Skip to content

[tests] device_map tests for all models. #11708

New issue

Have a question about this project? Sign up for a free GitHub account to open an issue and contact its maintainers and the community.

Sign up for GitHub

By clicking “Sign up for GitHub”, you agree to our terms of service and privacy statement. We’ll occasionally send you account related emails.

Already on GitHub? Sign in to your account

Open
wants to merge 2 commits into
base: main
Choose a base branch
from
Open

[tests] device_map tests for all models. #11708

Show file tree
Hide file tree
Changes from all commits
Commits
Show all changes
2 commits
Select commit Hold shift + click to select a range
a906f77
device_map tests for all models.
sayakpaul Jun 13, 2025
fdb56cf
updates
sayakpaul Jun 13, 2025
File filter

Filter by extension

Filter by extension
Conversations
Failed to load comments.
Loading
Jump to
Jump to file
Failed to load files.
Loading
Diff view
Diff view
38 changes: 38 additions & 0 deletions tests/models/test_modeling_common.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -1736,6 +1736,44 @@ def test_auto_model(self, expected_max_diff=5e-5):
f"AutoModel forward pass diff: {max_diff} exceeds threshold {expected_max_diff}",
)

@parameterized.expand(
[
(-1, "You can't pass device_map as a negative int"),
("foo", "When passing device_map as a string, the value needs to be a device name"),
]
)
def test_wrong_device_map_raises_error(self, device_map, msg_substring):
init_dict, _ = self.prepare_init_args_and_inputs_for_common()
model = self.model_class(**init_dict)
with tempfile.TemporaryDirectory() as tmpdir:
model.save_pretrained(tmpdir)
with self.assertRaises(ValueError) as err_ctx:
_ = self.model_class.from_pretrained(tmpdir, device_map=device_map)

assert msg_substring in str(err_ctx.exception)

@parameterized.expand([0, "cuda", torch.device("cuda"), torch.device("cuda:0")])
@require_torch_gpu
def test_passing_non_dict_device_map_works(self, device_map):
init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
model = self.model_class(**init_dict).eval()
with tempfile.TemporaryDirectory() as tmpdir:
model.save_pretrained(tmpdir)
loaded_model = self.model_class.from_pretrained(tmpdir, device_map=device_map)
_ = loaded_model(**inputs_dict)

@parameterized.expand([("", "cuda"), ("", torch.device("cuda"))])
@require_torch_gpu
def test_passing_dict_device_map_works(self, name, device_map):
# There are other valid dict-based `device_map` values too. It's best to refer to
# the docs for those: https://huggingface.co/docs/accelerate/en/concept_guides/big_model_inference#the-devicemap.
init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
model = self.model_class(**init_dict).eval()
with tempfile.TemporaryDirectory() as tmpdir:
model.save_pretrained(tmpdir)
loaded_model = self.model_class.from_pretrained(tmpdir, device_map=device_map)
_ = loaded_model(**inputs_dict)


@is_staging_test
class ModelPushToHubTester(unittest.TestCase):
Expand Down
37 changes: 0 additions & 37 deletions tests/models/unets/test_models_unet_2d_condition.py
View file
Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -46,7 +46,6 @@
require_peft_backend,
require_torch_accelerator,
require_torch_accelerator_with_fp16,
require_torch_gpu,
skip_mps,
slow,
torch_all_close,
Expand Down Expand Up @@ -1084,42 +1083,6 @@ def test_load_sharded_checkpoint_device_map_from_hub_local_subfolder(self):
assert loaded_model
assert new_output.sample.shape == (4, 4, 16, 16)

@parameterized.expand(
[
(-1, "You can't pass device_map as a negative int"),
("foo", "When passing device_map as a string, the value needs to be a device name"),
]
)
def test_wrong_device_map_raises_error(self, device_map, msg_substring):
with self.assertRaises(ValueError) as err_ctx:
_ = self.model_class.from_pretrained(
"hf-internal-testing/unet2d-sharded-dummy-subfolder", subfolder="unet", device_map=device_map
)

assert msg_substring in str(err_ctx.exception)

@parameterized.expand([0, "cuda", torch.device("cuda"), torch.device("cuda:0")])
@require_torch_gpu
def test_passing_non_dict_device_map_works(self, device_map):
_, inputs_dict = self.prepare_init_args_and_inputs_for_common()
loaded_model = self.model_class.from_pretrained(
"hf-internal-testing/unet2d-sharded-dummy-subfolder", subfolder="unet", device_map=device_map
)
output = loaded_model(**inputs_dict)
assert output.sample.shape == (4, 4, 16, 16)

@parameterized.expand([("", "cuda"), ("", torch.device("cuda"))])
@require_torch_gpu
def test_passing_dict_device_map_works(self, name, device_map):
# There are other valid dict-based `device_map` values too. It's best to refer to
# the docs for those: https://huggingface.co/docs/accelerate/en/concept_guides/big_model_inference#the-devicemap.
_, inputs_dict = self.prepare_init_args_and_inputs_for_common()
loaded_model = self.model_class.from_pretrained(
"hf-internal-testing/unet2d-sharded-dummy-subfolder", subfolder="unet", device_map={name: device_map}
)
output = loaded_model(**inputs_dict)
assert output.sample.shape == (4, 4, 16, 16)

@require_peft_backend
def test_load_attn_procs_raise_warning(self):
init_dict, inputs_dict = self.prepare_init_args_and_inputs_for_common()
Expand Down