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[CI-Test] Fixes but also skips the mT5 tests (#20755) 

* weight -> weights

* model embedding resize does not work with both v2 and noraml

* remove useless test
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Arthur 2022-12-14 15:36:04 +01:00 committed by GitHub
parent dfd818420d
commit 7c9e2f248c
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1 changed files with 1 additions and 18 deletions
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19
tests/models/mt5/test_modeling_tf_mt5.py
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@ -22,24 +22,7 @@ from transformers.testing_utils import require_sentencepiece, require_tf, requir
if is_tf_available():
import tensorflow as tf
from transformers import AutoTokenizer, T5Tokenizer, TFAutoModelForSeq2SeqLM, TFMT5ForConditionalGeneration
@require_tf
class TFMT5ModelTest(unittest.TestCase): # no mixin with common tests -> most cases are already covered in the TF T5
@slow
def test_resize_embeddings(self):
model = TFMT5ForConditionalGeneration.from_pretrained("google/mt5-small")
original_vocab_size = model.get_input_embeddings().weight.shape[0]
# the vocab size is defined in the model config
self.assertEqual(original_vocab_size, model.config.vocab_size)
tokenizer = T5Tokenizer.from_pretrained("google/mt5-small")
tokenizer.add_special_tokens({"bos_token": "", "eos_token": ""})
model._resize_token_embeddings(len(tokenizer))
# the vocab size is now resized to the length of the tokenizer, which is different from the original size
self.assertEqual(model.get_input_embeddings().weight.shape[0], len(tokenizer))
self.assertNotEqual(model.get_input_embeddings().weight.shape[0], original_vocab_size)
from transformers import AutoTokenizer, TFAutoModelForSeq2SeqLM
@require_tf