Add --hard-fail argument to benchmarks for CI errors (#8513)

* Add `--hard-fail` list argument to benchmarks for CI

Will cause CI to fail on a benchmark failure for given indices.

* Update ci-testing.yml

* Attempt Failure (CI should fail)

* Update benchmarks.py

* Update export.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update benchmarks.py

* [pre-commit.ci] auto fixes from pre-commit.com hooks

for more information, see https://pre-commit.ci

* Update ci-testing.yml

* Update benchmarks.py

* Update benchmarks.py

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
This commit is contained in:
Glenn Jocherandpre-commit-ci[bot] authored and GitHub committed 2022-07-07 23:41:34 +02:00
1 parent 39d7a93619
commit 3e54651fca
3 files changed
+25 -17

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@@ -26,6 +26,7 @@ Usage:
"""
import argparse
import platform
import sys
import time
from pathlib import Path
@@ -54,14 +55,17 @@ def run(
half=False, # use FP16 half-precision inference
test=False, # test exports only
pt_only=False, # test PyTorch only
hard_fail=False, # throw error on benchmark failure
):
y, t = [], time.time()
device = select_device(device)
for i, (name, f, suffix, gpu) in export.export_formats().iterrows(): # index, (name, file, suffix, gpu-capable)
for i, (name, f, suffix, cpu, gpu) in export.export_formats().iterrows(): # index, (name, file, suffix, CPU, GPU)
try:
assert i != 9, 'Edge TPU not supported'
assert i != 10, 'TF.js not supported'
if device.type != 'cpu':
assert i not in (9, 10), f'{name} inference not supported' # Edge TPU and TF.js are unsupported
assert i != 5 or platform.system() == 'Darwin', f'{name} inference only supported on macOS>=10.13'
if 'cpu' in device.type:
assert cpu, f'{name} inference not supported on CPU'
if 'cuda' in device.type:
assert gpu, f'{name} inference not supported on GPU'
# Export
@@ -77,6 +81,8 @@ def run(
speeds = result[2] # times (preprocess, inference, postprocess)
y.append([name, round(file_size(w), 1), round(metrics[3], 4), round(speeds[1], 2)]) # MB, mAP, t_inference
except Exception as e:
if hard_fail:
assert type(e) is AssertionError, f'Benchmark --hard-fail for {name}: {e}'
LOGGER.warning(f'WARNING: Benchmark failure for {name}: {e}')
y.append([name, None, None, None]) # mAP, t_inference
if pt_only and i == 0:
@@ -102,6 +108,7 @@ def test(
half=False, # use FP16 half-precision inference
test=False, # test exports only
pt_only=False, # test PyTorch only
hard_fail=False, # throw error on benchmark failure
):
y, t = [], time.time()
device = select_device(device)
@@ -134,6 +141,7 @@ def parse_opt():
parser.add_argument('--half', action='store_true', help='use FP16 half-precision inference')
parser.add_argument('--test', action='store_true', help='test exports only')
parser.add_argument('--pt-only', action='store_true', help='test PyTorch only')
parser.add_argument('--hard-fail', action='store_true', help='throw error on benchmark failure')
opt = parser.parse_args()
opt.data = check_yaml(opt.data) # check YAML
print_args(vars(opt))