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Update all references to canonical models (#29001)

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* Script & Manual edition

* Update
This commit is contained in:
Lysandre Debut
2024-02-16 08:16:58 +01:00
committed by GitHub
parent 1e402b957d
commit f497f564bb
561 changed files with 2682 additions and 2687 deletions
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4
tests/models/vision_encoder_decoder/test_modeling_flax_vision_encoder_decoder.py
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@@ -426,7 +426,7 @@ class FlaxViT2GPT2EncoderDecoderModelTest(FlaxEncoderDecoderMixin, unittest.Test
def get_pretrained_model(self):
return FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "gpt2"
"google/vit-base-patch16-224-in21k", "openai-community/gpt2"
)
@@ -434,7 +434,7 @@ class FlaxViT2GPT2EncoderDecoderModelTest(FlaxEncoderDecoderMixin, unittest.Test
class FlaxVisionEncoderDecoderModelTest(unittest.TestCase):
def get_from_encoderdecoder_pretrained_model(self):
return FlaxVisionEncoderDecoderModel.from_encoder_decoder_pretrained(
"google/vit-base-patch16-224-in21k", "gpt2"
"google/vit-base-patch16-224-in21k", "openai-community/gpt2"
)
def _check_configuration_tie(self, model):

20
tests/models/vision_encoder_decoder/test_modeling_tf_vision_encoder_decoder.py
View File

@@ -627,7 +627,9 @@ 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", "openai-community/gpt2"
)
def get_encoder_decoder_model(self, config, decoder_config):
encoder_model = TFViTModel(config, name="encoder")
@@ -672,10 +674,12 @@ 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", "openai-community/gpt2"
)
def get_decoder_config(self):
config = AutoConfig.from_pretrained("gpt2")
config = AutoConfig.from_pretrained("openai-community/gpt2")
config.is_decoder = True
config.add_cross_attention = True
return config
@@ -685,7 +689,9 @@ 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(
"openai-community/gpt2", config=self.get_decoder_config(), name="decoder"
)
return {"encoder": encoder_model, "decoder": decoder_model}
def _check_configuration_tie(self, model):
@@ -714,7 +720,7 @@ 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("openai-community/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):
@@ -829,7 +835,7 @@ class TFVisionEncoderDecoderModelSaveLoadTests(unittest.TestCase):
config = self.get_encoder_decoder_config()
image_processor = AutoImageProcessor.from_pretrained("google/vit-base-patch16-224-in21k")
decoder_tokenizer = AutoTokenizer.from_pretrained("gpt2")
decoder_tokenizer = AutoTokenizer.from_pretrained("openai-community/gpt2")
img = prepare_img()
pixel_values = image_processor(images=img, return_tensors="tf").pixel_values
@@ -845,7 +851,7 @@ 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"
"openai-community/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")