!47567 Add resnet50+boost st test case in GE process

Merge pull request !47567 from archer2049/master
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i-robot 2023-01-13 06:56:43 +00:00 committed by Gitee
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# Copyright 2023 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
import numpy as np
import mindspore as ms
from tests.st.model_zoo_tests import utils
ms.set_seed(1)
np.random.seed(1)
@pytest.mark.level0
@pytest.mark.platform_x86_ascend_training
@pytest.mark.platform_arm_ascend_training
@pytest.mark.env_single
def test_ge_resnet50_boost_imagenet2012_ascend():
"""
Feature: Resnet50 boost in ge process
Description: test_ge_resnet50_imagenet2012_ascend
Expectation: Success
"""
os.environ['MS_ENABLE_GE'] = '1'
os.environ['MS_GE_TRAIN'] = '1'
current_path = os.path.dirname(os.path.abspath(__file__))
model_path = "{}/../../../../tests/models/official/cv".format(current_path)
model = "resnet"
utils.copy_files(model_path, current_path, model)
cur_model_path = os.path.join(current_path, "resnet")
list_old = ["config.epoch_size - config.pretrain_epoch_size", "=dataset.get_dataset_size()", "=dataset_sink_mode",
"\\\"total_steps\\\""]
list_new = ["1", "=1", "=True", r"\\\"param_groups\\\"\: 2, \\\"total_steps\\\""]
utils.exec_sed_command(list_old, list_new, os.path.join(cur_model_path, "train.py"))
dataset = os.path.join(utils.data_root, "imagenet/imagenet_original/train")
# Do not execute ckpt graph
config = os.path.join(cur_model_path, "config", "resnet50_imagenet2012_Boost_config.yaml")
list_old = ["save_checkpoint: True"]
list_new = ["save_checkpoint: False"]
utils.exec_sed_command(list_old, list_new, config)
exec_network_shell = "cd {}/resnet/scripts; bash run_standalone_train.sh {} {}" \
.format(current_path, dataset, config)
os.system(exec_network_shell)
cmd = "ps -ef | grep python | grep train.py | grep -v grep"
result = utils.process_check(120, cmd)
assert result
log_file = os.path.join(cur_model_path, "scripts/train/log")
loss_list = utils.get_loss_data_list(log_file)
assert round(loss_list[-1]) <= 7