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sayakpaul merged 9 commits into from
May 18, 2026
+48 −38
Merged

fix lfs pointer rejection problems for hub tests #13733

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00767a4
fix lfs pointer rejection problems for hub tests
sayakpaul May 13, 2026
b510083
fix more
sayakpaul May 13, 2026
ff1f987
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 13, 2026
49d98fe
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 13, 2026
d3bef7a
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 15, 2026
35bfd30
Delete .claude directory
sayakpaul May 15, 2026
2584c88
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 15, 2026
5ac74c8
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 15, 2026
a06d940
Merge branch 'main' into fix-lfs-pointer-problems
sayakpaul May 18, 2026
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43 changes: 24 additions & 19 deletions tests/models/test_modeling_common.py
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Original file line number Diff line number Diff line change
Expand Up @@ -2042,19 +2042,20 @@ def test_push_to_hub(self):
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(token=TOKEN, repo_id=self.repo_id)

# Push to hub via save_pretrained
# Push to hub via save_pretrained to a separate repo. Reusing `self.repo_id` after
# deleting it makes the staging server's LFS GC reject the next commit with
# "LFS pointer pointed to a file that does not exist" when the model bytes are identical.
save_repo_id = f"{self.repo_id}-saved"
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, repo_id=self.repo_id, push_to_hub=True, token=TOKEN)
model.save_pretrained(tmp_dir, repo_id=save_repo_id, push_to_hub=True, token=TOKEN)

new_model = UNet2DConditionModel.from_pretrained(f"{USER}/{self.repo_id}")
new_model = UNet2DConditionModel.from_pretrained(f"{USER}/{save_repo_id}")
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(self.repo_id, token=TOKEN)
# Reset repos
delete_repo(token=TOKEN, repo_id=self.repo_id)
delete_repo(save_repo_id, token=TOKEN)

def test_push_to_hub_in_organization(self):
model = UNet2DConditionModel(
Expand All @@ -2073,19 +2074,20 @@ def test_push_to_hub_in_organization(self):
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(token=TOKEN, repo_id=self.org_repo_id)

# Push to hub via save_pretrained
# Push to hub via save_pretrained to a separate repo. Reusing `self.org_repo_id` after
# deleting it makes the staging server's LFS GC reject the next commit with
# "LFS pointer pointed to a file that does not exist" when the model bytes are identical.
save_org_repo_id = f"{self.org_repo_id}-saved"
with tempfile.TemporaryDirectory() as tmp_dir:
model.save_pretrained(tmp_dir, push_to_hub=True, token=TOKEN, repo_id=self.org_repo_id)
model.save_pretrained(tmp_dir, push_to_hub=True, token=TOKEN, repo_id=save_org_repo_id)

new_model = UNet2DConditionModel.from_pretrained(self.org_repo_id)
new_model = UNet2DConditionModel.from_pretrained(save_org_repo_id)
for p1, p2 in zip(model.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(self.org_repo_id, token=TOKEN)
# Reset repos
delete_repo(token=TOKEN, repo_id=self.org_repo_id)
delete_repo(save_org_repo_id, token=TOKEN)

@unittest.skipIf(
not is_jinja_available(),
Expand All @@ -2102,13 +2104,16 @@ def test_push_to_hub_library_name(self):
up_block_types=("CrossAttnUpBlock2D", "UpBlock2D"),
cross_attention_dim=32,
)
model.push_to_hub(self.repo_id, token=TOKEN)
# Use a method-unique repo to avoid recycling a name that `test_push_to_hub` just deleted,
# which the staging server rejects with an LFS pointer error.
repo_id = f"test-model-library-name-{uuid.uuid4()}"
model.push_to_hub(repo_id, token=TOKEN)

model_card = ModelCard.load(f"{USER}/{self.repo_id}", token=TOKEN).data
model_card = ModelCard.load(f"{USER}/{repo_id}", token=TOKEN).data
assert model_card.library_name == "diffusers"

