forked from mindspore-Ecosystem/mindspore
63 lines
3.0 KiB
Python
63 lines
3.0 KiB
Python
# Copyright 2021 Huawei Technologies Co., Ltd
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#
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# Licensed under the Apache License, Version 2.0 (the "License");
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# you may not use this file except in compliance with the License.
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# You may obtain a copy of the License at
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#
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# http://www.apache.org/licenses/LICENSE-2.0
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#
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# Unless required by applicable law or agreed to in writing, software
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# distributed under the License is distributed on an "AS IS" BASIS,
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# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
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# See the License for the specific language governing permissions and
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# limitations under the License.
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# ============================================================================
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import os
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import pytest
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from tests.st.model_zoo_tests import utils
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@pytest.mark.level1
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@pytest.mark.platform_x86_ascend_training
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@pytest.mark.platform_arm_ascend_training
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@pytest.mark.env_single
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def test_center_net():
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cur_path = os.path.dirname(os.path.abspath(__file__))
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model_path = "{}/../../../../tests/models/research/cv".format(cur_path)
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model_name = "centernet"
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utils.copy_files(model_path, cur_path, model_name)
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cur_model_path = os.path.join(cur_path, model_name)
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old_list = ['new_repeat_count, dataset', 'args_opt.data_sink_steps']
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new_list = ['5, dataset', '20']
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utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, "train.py"))
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old_list = ["device_ips = {}", "device_ip.strip()",
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"rank_size = 0", "this_server = server",
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"this_server\\[\\\"device\\\"\\]",
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"instance\\[\\\"device_id\\\"\\]"]
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new_list = ["device_ips = {}\\n '''", "device_ip.strip()\\n '''",
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"rank_size = 8\\n this_server = hccl_config[\\\"group_list\\\"][0]\\n '''",
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"this_server = server\\n '''",
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"this_server[\\\"instance_list\\\"]",
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"instance[\\\"devices\\\"][0][\\\"device_id\\\"]"]
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generator_cmd_file = "scripts/ascend_distributed_launcher/get_distribute_train_cmd.py"
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utils.exec_sed_command(old_list, new_list, os.path.join(cur_model_path, generator_cmd_file))
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dataset_path = os.path.join(utils.data_root, "coco/coco2017/mindrecord_train/centernet_mindrecord")
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exec_network_shell = "cd centernet; bash scripts/run_distributed_train_ascend.sh {0} {1}"\
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.format(dataset_path, utils.rank_table_path)
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os.system(exec_network_shell)
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cmd = "ps -ef |grep train.py | grep coco | grep -v grep"
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ret = utils.process_check(120, cmd)
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assert ret
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log_file = os.path.join(cur_model_path, "LOG{}/training_log.txt")
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for i in range(8):
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per_step_time = utils.get_perf_data(log_file.format(i))
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assert per_step_time < 435
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loss_list = []
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for i in range(8):
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loss_cmd = "grep -nr \"outputs are\" {} | awk '{{print $14}}' | awk -F\")\" '{{print $1}}'"\
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.format(log_file.format(i))
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loss = utils.get_loss_data_list(log_file.format(i), cmd=loss_cmd)
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loss_list.append(loss[-1])
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assert sum(loss_list) / len(loss_list) < 58.8
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