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Use tiny models for get_pretrained_model in TFEncoderDecoderModelTest #15989

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Merged
merged 4 commits into from
Mar 9, 2022
Merged

Use tiny models for get_pretrained_model in TFEncoderDecoderModelTest #15989

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7768d90
Use tiny model for TFRembertEncoderDecoderModelTest.get_pretrained_mo…
ydshieh Mar 8, 2022
07c0a68
Use more tiny models
ydshieh Mar 8, 2022
42d4e6d
fix names
ydshieh Mar 8, 2022
9168a3b
rename
ydshieh Mar 8, 2022
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23 changes: 17 additions & 6 deletions tests/encoder_decoder/test_modeling_tf_encoder_decoder.py
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Original file line number Diff line number Diff line change
Expand Up @@ -509,8 +509,7 @@ def test_pt_tf_equivalence(self):
model = TFEncoderDecoderModel(encoder_decoder_config)
model(**inputs_dict)

@slow
def test_real_model_save_load_from_pretrained(self):
def test_model_save_load_from_pretrained(self):
model_2 = self.get_pretrained_model()
input_ids = ids_tensor([13, 5], model_2.config.encoder.vocab_size)
decoder_input_ids = ids_tensor([13, 1], model_2.config.decoder.vocab_size)
Expand Down Expand Up @@ -542,7 +541,10 @@ def test_real_model_save_load_from_pretrained(self):
@require_tf
class TFBertEncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
def get_pretrained_model(self):
return TFEncoderDecoderModel.from_encoder_decoder_pretrained("bert-base-uncased", "bert-base-uncased")
return TFEncoderDecoderModel.from_encoder_decoder_pretrained(
"hf-internal-testing/tiny-random-bert",
"hf-internal-testing/tiny-random-bert",
)

def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFBertModel(config, name="encoder")
Expand Down Expand Up @@ -637,7 +639,10 @@ def test_bert2bert_summarization(self):
@require_tf
class TFGPT2EncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
def get_pretrained_model(self):
return TFEncoderDecoderModel.from_encoder_decoder_pretrained("bert-base-cased", "../gpt2")
return TFEncoderDecoderModel.from_encoder_decoder_pretrained(
"hf-internal-testing/tiny-random-bert",
"hf-internal-testing/tiny-random-gpt2",
)

def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFBertModel(config, name="encoder")
Expand Down Expand Up @@ -726,7 +731,10 @@ def test_bert2gpt2_summarization(self):
@require_tf
class TFRoBertaEncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
def get_pretrained_model(self):
return TFEncoderDecoderModel.from_encoder_decoder_pretrained("roberta-base", "roberta-base")
return TFEncoderDecoderModel.from_encoder_decoder_pretrained(
"hf-internal-testing/tiny-random-roberta",
"hf-internal-testing/tiny-random-roberta",
)

def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFRobertaModel(config, name="encoder")
Expand Down Expand Up @@ -782,7 +790,10 @@ def prepare_config_and_inputs(self):
@require_tf
class TFRembertEncoderDecoderModelTest(TFEncoderDecoderMixin, unittest.TestCase):
def get_pretrained_model(self):
return TFEncoderDecoderModel.from_encoder_decoder_pretrained("google/rembert", "google/rembert")
return TFEncoderDecoderModel.from_encoder_decoder_pretrained(
"hf-internal-testing/tiny-random-rembert",
"hf-internal-testing/tiny-random-rembert",
)

def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFRemBertModel(config, name="encoder")
Expand Down