TestMarian_MT_EN::test_batch_generation_mt_en Failing due to randomly generated tokens

[LysandreJik]

The test fails with the following:

_________________ TestMarian_MT_EN.test_batch_generation_mt_en _________________
[gw0] linux -- Python 3.6.9 /usr/local/bin/python

self = <tests.test_modeling_tf_marian.TestMarian_MT_EN testMethod=test_batch_generation_mt_en>

    @slow
    def test_batch_generation_mt_en(self):
>       self._assert_generated_batch_equal_expected()

tests/test_modeling_tf_marian.py:390: 
_ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ _ 
tests/test_modeling_tf_marian.py:366: in _assert_generated_batch_equal_expected
    self.assertListEqual(self.expected_text, generated_words)
E   AssertionError: Lists differ: ['Tou[19 chars] healed a man who was affected by the sad disease of leprosy.'] != ['Tou[19 chars] healed a man who was affected by▁kifkażUnjonik ill.']
E   
E   First differing element 0:
E   'Touc[17 chars]s healed a man who was affected by the sad disease of leprosy.'
E   'Touc[17 chars]s healed a man who was affected by▁kifkażUnjonik ill.'
E   
E   - ['Touching gently, Jesus healed a man who was affected by the sad disease of '
E   ?                                                          ^^^^^^ ^^^ ^^^^^^^^^
E   
E   + ['Touching gently, Jesus healed a man who was affected by▁kifkażUnjonik ill.']
E   ?                                                          ^^^^^ ^^^^^^ ^^^^^^ +
E   
E   -  'leprosy.']

[LysandreJik]

Traced back to this commit: 184ef8e

I suspect there is a difference between the upload TF and PT checkpoints

[LysandreJik]

It seems there's a single difference in the final logits bias:

import torch
from transformers import MarianMTModel

pt_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-mt-en")
tf_model = MarianMTModel.from_pretrained("Helsinki-NLP/opus-mt-mt-en", from_tf=True)

pt, tf = pt_model.state_dict(), tf_model.state_dict()

ptf = {}

for key, value in pt.items():
    ptf[key] = [value]

for key, value in tf.items():
    if key not in ptf:
        print(key, "not in ptf")
    else:
        ptf[key].append(value)

for key, value in ptf.items():
    _pt, _tf = value
    difference = torch.max(torch.abs(_pt - _tf)).tolist()
    if difference > 0:
        print(key, difference)

# final_logits_bias 10.176068305969238

Seems systematic, independent of runtime or seed.

[LysandreJik]

I would say the error comes from the TF checkpoint on the hub, looking forward to your input @patrickvonplaten and @patil-suraj.

I'll deactivate the test in the meantime.

[LysandreJik]

This is also the case for the Helsinki-NLP/opus-mt-en-zh checkpoint:

# final_logits_bias 8.724637031555176

[LysandreJik]

And for the Helsinki-NLP/opus-mt-en-ROMANCE checkpoint:

final_logits_bias 11.757145881652832

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