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Fix Encoder-Decoder testing issue about repo. names (#19250)

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* Change "../gpt2" to "gpt2"

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>
This commit is contained in:
Yih-Dar
2022-09-30 18:15:07 +02:00
committed by GitHub
parent 2fba98e585
commit f33858d18a
3 changed files with 10 additions and 14 deletions
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18
tests/models/vision_encoder_decoder/test_modeling_tf_vision_encoder_decoder.py
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@@ -673,9 +673,7 @@ class TFVisionEncoderDecoderMixin:
@require_tf
class TFViT2GPT2EncoderDecoderModelTest(TFVisionEncoderDecoderMixin, unittest.TestCase):
def get_pretrained_model(self):
return TFVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "../gpt2"
)
return TFVisionEncoderDecoderModel.from_encoder_decoder_pretrained("google/vit-base-patch16-224-in21k", "gpt2")
def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFViTModel(config, name="encoder")
@@ -720,12 +718,10 @@ class TFViT2GPT2EncoderDecoderModelTest(TFVisionEncoderDecoderMixin, unittest.Te
@require_tf
class TFVisionEncoderDecoderModelTest(unittest.TestCase):
def get_from_encoderdecoder_pretrained_model(self):
return TFVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "../gpt2"
)
return TFVisionEncoderDecoderModel.from_encoder_decoder_pretrained("google/vit-base-patch16-224-in21k", "gpt2")
def get_decoder_config(self):
config = AutoConfig.from_pretrained("../gpt2")
config = AutoConfig.from_pretrained("gpt2")
config.is_decoder = True
config.add_cross_attention = True
return config
@@ -735,7 +731,7 @@ class TFVisionEncoderDecoderModelTest(unittest.TestCase):
def get_encoder_decoder_models(self):
encoder_model = TFViTModel.from_pretrained("google/vit-base-patch16-224-in21k", name="encoder")
decoder_model = TFGPT2LMHeadModel.from_pretrained("../gpt2", config=self.get_decoder_config(), name="decoder")
decoder_model = TFGPT2LMHeadModel.from_pretrained("gpt2", config=self.get_decoder_config(), name="decoder")
return {"encoder": encoder_model, "decoder": decoder_model}
def _check_configuration_tie(self, model):
@@ -764,7 +760,7 @@ def prepare_img():
class TFVisionEncoderDecoderModelSaveLoadTests(unittest.TestCase):
def get_encoder_decoder_config(self):
encoder_config = AutoConfig.from_pretrained("google/vit-base-patch16-224-in21k")
decoder_config = AutoConfig.from_pretrained("../gpt2", is_decoder=True, add_cross_attention=True)
decoder_config = AutoConfig.from_pretrained("gpt2", is_decoder=True, add_cross_attention=True)
return VisionEncoderDecoderConfig.from_encoder_decoder_configs(encoder_config, decoder_config)
def get_encoder_decoder_config_small(self):
@@ -879,7 +875,7 @@ class TFVisionEncoderDecoderModelSaveLoadTests(unittest.TestCase):
config = self.get_encoder_decoder_config()
feature_extractor = AutoFeatureExtractor.from_pretrained("google/vit-base-patch16-224-in21k")
decoder_tokenizer = AutoTokenizer.from_pretrained("../gpt2")
decoder_tokenizer = AutoTokenizer.from_pretrained("gpt2")
img = prepare_img()
pixel_values = feature_extractor(images=img, return_tensors="tf").pixel_values
@@ -896,7 +892,7 @@ class TFVisionEncoderDecoderModelSaveLoadTests(unittest.TestCase):
encoder = TFAutoModel.from_pretrained("google/vit-base-patch16-224-in21k", name="encoder")
# It's necessary to specify `add_cross_attention=True` here.
decoder = TFAutoModelForCausalLM.from_pretrained(
"../gpt2", is_decoder=True, add_cross_attention=True, name="decoder"
"gpt2", is_decoder=True, add_cross_attention=True, name="decoder"
)
pretrained_encoder_dir = os.path.join(tmp_dirname, "pretrained_encoder")
pretrained_decoder_dir = os.path.join(tmp_dirname, "pretrained_decoder")