ultralytics 8.0.163 add new gpu-latest runner to CI actions (#4565)

Co-authored-by: pre-commit-ci[bot] <66853113+pre-commit-ci[bot]@users.noreply.github.com>
Co-authored-by: Maia Numerosky <17316848+maianumerosky@users.noreply.github.com>

tests/conftest.py

@@ -44,5 +44,5 @@ def pytest_terminal_summary(terminalreporter, exitstatus, config):
         Path(file).unlink(missing_ok=True)
 
     # Remove directories
-    for directory in ['.pytest_cache/', TMP]:
+    for directory in [ROOT / '../.pytest_cache', TMP]:
         shutil.rmtree(directory, ignore_errors=True)

tests/test_cli.py

@@ -63,7 +63,7 @@ def test_export(model, format):
 
 def test_rtdetr(task='detect', model='yolov8n-rtdetr.yaml', data='coco8.yaml'):
     # Warning: MUST use imgsz=640
-    run(f'yolo train {task} model={model} data={data} imgsz=640 epochs=1, cache = disk')  # add coma, space to args
+    run(f'yolo train {task} model={model} data={data} --imgsz= 640 epochs =1, cache = disk')  # add coma, spaces to args
     run(f"yolo predict {task} model={model} source={ASSETS / 'bus.jpg'} imgsz=640 save save_crop save_txt")
 
 

tests/test_cuda.py

@@ -0,0 +1,73 @@
+# Ultralytics YOLO 🚀, AGPL-3.0 license
+import subprocess
+from pathlib import Path
+
+import pytest
+import torch
+
+from ultralytics import YOLO
+from ultralytics.utils import ASSETS, SETTINGS
+
+CUDA_IS_AVAILABLE = torch.cuda.is_available()
+CUDA_DEVICE_COUNT = torch.cuda.device_count()
+
+WEIGHTS_DIR = Path(SETTINGS['weights_dir'])
+MODEL = WEIGHTS_DIR / 'path with spaces' / 'yolov8n.pt'  # test spaces in path
+DATA = 'coco8.yaml'
+
+
+def test_checks():
+    from ultralytics.utils.checks import cuda_device_count, cuda_is_available
+
+    assert cuda_device_count() == CUDA_DEVICE_COUNT
+    assert cuda_is_available() == CUDA_IS_AVAILABLE
+
+
+@pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
+def test_train():
+    YOLO(MODEL).train(data=DATA, imgsz=64, epochs=1, batch=-1, device=0)  # also test AutoBatch, requires imgsz>=64
+
+
+@pytest.mark.skipif(CUDA_DEVICE_COUNT < 2, reason=f'DDP is not available, {CUDA_DEVICE_COUNT} device(s) found')
+def test_train_ddp():
+    YOLO(MODEL).train(data=DATA, imgsz=64, epochs=1, device=[0, 1])  # requires imgsz>=64
+
+
+@pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
+def test_utils_benchmarks():
+    from ultralytics.utils.benchmarks import ProfileModels
+
+    YOLO(MODEL).export(format='engine', imgsz=32, dynamic=True, batch=1)  # pre-export engine model, auto-device
+    ProfileModels([MODEL], imgsz=32, half=False, min_time=1, num_timed_runs=3, num_warmup_runs=1).profile()
+
+
+@pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
+def test_predict_sam():
+    from ultralytics import SAM
+
+    # Load a model
+    model = SAM(WEIGHTS_DIR / 'sam_b.pt')
+
+    # Display model information (optional)
+    model.info()
+
+    # Run inference
+    model(ASSETS / 'bus.jpg', device=0)
+
+    # Run inference with bboxes prompt
+    model(ASSETS / 'zidane.jpg', bboxes=[439, 437, 524, 709], device=0)
+
+    # Run inference with points prompt
+    model(ASSETS / 'zidane.jpg', points=[900, 370], labels=[1], device=0)
+
+
+@pytest.mark.skipif(not CUDA_IS_AVAILABLE, reason='CUDA is not available')
+def test_model_tune():
+    subprocess.run('pip install ray[tune]'.split(), check=True)
+    YOLO('yolov8n-cls.yaml').tune(data='imagenet10',
+                                  grace_period=1,
+                                  max_samples=1,
+                                  imgsz=32,
+                                  epochs=1,
+                                  plots=False,
+                                  device='cpu')

tests/test_python.py

@@ -1,5 +1,6 @@
 # Ultralytics YOLO 🚀, AGPL-3.0 license
 
+import contextlib
 import shutil
 from copy import copy
 from pathlib import Path
@@ -38,6 +39,8 @@ def test_model_methods():
     model = model.load(MODEL)
     model.to('cpu')
     model.fuse()
+    model.clear_callback('on_train_start')
+    model._reset_callbacks()
 
     # Model properties
     _ = model.names
@@ -314,6 +317,15 @@ def test_events():
     events(cfg)
 
 
+def test_cfg_init():
+    from ultralytics.cfg import check_dict_alignment, copy_default_cfg, smart_value
+
+    with contextlib.suppress(SyntaxError):
+        check_dict_alignment({'a': 1}, {'b': 2})
+    copy_default_cfg()
+    [smart_value(x) for x in ['none', 'true', 'false']]
+
+
 def test_utils_init():
     from ultralytics.utils import get_git_branch, get_git_origin_url, get_ubuntu_version, is_github_actions_ci
 
@@ -354,6 +366,7 @@ def test_utils_torchutils():
     time_sync()
 
 
+@pytest.mark.skipif(not ONLINE, reason='environment is offline')
 def test_utils_downloads():
     from ultralytics.utils.downloads import get_google_drive_file_info
 
@@ -422,8 +435,11 @@ def test_nn_modules_block():
     BottleneckCSP(c1, c2)(x)
 
 
+@pytest.mark.skipif(not ONLINE, reason='environment is offline')
 def test_hub():
     from ultralytics.hub import export_fmts_hub, logout
+    from ultralytics.hub.utils import smart_request
 
     export_fmts_hub()
     logout()
+    smart_request('GET', 'http://github.com', progress=True)