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Byebye test_batching_equivalence's flakiness (#35729)

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* fix

* fix

* skip

* better error message

---------

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2025-01-21 13:11:33 +01:00
committed by GitHub
parent 78f5ee0217
commit fd8d61fdb2
18 changed files with 92 additions and 50 deletions
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6
tests/models/superpoint/test_modeling_superpoint.py
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@@ -16,7 +16,7 @@ import unittest
from typing import List
from transformers.models.superpoint.configuration_superpoint import SuperPointConfig
from transformers.testing_utils import require_torch, require_vision, slow, torch_device
from transformers.testing_utils import is_flaky, require_torch, require_vision, slow, torch_device
from transformers.utils import cached_property, is_torch_available, is_vision_available
from ...test_configuration_common import ConfigTester
@@ -135,6 +135,10 @@ class SuperPointModelTest(ModelTesterMixin, unittest.TestCase):
def test_config(self):
self.config_tester.run_common_tests()
@is_flaky(description="The `indices` computed with `topk()` in `top_k_keypoints` is not stable.")
def test_batching_equivalence(self):
super().test_batching_equivalence()
@unittest.skip(reason="SuperPointForKeypointDetection does not use inputs_embeds")
def test_inputs_embeds(self):
pass