add modelzoo network bgcf testcase

tests/st/model_zoo_tests/bgcf/test_BGCF_amazon_beauty.py

@@ -0,0 +1,72 @@
+# 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_onecard
+def test_BGCF_amazon_beauty():
+    cur_path = os.path.dirname(os.path.abspath(__file__))
+    model_path = "{}/../../../../model_zoo/official/gnn".format(cur_path)
+    model_name = "bgcf"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+
+    old_list = ["--datapath=../data_mr"]
+    new_list = ["--datapath={}".format(os.path.join(utils.data_root, "amazon_beauty/mindrecord_train"))]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "scripts/run_train_ascend.sh"))
+    old_list = ["default=600,"]
+    new_list = ["default=50,"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "src/config.py"))
+    old_list = ["context.set_context(device_id=int(parser.device))"]
+    new_list = ["context.set_context()"]
+    utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
+    exec_network_shell = "cd {}/scripts; bash run_train_ascend.sh".format(model_name)
+    ret = os.system(exec_network_shell)
+    assert ret == 0
+
+    cmd = "ps -ef|grep python |grep train.py|grep amazon_beauty|grep -v grep"
+    ret = utils.process_check(300, cmd)
+    assert ret
+
+    log_file = os.path.join(cur_model_path, "scripts/train/log")
+    pattern1 = r"loss ([\d\.\+]+)\,"
+    loss_list = utils.parse_log_file(pattern1, log_file)
+    loss_list = loss_list[-5:]
+    print("last 5 epoch average loss is", sum(loss_list) / len(loss_list))
+    assert sum(loss_list) / len(loss_list) < 6400
+
+    pattern1 = r"cost:([\d\.\+]+)"
+    epoch_time_list = utils.parse_log_file(pattern1, log_file)[1:]
+    print("per epoch time:", sum(epoch_time_list) / len(epoch_time_list))
+    assert sum(epoch_time_list) / len(epoch_time_list) < 1.9
+
+
+def test_bgcf_export_mindir():
+    cur_path = os.getcwd()
+    model_path = "{}/../../../../model_zoo/official/gnn".format(cur_path)
+    model_name = "bgcf"
+    utils.copy_files(model_path, cur_path, model_name)
+    cur_model_path = os.path.join(cur_path, model_name)
+
+    ckpt_path = os.path.join(utils.ckpt_root, "bgcf/bgcf_trained.ckpt")
+    exec_export_shell = "cd {}; python export.py --ckpt_file={} --file_format=MINDIR".format(model_name, ckpt_path)
+    os.system(exec_export_shell)
+    assert os.path.exists(os.path.join(cur_model_path, "{}.mindir".format(model_name)))

tests/st/model_zoo_tests/utils.py

@@ -14,7 +14,7 @@ from mindspore import log as logger
 
 rank_table_path = "/home/workspace/mindspore_config/hccl/rank_table_8p.json"
 data_root = "/home/workspace/mindspore_dataset/"
-ckpt_root = "/home/workspace/mindspore_ckpt/"
+ckpt_root = "/home/workspace/mindspore_dataset/checkpoint"
 cur_path = os.path.split(os.path.realpath(__file__))[0]
 geir_root = os.path.join(cur_path, "mindspore_geir")
 arm_main_path = os.path.join(cur_path, "mindir_310infer_exe")