[Core] [Offloading] Enable saving offloaded models with multiple shared tensor groups (#39263)

* fix counting meta tensors, fix onloading meta tensors

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

* remove unrelated fix

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

* add test

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>

---------

Signed-off-by: Kyle Sayers <kylesayrs@gmail.com>
This commit is contained in:
Kyle Sayers
2025-07-10 12:33:30 -04:00
committed by GitHub
parent df49b399dc
commit bdc8028cb3
2 changed files with 39 additions and 18 deletions

View File

@@ -1187,6 +1187,29 @@ class ModelUtilsTest(TestCasePlus):
torch.testing.assert_close(output, presaved_output, rtol=1e-4, atol=1e-4)
torch.testing.assert_close(presaved_output, postsaved_output)
@require_accelerate
@mark.accelerate_tests
@require_torch_accelerator
def test_save_offloaded_model_dynamic_tied_weights_keys(self):
from accelerate import dispatch_model
device_map = {"base": f"{torch_device}:0", "linear": "cpu", "linear2": "cpu"}
model = ModelWithHead(PretrainedConfig())
dispatch_model(model, device_map)
transform_a = torch.nn.Linear(1, 1, bias=False)
transform_a._dynamic_tied_weights_keys = ["weight"]
transform_b = torch.nn.Linear(1, 1, bias=False)
transform_b._dynamic_tied_weights_keys = ["weight"]
model.linear.register_module("transform_a", transform_a)
model.linear.register_module("transform_b", transform_b)
model.linear2.register_module("transform_a", transform_a)
model.linear2.register_module("transform_b", transform_b)
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir)
@require_safetensors
def test_use_safetensors(self):
# Should not raise anymore