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!15830 add modelzoo network yolov3-darknet testcase 

From: @anzhengqi
Reviewed-by: @liucunwei,@jonyguo
Signed-off-by: @liucunwei
This commit is contained in:
mindspore-ci-bot 2021-04-29 14:52:23 +08:00 committed by Gitee
parent b431fab4ec b7eb95a167
commit b5555f00de
1 changed files with 39 additions and 0 deletions
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39
tests/st/model_zoo_tests/yolov3_darknet53/test_yolov3_darknet53.py
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@ -38,6 +38,7 @@ from src.lr_scheduler import warmup_cosine_annealing_lr
from src.yolo_dataset import create_yolo_dataset
from src.initializer import default_recurisive_init
from src.config import ConfigYOLOV3DarkNet53
from tests.st.model_zoo_tests import utils
np.random.seed(1)
def get_lr(learning_rate, start_step, global_step, decay_step, decay_rate, steps=False):
@ -209,3 +210,41 @@ def test_yolov3_darknet53():
print('time_used_per_epoch:{}'.format(time_used_per_epoch))
assert time_used_per_epoch < export_time_used
print('==========test case passed===========')
@pytest.mark.level0
@pytest.mark.platform_x86_ascend_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.env_single
def test_yolov3_darknet_8p():
cur_path = os.path.dirname(os.path.abspath(__file__))
model_path = "{}/../../../../model_zoo/official/cv".format(cur_path)
model_name = "yolov3_darknet53"
dataset_path = os.path.join(utils.data_root, "coco/coco2014/")
ckpt_path = os.path.join(utils.ckpt_root, "yolov3_darknet/yolov3_darknet53_pretrain.ckpt")
utils.copy_files(model_path, cur_path, model_name)
cur_model_path = os.path.join(cur_path, model_name)
train_file = os.path.join(cur_model_path, "train.py")
old_list = ["--lr_scheduler=cosine_annealing"]
new_list = ["--lr_scheduler=cosine_annealing --training_shape=416"]
utils.exec_sed_command(old_list, new_list,
os.path.join(cur_model_path, "scripts/run_distribute_train.sh"))
old_list = ["default=100", "max_epoch=args.max_epoch"]
new_list = ["default=10", "max_epoch=1"]
utils.exec_sed_command(old_list, new_list, train_file)
old_list = ["sampler=distributed_sampler"]
new_list = ["sampler=distributed_sampler, num_samples=100*batch_size"]
utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/yolo_dataset.py"))
exec_network_shell = "cd yolov3_darknet53/scripts; bash run_distribute_train.sh {0} {1} {2}"\
.format(dataset_path, ckpt_path, utils.rank_table_path)
os.system(exec_network_shell)
cmd = "ps -ef | grep python | grep train.py | grep -v grep"
ret = utils.process_check(120, cmd)
assert ret
train_log_file = os.path.join(cur_path, "yolov3_darknet53/scripts/train_parallel0/log.txt")
pattern1 = r", *([\d\.]+) imgs/sec"
pattern2 = r"loss:*([\d\.]+),"
fps_list = utils.parse_log_file(pattern1, train_log_file)[1:]
assert sum(fps_list) / len(fps_list) > 480
loss_list = utils.parse_log_file(pattern2, train_log_file)
assert loss_list[-1] < 280