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More TF fixes (#28081)

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* More build_in_name_scope()

* Make sure we set the save spec now we don't do it with dummies anymore

* make fixup
This commit is contained in:
Matt
2023-12-18 15:26:03 +00:00
committed by GitHub
parent 0695b2421a
commit 71d47f0ad4
5 changed files with 6 additions and 5 deletions
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1
src/transformers/modeling_tf_utils.py
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@@ -1147,6 +1147,7 @@ class TFPreTrainedModel(tf.keras.Model, TFModelUtilsMixin, TFGenerationMixin, Pu
self.config = config self.config = config
self.name_or_path = config.name_or_path self.name_or_path = config.name_or_path
self.generation_config = GenerationConfig.from_model_config(config) if self.can_generate() else None self.generation_config = GenerationConfig.from_model_config(config) if self.can_generate() else None
self._set_save_spec(self.input_signature)
def get_config(self): def get_config(self):
return self.config.to_dict() return self.config.to_dict()

4
tests/models/auto/test_modeling_tf_auto.py
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@@ -211,7 +211,7 @@ class TFAutoModelTest(unittest.TestCase):
config = copy.deepcopy(model.config) config = copy.deepcopy(model.config)
config.architectures = ["FunnelBaseModel"] config.architectures = ["FunnelBaseModel"]
model = TFAutoModel.from_config(config) model = TFAutoModel.from_config(config)
model.build() model.build_in_name_scope()
self.assertIsInstance(model, TFFunnelBaseModel) self.assertIsInstance(model, TFFunnelBaseModel)
@@ -249,7 +249,7 @@ class TFAutoModelTest(unittest.TestCase):
config = NewModelConfig(**tiny_config.to_dict()) config = NewModelConfig(**tiny_config.to_dict())
model = auto_class.from_config(config) model = auto_class.from_config(config)
model.build() model.build_in_name_scope()
self.assertIsInstance(model, TFNewModel) self.assertIsInstance(model, TFNewModel)

2
tests/models/gpt2/test_modeling_tf_gpt2.py
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@@ -445,7 +445,7 @@ class TFGPT2ModelTest(TFModelTesterMixin, TFCoreModelTesterMixin, PipelineTester
continue continue
model = model_class(config) model = model_class(config)
model.build() model.build_in_name_scope()
onnx_model_proto, _ = tf2onnx.convert.from_keras(model, opset=self.onnx_min_opset) onnx_model_proto, _ = tf2onnx.convert.from_keras(model, opset=self.onnx_min_opset)

2
tests/models/whisper/test_modeling_tf_whisper.py
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@@ -312,7 +312,7 @@ class TFWhisperModelTest(TFModelTesterMixin, PipelineTesterMixin, unittest.TestC
config = self.model_tester.get_config() config = self.model_tester.get_config()
for model_class in self.all_model_classes: for model_class in self.all_model_classes:
model = model_class(config) model = model_class(config)
model.build() model.build_in_name_scope()
embeds = model.get_encoder().embed_positions.get_weights()[0] embeds = model.get_encoder().embed_positions.get_weights()[0]
sinusoids = sinusoidal_embedding_init(embeds.shape).numpy() sinusoids = sinusoidal_embedding_init(embeds.shape).numpy()

2
tests/utils/test_modeling_tf_core.py
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@@ -217,7 +217,7 @@ class TFCoreModelTesterMixin:
for model_class in self.all_model_classes[:2]: for model_class in self.all_model_classes[:2]:
class_inputs_dict = self._prepare_for_class(inputs_dict, model_class) class_inputs_dict = self._prepare_for_class(inputs_dict, model_class)
model = model_class(config) model = model_class(config)
model.build() model.build_in_name_scope()
num_out = len(model(class_inputs_dict)) num_out = len(model(class_inputs_dict))
for key in list(class_inputs_dict.keys()): for key in list(class_inputs_dict.keys()):