def _setup_cuda_marker(item):
"""Pytest marker to indicate number of NVIDIA GPUs required to run the test.
Tests can be annotated with this decorator (e.g., ``@pytest.mark.cuda``) to
declare that one NVIDIA GPU is required to run.
Tests can also be annotated as ``@pytest.mark.cuda(2)`` to declare number
of NVIDIA GPUs required to run. When running tests, if
``CHAINERX_TEST_CUDA_DEVICE_LIMIT`` environment variable is set to value
greater than or equals to 0, test cases that require GPUs more than the
limit will be skipped.
"""
cuda_marker = [m for m in item.iter_markers() if m.name == 'cuda']
if cuda_marker:
cuda_marker, = cuda_marker # asserts len == 1
required_num = cuda_marker.args[0] if cuda_marker.args else 1
if cuda_utils.get_cuda_limit() < required_num:
pytest.skip('{} NVIDIA GPUs required'.format(required_num))
def _setup_cuda_marker(item):
"""Pytest marker to indicate number of NVIDIA GPUs required to run the test.
Tests can be annotated with this decorator (e.g., ``@pytest.mark.cuda``) to
declare that one NVIDIA GPU is required to run.
Tests can also be annotated as ``@pytest.mark.cuda(2)`` to declare number
of NVIDIA GPUs required to run. When running tests, if
``CHAINERX_TEST_CUDA_DEVICE_LIMIT`` environment variable is set to value
greater than or equals to 0, test cases that require GPUs more than the
limit will be skipped.
"""
cuda_marker = [m for m in item.iter_markers() if m.name == 'cuda']
if len(cuda_marker) > 0:
cuda_marker, = cuda_marker # asserts len == 1
required_num = cuda_marker.args[0] if cuda_marker.args else 1
if cuda_utils.get_cuda_limit() < required_num:
pytest.skip('{} NVIDIA GPUs required'.format(required_num))
def device(request):
# A fixture to wrap a test with a device scope, given a device name.
# Device instance is passed to the test.
device_name = request.param
# Skip if the device is CUDA device and there's no sufficient CUDA devices.
cuda_device_count = _get_required_cuda_devices_from_device_name(
device_name)
if cuda_device_count > cuda_utils.get_cuda_limit():
pytest.skip()
device = chainerx.get_device(device_name)
device_scope = chainerx.using_device(device)
def finalize():
device_scope.__exit__()
request.addfinalizer(finalize)
device_scope.__enter__()
return device
def device(request):
# A fixture to wrap a test with a device scope, given a device name.
# Device instance is passed to the test.
device_name = request.param
# Skip if the device is CUDA device and there's no sufficient CUDA devices.
cuda_device_count = _get_required_cuda_devices_from_device_name(
device_name)
if cuda_device_count > cuda_utils.get_cuda_limit():
pytest.skip()
device = chainerx.get_device(device_name)
device_scope = chainerx.using_device(device)
def finalize():
device_scope.__exit__()
request.addfinalizer(finalize)
device_scope.__enter__()
return device
def pytest_ignore_collect(path, config):
if 0 == cuda_utils.get_cuda_limit():
if str(path).endswith('_cuda.rst'):
return True
return False
def _skip_if_no_cuda_device_available(device_name):
# Skip if the device is CUDA device and there's no sufficient CUDA devices.
cuda_device_count = _get_required_cuda_devices_from_device_name(
device_name)
if cuda_device_count > cuda_utils.get_cuda_limit():
pytest.skip()
