']:
|
|
dist.init_parallel_env()
|
|
|
|
global_config = config['Global']
|
|
|
|
# build dataloader
|
|
train_dataloader = build_dataloader(config, 'Train', device, logger)
|
|
if config['Eval']:
|
|
valid_dataloader = build_dataloader(config, 'Eval', device, logger)
|
|
else:
|
|
valid_dataloader = None
|
|
|
|
# build post process
|
|
post_process_class = build_post_process(config['PostProcess'],
|
|
global_config)
|
|
|
|
# build model
|
|
# for rec algorithm
|
|
if hasattr(post_process_class, 'character'):
|
|
char_num = len(getattr(post_process_class, 'character'))
|
|
config['Architecture']["Head"]['out_channels'] = char_num
|
|
model = build_model(config['Architecture'])
|
|
if config['Global']['distributed']:
|
|
model = paddle.DataParallel(model)
|
|
|
|
# build loss
|
|
loss_class = build_loss(config['Loss'])
|
|
|
|
# build optim
|
|
optimizer, lr_scheduler = build_optimizer(
|
|
config['Optimizer'],
|
|
epochs=config['Global']['epoch_num'],
|
|
step_each_epoch=len(train_dataloader),
|
|
parameters=model.parameters())
|
|
|
|
# build metric
|
|
eval_class = build_metric(config['Metric'])
|
|
# load pretrain model
|
|
pre_best_model_dict = init_model(config, model, logger, optimizer)
|
|
|
|
logger.info('train dataloader has {} iters, valid dataloader has {} iters'.
|
|
format(len(train_dataloader), len(valid_dataloader)))
|
|
# start train
|
|
program.train(config, train_dataloader, valid_dataloader, device, model,
|
|
loss_class, optimizer, lr_scheduler, post_process_class,
|
|
eval_class, pre_best_model_dict, logger, vdl_writer)
|
|
|
|
|
|
def test_reader(config, device, logger):
|
|
loader = build_dataloader(config, 'Train', device, logger)
|
|
import time
|
|
starttime = time.time()
|
|
count = 0
|
|
try:
|
|
for data in loader():
|
|
count += 1
|
|
if count % 1 == 0:
|
|
batch_time = time.time() - starttime
|
|
starttime = time.time()
|
|
logger.info("reader: {}, {}, {}".format(
|
|
count, len(data[0]), batch_time))
|
|
except Exception as e:
|
|
logger.info(e)
|
|
logger.info("finish reader: {}, Success!".format(count))
|
|
|
|
|
|
if __name__ == '__main__':
|
|
config, device, logger, vdl_writer = program.preprocess()
|
|
main(config, device, logger, vdl_writer)
|
|
# test_reader(config, device, logger)
|