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Make test.py run tests using the inductor backend #3

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Make test.py run tests using the inductor backend #3

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0eef8fb
Add inductor tests to test.py
gbeckenkamp Dec 16, 2024
0dd2b00
Add quantized back
gbeckenkamp Dec 17, 2024
0f4f627
Allow all tests to be validated for both backends
gbeckenkamp Dec 17, 2024
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26 changes: 16 additions & 10 deletions test.py
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Original file line number Diff line number Diff line change
Expand Up @@ -36,14 +36,17 @@ def tearDown(self):
gc.collect()


def _create_example_model_instance(task: ModelTask, device: str):
def _create_example_model_instance(task: ModelTask, device: str, mode: str):
skip = False
extra_args = ["--accuracy"]
if mode == "inductor":
extra_args.append("--inductor")
try:
task.make_model_instance(test="eval", device=device, extra_args=["--accuracy"])
task.make_model_instance(test="eval", device=device, extra_args=extra_args)
except NotImplementedError:
try:
task.make_model_instance(
test="train", device=device, extra_args=["--accuracy"]
test="train", device=device, extra_args=extra_args
)
except NotImplementedError:
skip = True
Expand All @@ -54,7 +57,7 @@ def _create_example_model_instance(task: ModelTask, device: str):
)


def _load_test(path, device):
def _load_test(path, device, mode):
model_name = os.path.basename(path)

def _skip_cuda_memory_check_p(metadata):
Expand All @@ -70,7 +73,7 @@ def example_fn(self):
skip=_skip_cuda_memory_check_p(metadata), assert_equal=self.assertEqual
):
try:
_create_example_model_instance(task, device)
_create_example_model_instance(task, device, mode)
accuracy = task.get_model_attribute("accuracy")
assert (
accuracy == "pass"
Expand All @@ -96,7 +99,7 @@ def train_fn(self):
):
try:
task.make_model_instance(
test="train", device=device, batch_size=batch_size
test="train", device=device, batch_size=batch_size, extra_args=["--inductor"] if mode == "inductor" else []
)
task.invoke()
task.check_details_train(device=device, md=metadata)
Expand All @@ -119,7 +122,7 @@ def eval_fn(self):
):
try:
task.make_model_instance(
test="eval", device=device, batch_size=batch_size
test="eval", device=device, batch_size=batch_size, extra_args=["--inductor"] if mode == "inductor" else []
)
task.invoke()
task.check_details_eval(device=device, md=metadata)
Expand All @@ -136,7 +139,7 @@ def check_device_fn(self):
skip=_skip_cuda_memory_check_p(metadata), assert_equal=self.assertEqual
):
try:
task.make_model_instance(test="eval", device=device)
task.make_model_instance(test="eval", device=device, extra_args=["--inductor"] if mode == "inductor" else [])
task.check_device()
task.del_model_instance()
except NotImplementedError as e:
Expand All @@ -152,9 +155,10 @@ def check_device_fn(self):
# set exclude list based on metadata
setattr(
TestBenchmark,
f"test_{model_name}_{fn_name}_{device}",
f"test_{model_name}_{fn_name}_{device}_{mode}",
(
unittest.skipIf(
# This is expecting that models will never be skipped just based on backend, just on eval or train functions being implemented
skip_by_metadata(
test=fn_name, device=device, extra_args=[], metadata=metadata
),
Expand All @@ -165,6 +169,7 @@ def check_device_fn(self):


def _load_tests():
modes = ["eager", "inductor"]
devices = ["cpu"]
if torch.cuda.is_available():
devices.append("cuda")
Expand All @@ -181,7 +186,8 @@ def _load_tests():
if "quantized" in path:
continue
for device in devices:
_load_test(path, device)
for mode in modes:
_load_test(path, device, mode)


_load_tests()
Expand Down