SUMIN/HuggingFace_transformer
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[Seq2Seq] Fix a couple of bugs and clean examples (#7474)

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* clean T5

* fix t5 tests

* fix index typo

* fix tf common test

* fix examples

* change positional ordering for Bart and FSTM

* add signature test

* clean docs and add tests

* add docs to encoder decoder

* clean docs

* correct two doc strings

* remove sig test for TF Elektra & Funnel

* fix tf t5 slow tests

* fix input_ids to inputs in tf

* Update src/transformers/modeling_bart.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_bart.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* implement lysandre results

* make style

* fix encoder decoder typo

* fix tf slow tests

* fix slow tests

* renaming

* remove unused input

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>
This commit is contained in:
Patrick von Platen
2020-10-01 17:38:50 +02:00
committed by GitHub
parent a42f62d34f
commit 62f5ae68ec
27 changed files with 686 additions and 414 deletions
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19
tests/test_modeling_fsmt.py
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@@ -71,7 +71,7 @@ class ModelTester:
# hack needed for modeling_common tests - despite not really having this attribute in this model
self.vocab_size = self.src_vocab_size
def prepare_config_and_inputs_for_common(self):
def prepare_config_and_inputs(self):
input_ids = ids_tensor([self.batch_size, self.seq_length], self.src_vocab_size).clamp(
3,
)
@@ -99,6 +99,13 @@ class ModelTester:
inputs_dict = prepare_fsmt_inputs_dict(config, input_ids)
return config, inputs_dict
def prepare_config_and_inputs_for_common(self):
config, inputs_dict = self.prepare_config_and_inputs()
inputs_dict["decoder_input_ids"] = inputs_dict["input_ids"]
inputs_dict["decoder_attention_mask"] = inputs_dict["attention_mask"]
inputs_dict["use_cache"] = False
return config, inputs_dict
def prepare_fsmt_inputs_dict(
config,
@@ -142,7 +149,7 @@ class FSMTModelTest(ModelTesterMixin, unittest.TestCase):
# XXX: override test_model_common_attributes / different Embedding type
def test_model_common_attributes(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config, inputs_dict = self.model_tester.prepare_config_and_inputs()
for model_class in self.all_model_classes:
model = model_class(config)
@@ -152,7 +159,7 @@ class FSMTModelTest(ModelTesterMixin, unittest.TestCase):
self.assertTrue(x is None or isinstance(x, torch.nn.modules.sparse.Embedding))
def test_initialization_more(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config, inputs_dict = self.model_tester.prepare_config_and_inputs()
model = FSMTModel(config)
model.to(torch_device)
model.eval()
@@ -170,7 +177,7 @@ class FSMTModelTest(ModelTesterMixin, unittest.TestCase):
# self.assertAlmostEqual(torch.std(model.encoder.embed_positions.weights).item(), config.init_std, 2)
def test_advanced_inputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config, inputs_dict = self.model_tester.prepare_config_and_inputs()
config.use_cache = False
inputs_dict["input_ids"][:, -2:] = config.pad_token_id
decoder_input_ids, decoder_attn_mask, causal_mask = _prepare_fsmt_decoder_inputs(
@@ -200,7 +207,7 @@ class FSMTModelTest(ModelTesterMixin, unittest.TestCase):
_assert_tensors_equal(decoder_features_with_long_encoder_mask, decoder_features_with_created_mask)
def test_save_load_strict(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config, inputs_dict = self.model_tester.prepare_config_and_inputs()
for model_class in self.all_model_classes:
model = model_class(config)
@@ -210,7 +217,7 @@ class FSMTModelTest(ModelTesterMixin, unittest.TestCase):
self.assertEqual(info["missing_keys"], [])
def test_save_load_no_save_keys(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config, inputs_dict = self.model_tester.prepare_config_and_inputs()
for model_class in self.all_model_classes:
model = model_class(config)