# Reset repo
delete_repo(self.repo_id, token=TOKEN)
delete_repo(repo_id, token=TOKEN)


@require_torch_accelerator
Expand Down
43 changes: 24 additions & 19 deletions tests/pipelines/test_pipelines_common.py
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Open in desktop
Original file line number Diff line number Diff line change
Expand Up @@ -2583,19 +2583,20 @@ def test_push_to_hub(self):
for p1, p2 in zip(unet.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(token=TOKEN, repo_id=self.repo_id)

# Push to hub via save_pretrained
# Push to hub via save_pretrained to a separate repo. Reusing `self.repo_id` after
# deleting it makes the staging server's LFS GC reject the next commit with
# "LFS pointer pointed to a file that does not exist" when the model bytes are identical.
save_repo_id = f"{self.repo_id}-saved"
with tempfile.TemporaryDirectory() as tmp_dir:
pipeline.save_pretrained(tmp_dir, repo_id=self.repo_id, push_to_hub=True, token=TOKEN)
pipeline.save_pretrained(tmp_dir, repo_id=save_repo_id, push_to_hub=True, token=TOKEN)

new_model = UNet2DConditionModel.from_pretrained(f"{USER}/{self.repo_id}", subfolder="unet")
new_model = UNet2DConditionModel.from_pretrained(f"{USER}/{save_repo_id}", subfolder="unet")
for p1, p2 in zip(unet.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(self.repo_id, token=TOKEN)
# Reset repos
delete_repo(token=TOKEN, repo_id=self.repo_id)
delete_repo(save_repo_id, token=TOKEN)

def test_push_to_hub_in_organization(self):
components = self.get_pipeline_components()
Expand All @@ -2607,19 +2608,20 @@ def test_push_to_hub_in_organization(self):
for p1, p2 in zip(unet.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(token=TOKEN, repo_id=self.org_repo_id)

# Push to hub via save_pretrained
# Push to hub via save_pretrained to a separate repo. Reusing `self.org_repo_id` after
# deleting it makes the staging server's LFS GC reject the next commit with
# "LFS pointer pointed to a file that does not exist" when the model bytes are identical.
save_org_repo_id = f"{self.org_repo_id}-saved"
with tempfile.TemporaryDirectory() as tmp_dir:
pipeline.save_pretrained(tmp_dir, push_to_hub=True, token=TOKEN, repo_id=self.org_repo_id)
pipeline.save_pretrained(tmp_dir, push_to_hub=True, token=TOKEN, repo_id=save_org_repo_id)

new_model = UNet2DConditionModel.from_pretrained(self.org_repo_id, subfolder="unet")
new_model = UNet2DConditionModel.from_pretrained(save_org_repo_id, subfolder="unet")
for p1, p2 in zip(unet.parameters(), new_model.parameters()):
self.assertTrue(torch.equal(p1, p2))

# Reset repo
delete_repo(self.org_repo_id, token=TOKEN)
# Reset repos
delete_repo(token=TOKEN, repo_id=self.org_repo_id)
delete_repo(save_org_repo_id, token=TOKEN)

@unittest.skipIf(
not is_jinja_available(),
Expand All @@ -2628,13 +2630,16 @@ def test_push_to_hub_in_organization(self):
def test_push_to_hub_library_name(self):
components = self.get_pipeline_components()
pipeline = StableDiffusionPipeline(**components)
pipeline.push_to_hub(self.repo_id, token=TOKEN)
# Use a method-unique repo to avoid recycling a name that `test_push_to_hub` just deleted,
# which the staging server rejects with an LFS pointer error.
repo_id = f"test-pipeline-library-name-{uuid.uuid4()}"
pipeline.push_to_hub(repo_id, token=TOKEN)

model_card = ModelCard.load(f"{USER}/{self.repo_id}", token=TOKEN).data
model_card = ModelCard.load(f"{USER}/{repo_id}", token=TOKEN).data
assert model_card.library_name == "diffusers"

# Reset repo
delete_repo(self.repo_id, token=TOKEN)
delete_repo(repo_id, token=TOKEN)


class PyramidAttentionBroadcastTesterMixin:
Expand Down
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