def test_train(self, hub_model, benchmark):
try:
hub_model.set_train()
benchmark(hub_model.train)
benchmark.extra_info['machine_state'] = get_machine_state()
except NotImplementedError:
print('Method train is not implemented, skipping...')
def test_eval(self, hub_model, benchmark, pytestconfig):
try:
ng_flag = hub_model.eval_in_nograd(
) and not pytestconfig.getoption("disable_nograd")
with no_grad(ng_flag):
hub_model.set_eval()
benchmark(hub_model.eval)
benchmark.extra_info['machine_state'] = get_machine_state()
except NotImplementedError:
print('Method eval is not implemented, skipping...')
def test_train(self, model_path, device, compiler, benchmark):
try:
task = ModelTask(model_path)
if not task.model_details.exists:
return # Model is not supported.
task.make_model_instance(device=device, jit=(compiler == 'jit'))
task.set_train()
benchmark(task.train)
benchmark.extra_info['machine_state'] = get_machine_state()
except NotImplementedError:
print('Method eval is not implemented, skipping...')
def test_eval(self, model_path, device, compiler, benchmark, pytestconfig):
try:
task = ModelTask(model_path)
if not task.model_details.exists:
return # Model is not supported.
task.make_model_instance(device=device, jit=(compiler == 'jit'))
with task.no_grad(
disable_nograd=pytestconfig.getoption("disable_nograd")):
task.set_eval()
benchmark(task.eval)
benchmark.extra_info['machine_state'] = get_machine_state()
if pytestconfig.getoption("check_opt_vs_noopt_jit"):
task.check_opt_vs_noopt_jit()
except NotImplementedError:
print('Method eval is not implemented, skipping...')