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Optional layers (#8961)

Browse Source 
* Apply on BERT and ALBERT

* Update TF Bart

* Add input processing to TF BART

* Add input processing for TF CTRL

* Add input processing to TF Distilbert

* Add input processing to TF DPR

* Add input processing to TF Electra

* Add deprecated arguments

* Add input processing to TF XLM

* remove unused imports

* Add input processing to TF Funnel

* Add input processing to TF GPT2

* Add input processing to TF Longformer

* Add input processing to TF Lxmert

* Apply style

* Add input processing to TF Mobilebert

* Add input processing to TF GPT

* Add input processing to TF Roberta

* Add input processing to TF T5

* Add input processing to TF TransfoXL

* Apply style

* Rebase on master

* Fix wrong model name

* Fix BART

* Apply style

* Put the deprecated warnings in the input processing function

* Remove the unused imports

* Raise an error when len(kwargs)>0

* test ModelOutput instead of TFBaseModelOutput

* Address Patrick's comments

* Address Patrick's comments

* Add boolean processing for the inputs

* Take into account the optional layers

* Add missing/unexpected weights in the other models

* Apply style

* rename parameters

* Apply style

* Remove useless

* Remove useless

* Remove useless

* Update num parameters

* Fix tests

* Address Patrick's comment

* Remove useless attribute
This commit is contained in:
Julien Plu
2020-12-08 15:14:09 +01:00
committed by GitHub
parent 9d7d0005b0
commit bf7f79cd57
17 changed files with 195 additions and 98 deletions
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8
tests/test_modeling_tf_auto.py
View File

@@ -167,14 +167,14 @@ class TFAutoModelTest(unittest.TestCase):
def test_from_pretrained_identifier(self):
model = TFAutoModelWithLMHead.from_pretrained(SMALL_MODEL_IDENTIFIER)
self.assertIsInstance(model, TFBertForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)
self.assertEqual(model.num_parameters(only_trainable=True), 14830)
self.assertEqual(model.num_parameters(), 14410)
self.assertEqual(model.num_parameters(only_trainable=True), 14410)
def test_from_identifier_from_model_type(self):
model = TFAutoModelWithLMHead.from_pretrained(DUMMY_UNKWOWN_IDENTIFIER)
self.assertIsInstance(model, TFRobertaForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)
self.assertEqual(model.num_parameters(only_trainable=True), 14830)
self.assertEqual(model.num_parameters(), 14410)
self.assertEqual(model.num_parameters(only_trainable=True), 14410)
def test_parents_and_children_in_mappings(self):
# Test that the children are placed before the parents in the mappings, as the `instanceof` will be triggered

2
tests/test_modeling_tf_bert.py
View File

@@ -335,7 +335,7 @@ class TFBertModelTest(TFModelTesterMixin, unittest.TestCase):
model, output_loading_info = TFBertForTokenClassification.from_pretrained(
"jplu/tiny-tf-bert-random", output_loading_info=True
)
self.assertEqual(sorted(output_loading_info["unexpected_keys"]), ["mlm___cls", "nsp___cls"])
self.assertEqual(sorted(output_loading_info["unexpected_keys"]), [])
for layer in output_loading_info["missing_keys"]:
self.assertTrue(layer.split("_")[0] in ["dropout", "classifier"])

8
tests/test_modeling_tf_pytorch.py
View File

@@ -223,8 +223,8 @@ class TFPTAutoModelTest(unittest.TestCase):
def test_from_pretrained_identifier(self):
model = TFAutoModelWithLMHead.from_pretrained(SMALL_MODEL_IDENTIFIER, from_pt=True)
self.assertIsInstance(model, TFBertForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)
self.assertEqual(model.num_parameters(only_trainable=True), 14830)
self.assertEqual(model.num_parameters(), 14410)
self.assertEqual(model.num_parameters(only_trainable=True), 14410)
model = AutoModelWithLMHead.from_pretrained(SMALL_MODEL_IDENTIFIER, from_tf=True)
self.assertIsInstance(model, BertForMaskedLM)
@@ -234,8 +234,8 @@ class TFPTAutoModelTest(unittest.TestCase):
def test_from_identifier_from_model_type(self):
model = TFAutoModelWithLMHead.from_pretrained(DUMMY_UNKWOWN_IDENTIFIER, from_pt=True)
self.assertIsInstance(model, TFRobertaForMaskedLM)
self.assertEqual(model.num_parameters(), 14830)
self.assertEqual(model.num_parameters(only_trainable=True), 14830)
self.assertEqual(model.num_parameters(), 14410)
self.assertEqual(model.num_parameters(only_trainable=True), 14410)
model = AutoModelWithLMHead.from_pretrained(DUMMY_UNKWOWN_IDENTIFIER, from_tf=True)
self.assertIsInstance(model, RobertaForMaskedLM)