!15827 add modelzoo network ssd-mobilenet testcase

From: @anzhengqi
Reviewed-by: @c_34,@jonyguo
Signed-off-by: @c_34

tests/st/model_zoo_tests/ssd_mobilenet_fpn/test_ssd_modelnet_fpn.py

@@ -0,0 +1,64 @@
+# 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.level0
+@pytest.mark.platform_x86_ascend_training
+@pytest.mark.platform_arm_ascend_training
+@pytest.mark.env_single
+def test_SSD_mobilenet_v1_fpn_coco2017():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/official/cv".format(cur_path)
+    model_name = "ssd"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+
+    old_list = ["/data/MindRecord_COCO",
+                "/ckpt/mobilenet_v1.ckpt",
+                "/data/coco2017"]
+    new_list = [os.path.join(utils.data_root, "coco/coco2017/mindrecord_train/ssd_mindrecord"),
+                os.path.join(utils.ckpt_root, "ssd_mobilenet_v1/mobilenet-v1.ckpt"),
+                os.path.join(utils.data_root, "coco/coco2017")]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/config_ssd_mobilenet_v1_fpn.py"))
+    old_list = ["ssd300"]
+    new_list = ["ssd_mobilenet_v1_fpn"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/config.py"))
+    old_list = ["args_opt.epoch_size", "dataset_sink_mode=dataset_sink_mode"]
+    new_list = ["5", "dataset_sink_mode=dataset_sink_mode, sink_size=100"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
+
+    exec_network_shell = "cd {0}; sh -x scripts/run_distribute_train.sh 8 {1} 0.2 coco {2}"\
+        .format(model_name, 60, utils.rank_table_path)
+    os.system(exec_network_shell)
+    cmd = "ps -ef | grep train.py | grep coco | grep device_num | grep device_id | grep -v grep"
+    ret = utils.process_check(120, cmd)
+    assert ret
+
+    log_file = os.path.join(cur_model_path, "LOG{}/log.txt")
+    for i in range(8):
+        per_step_time = utils.get_perf_data(log_file.format(i))
+        print("per_step_time is", per_step_time)
+        assert per_step_time < 545
+    loss_list = []
+    for i in range(8):
+        loss = utils.get_loss_data_list(log_file.format(i))
+        print("loss is", loss[-1])
+        loss_list.append(loss[-1])
+    assert sum(loss_list) / len(loss_list) < 2.72