add modelzoo network face_detection testcase

tests/st/model_zoo_tests/face_detection/test_FaceDetection_WIDER.py

@@ -0,0 +1,55 @@
+# Copyright 2021 Huawei Technologies Co., Ltd
+#
+# 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 os
+import pytest
+
+from tests.st.model_zoo_tests import utils
+
+
+@pytest.mark.level1
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_onecard
+def test_FaceDetection_WIDER():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/research/cv".format(cur_path)
+    model_name = "FaceDetection"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+    old_list = ["'max_epoch': 2500,"]
+    new_list = ["'max_epoch': 1,"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/config.py"))
+    dataset_path = os.path.join(utils.data_root, "widerface/mindrecord_train/data.mindrecord")
+    device_id = int(os.environ.get("DEVICE_ID", "0"))
+    model_train_command = "cd {}/scripts;sh run_standalone_train.sh Ascend {} {}"\
+        .format(model_name, dataset_path, device_id)
+    ret = os.system(model_train_command)
+    assert ret == 0
+
+    cmd = "ps -ef | grep train.py | grep Ascend | grep -v grep"
+    ret = utils.process_check(150, cmd)
+    assert ret
+
+    log_file = os.path.join(cur_model_path, "scripts/device{}/train.log".format(device_id))
+    pattern1 = r"loss\[([\d\.\+]+)\]"
+    loss_list = utils.parse_log_file(pattern1, log_file)
+    loss_list = loss_list[-10:]
+    print("loss_list is", loss_list)
+    assert sum(loss_list) / len(loss_list) < 12000
+    pattern1 = r"\]\, ([\d\.\+]+) imgs\/sec"
+    imgs_sec_list = utils.parse_log_file(pattern1, log_file)
+    imgs_sec_list = imgs_sec_list[1:]
+    print("imgs_sec_list is", imgs_sec_list)
+    assert sum(imgs_sec_list) / len(imgs_sec_list) > 60