forked from Deci-AI/super-gradients
-
Notifications
You must be signed in to change notification settings - Fork 0
/
Makefile
35 lines (27 loc) · 2.4 KB
/
Makefile
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
unit_tests:
python -m unittest tests/deci_core_unit_test_suite_runner.py
integration_tests:
python -m unittest tests/deci_core_integration_test_suite_runner.py
yolo_nas_integration_tests:
python -m unittest tests/integration_tests/yolo_nas_integration_test.py
recipe_accuracy_tests:
python src/super_gradients/train_from_recipe.py --config-name=coco2017_pose_dekr_w32_no_dc experiment_name=shortened_coco2017_pose_dekr_w32_ap_test epochs=1 batch_size=4 val_batch_size=8 training_hyperparams.lr_warmup_steps=0 training_hyperparams.average_best_models=False training_hyperparams.max_train_batches=1000 training_hyperparams.max_valid_batches=100 multi_gpu=DDP num_gpus=4
python src/super_gradients/train_from_recipe.py --config-name=cifar10_resnet experiment_name=shortened_cifar10_resnet_accuracy_test epochs=100 training_hyperparams.average_best_models=False multi_gpu=DDP num_gpus=4
python src/super_gradients/train_from_recipe.py --config-name=coco2017_yolox experiment_name=shortened_coco2017_yolox_n_map_test epochs=10 architecture=yolox_n training_hyperparams.loss=YoloXFastDetectionLoss training_hyperparams.average_best_models=False multi_gpu=DDP num_gpus=4
python src/super_gradients/train_from_recipe.py --config-name=cityscapes_regseg48 experiment_name=shortened_cityscapes_regseg48_iou_test epochs=10 training_hyperparams.average_best_models=False multi_gpu=DDP num_gpus=4
python src/super_gradients/examples/convert_recipe_example/convert_recipe_example.py --config-name=cifar10_conversion_params experiment_name=shortened_cifar10_resnet_accuracy_test
coverage run --source=super_gradients -m unittest tests/deci_core_recipe_test_suite_runner.py
sweeper_test:
python -m super_gradients.train_from_recipe -m --config-name=cifar10_resnet \
ckpt_root_dir=$$PWD \
experiment_name=sweep_cifar10 \
training_hyperparams.max_epochs=1 \
training_hyperparams.initial_lr=0.001,0.01
# Make sure that experiment_dir includes $$expected_num_dir subdirectories. If not, fail
subdir_count=$$(find "$$PWD/sweep_cifar10" -mindepth 1 -maxdepth 1 -type d | wc -l); \
if [ "$$subdir_count" -ne 2 ]; then \
echo "Error: $$PWD/sweep_cifar10 should include 2 subdirectories but includes $$subdir_count."; \
exit 1; \
fi
examples_to_docs:
jupyter nbconvert --to markdown --output-dir="documentation/source/" --execute src/super_gradients/examples/model_export/models_export.ipynb