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Azure-Pipeline: Remove redundant print information #134

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Merged
chensuyue merged 2 commits into from
Nov 22, 2022
Merged

Azure-Pipeline: Remove redundant print information #134

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c44d58c
Remove redundant print information
XuehaoSun Nov 22, 2022
5fe5ea8
Round up to 3 decimal places
XuehaoSun Nov 22, 2022
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8 changes: 3 additions & 5 deletions .azure-pipelines/scripts/models/collect_log_model.py
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Original file line number Diff line number Diff line change
Expand Up @@ -12,8 +12,7 @@
parser.add_argument("--stage", type=str, default="collect_log")
parser.add_argument("--gap", type=float, default=0.05)
args = parser.parse_args()
print('===== collecting log model =======')
print('build_id: '+args.build_id)
print('====== collecting model test log =======')
OS='linux'
PLATFORM='icx'
URL ='https://dev.azure.com/lpot-inc/neural-compressor/_build/results?buildId='+args.build_id+'&view=artifacts&pathAsName=false&type=publishedArtifacts'
Expand Down Expand Up @@ -79,7 +78,6 @@ def get_model_benchmark_dict_results():
for root, dirs, files in os.walk(args.logs_dir):
for name in files:
file_name = os.path.join(root, name)
print(file_name)
if "performance-" + precision in name:
for line in open(file_name, "r"):
result = parse_perf_line(line)
Expand Down Expand Up @@ -222,14 +220,14 @@ def check_status(precision, precision_upper, check_accuracy=False):
performance_result = get_model_benchmark_dict_results()
current_performance = performance_result.get(precision).get("Value")
refer_performance = refer.get(f"{precision_upper}_Performance")
print(f"current_performance_data = {current_performance}, refer_performance_data = {refer_performance}")
print(f"current_performance_data = {current_performance:.3f}, refer_performance_data = {refer_performance:.3f}")
assert abs(current_performance - refer_performance) / refer_performance <= args.gap

if check_accuracy:
_, accuracy_result = get_model_tuning_dict_results()
current_accuracy = accuracy_result.get(precision).get("Value")
refer_accuracy = refer.get(f"{precision_upper}_Accuracy")
print(f"current_accuracy_data = {current_accuracy}, refer_accuarcy_data = {refer_accuracy}")
print(f"current_accuracy_data = {current_accuracy:.3f}, refer_accuarcy_data = {refer_accuracy:.3f}")
assert abs(current_accuracy - refer_accuracy) / refer_accuracy <= 0.05


Expand Down