📦 Update torch to 2.3.1 #368
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Signed-off-by: gkumbhat <[email protected]>
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…h lib update Signed-off-by: gkumbhat <[email protected]>
Signed-off-by: gkumbhat <[email protected]>
Signed-off-by: Flavia Beo <[email protected]>
Changes result vector comparison to approximately.
Signed-off-by: gkumbhat <[email protected]>
Signed-off-by: gkumbhat <[email protected]>
Signed-off-by: Flavia Beo <[email protected]>
Adds tolerance params
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| @@ -1018,7 +1018,7 @@ def test_encoding_order(loaded_model: EmbeddingModule, truncate_input_tokens): | |||
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| # test order by comparing value of individual embeddings in sequence | |||
| for i, e in enumerate(separate_vectors): | |||
| assert np.allclose(e, combined_vectors[i]) | |||
| assert np.isclose(e, combined_vectors[i], rtol=1e-03, atol=1e-05).all() | |||
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q - what's the difference between isclose.all() here vs. allclose? Can't allclose also take the rtol etc. https://numpy.org/doc/stable/reference/generated/numpy.allclose.html
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