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use torch.testing.assertclose instead to get more details about error in cis (#35659)

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* use torch.testing.assertclose instead to get more details about error in cis

* fix

* style

* test_all

* revert for I bert

* fixes and updates

* more image processing fixes

* more image processors

* fix mamba and co

* style

* less strick

* ok I won't be strict

* skip and be done

* up
This commit is contained in:
Arthur
2025-01-24 16:55:28 +01:00
committed by GitHub
parent 72d1a4cd53
commit b912f5ee43
255 changed files with 1048 additions and 969 deletions
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6
tests/models/phi3/test_modeling_phi3.py
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@@ -491,7 +491,7 @@ class Phi3ModelTest(ModelTesterMixin, GenerationTesterMixin, PipelineTesterMixin
# KV cache is re-computed after reaching the (`config.original_max_position_embeddings`+1)th token position
self.assertFalse(torch.allclose(keys_with_short_factor, keys_with_long_factor, atol=1e-2, rtol=1e-2))
# Last token generated using long factor
self.assertTrue(torch.allclose(last_token_logits, regenerated_last_token_logits, atol=1e-2, rtol=1e-2))
torch.testing.assert_close(last_token_logits, regenerated_last_token_logits, rtol=1e-2, atol=1e-2)
@slow
@@ -511,7 +511,7 @@ class Phi3IntegrationTest(unittest.TestCase):
EXPECTED_OUTPUT = torch.tensor([[ 0.9979, -1.9449, -2.5613, -2.2110, -0.9323, -2.2726, -3.2468, -2.0122,-1.0021, -1.2764, -1.0876, -1.2358, 3.9385, 6.2152, -0.3695, -2.3285,-1.2907, -1.8238, -1.9941, -2.2098, -0.6923, -1.6793, -1.1660, -2.0469,-0.7369, -1.4101, -1.4091, -3.1694, -1.8383, -1.1952],[ 3.0525, 1.9178, 3.7016, 0.9263, 0.3397, 1.9584, 2.1347, 0.3482, 1.3773, 0.2153, 0.2798, 0.8360, 9.0936, 11.4944, -0.3575, -0.9442,-0.1246, 1.3869, 0.9846, 1.7243, 0.9150, 1.0823, 0.4313, 1.5742, 0.2566, -0.1401, -1.3019, 0.4967, 0.6941, 0.7214]]).to(torch_device) # fmt: skip
self.assertTrue(torch.allclose(EXPECTED_OUTPUT, output[0, :2, :30], atol=1e-4, rtol=1e-4))
torch.testing.assert_close(EXPECTED_OUTPUT, output[0, :2, :30], rtol=1e-4, atol=1e-4)
def test_phi3_mini_4k_instruct_generation(self):
model = Phi3ForCausalLM.from_pretrained("microsoft/phi-3-mini-4k-instruct")
@@ -572,7 +572,7 @@ class Phi3IntegrationTest(unittest.TestCase):
EXPECTED_OUTPUT = torch.tensor([[ 1.8478, -0.5709, -1.6792, -1.2133, -0.7809, -0.8817, -2.0969, -1.1191,-0.7731, -1.0483, -0.5961, -1.3067, 3.1325, 6.9442, -0.4803, -0.9154,-1.3085, -1.0822, -1.1433, -0.7660, -0.8531, -0.9150, -0.6179, -1.6153,-0.2239, -1.3207, -1.1187, -2.4795, -1.4733, -0.4931],[ 3.5839, 2.4722, 3.7130, 1.2032, 0.7356, 2.7777, 2.5256, 0.9157, 1.6431, 0.3533, 0.5100, 1.3512, 8.9873, 10.9815, 0.3530, 0.1473, 0.2051, 1.8553, 1.5988, 2.2268, 1.1897, 1.2829, 0.7894, 1.8895, 0.7666, 0.4122, -0.9316, 0.9936, 1.2722, 0.8263]]).to(torch_device) # fmt: skip
self.assertTrue(torch.allclose(EXPECTED_OUTPUT, output[0, :2, :30], atol=1e-4, rtol=1e-4))
torch.testing.assert_close(EXPECTED_OUTPUT, output[0, :2, :30], rtol=1e-4, atol=1e-4)
def test_phi3_mini_128k_instruct_generation(self):
model = Phi3ForCausalLM.from_pretrained("microsoft/phi-3-mini-128k-instruct")