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Switch return_dict to True by default. (#8530)

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* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Use the CI to identify failing tests

* Remove from all examples and tests

* More default switch

* Fixes

* More test fixes

* More fixes

* Last fixes hopefully

* Run on the real suite

* Fix slow tests
This commit is contained in:
Sylvain Gugger
2020-11-16 11:43:00 -05:00
committed by GitHub
parent 0d0a0785fd
commit 1073a2bde5
106 changed files with 138 additions and 234 deletions
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22
tests/test_modeling_prophetnet.py
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@@ -142,7 +142,6 @@ class ProphetNetModelTester:
disable_ngram_loss=self.disable_ngram_loss,
max_position_embeddings=self.max_position_embeddings,
is_encoder_decoder=self.is_encoder_decoder,
return_dict=True,
)
return (
@@ -344,7 +343,6 @@ class ProphetNetModelTester:
decoder_input_ids=decoder_input_ids,
attention_mask=attention_mask,
decoder_attention_mask=decoder_attention_mask,
return_dict=True,
)
tied_model_result = tied_model(
@@ -352,7 +350,6 @@ class ProphetNetModelTester:
decoder_input_ids=decoder_input_ids,
attention_mask=attention_mask,
decoder_attention_mask=decoder_attention_mask,
return_dict=True,
)
# check that models has less parameters
@@ -419,7 +416,6 @@ class ProphetNetModelTester:
attention_mask=attention_mask,
decoder_attention_mask=decoder_attention_mask,
labels=lm_labels,
return_dict=True,
)
self.parent.assertTrue(torch.allclose(result.loss, torch.tensor(128.2925, device=torch_device), atol=1e-3))
@@ -433,9 +429,7 @@ class ProphetNetModelTester:
model.to(torch_device)
model.eval()
outputs_no_mask = model(
input_ids=input_ids[:, :5], decoder_input_ids=decoder_input_ids[:, :5], return_dict=True
)
outputs_no_mask = model(input_ids=input_ids[:, :5], decoder_input_ids=decoder_input_ids[:, :5])
attention_mask = torch.ones_like(input_ids)
decoder_attention_mask = torch.ones_like(decoder_input_ids)
@@ -446,7 +440,6 @@ class ProphetNetModelTester:
attention_mask=attention_mask,
decoder_input_ids=decoder_input_ids,
decoder_attention_mask=decoder_attention_mask,
return_dict=True,
)
# check encoder
@@ -524,7 +517,6 @@ class ProphetNetStandaloneDecoderModelTester:
bos_token_id=1,
eos_token_id=2,
ngram=2,
return_dict=True,
num_buckets=32,
relative_max_distance=128,
disable_ngram_loss=False,
@@ -562,7 +554,6 @@ class ProphetNetStandaloneDecoderModelTester:
self.max_position_embeddings = max_position_embeddings
self.add_cross_attention = add_cross_attention
self.is_encoder_decoder = is_encoder_decoder
self.return_dict = return_dict
self.scope = None
self.decoder_key_length = decoder_seq_length
@@ -602,7 +593,6 @@ class ProphetNetStandaloneDecoderModelTester:
max_position_embeddings=self.max_position_embeddings,
add_cross_attention=self.add_cross_attention,
is_encoder_decoder=self.is_encoder_decoder,
return_dict=self.return_dict,
)
return (
@@ -757,7 +747,6 @@ class ProphetNetStandaloneEncoderModelTester:
pad_token_id=0,
bos_token_id=1,
eos_token_id=2,
return_dict=True,
num_buckets=32,
relative_max_distance=128,
disable_ngram_loss=False,
@@ -794,7 +783,6 @@ class ProphetNetStandaloneEncoderModelTester:
self.max_position_embeddings = max_position_embeddings
self.add_cross_attention = add_cross_attention
self.is_encoder_decoder = is_encoder_decoder
self.return_dict = return_dict
self.scope = None
self.decoder_key_length = decoder_seq_length
@@ -829,7 +817,6 @@ class ProphetNetStandaloneEncoderModelTester:
max_position_embeddings=self.max_position_embeddings,
add_cross_attention=self.add_cross_attention,
is_encoder_decoder=self.is_encoder_decoder,
return_dict=self.return_dict,
)
return (
@@ -919,7 +906,6 @@ class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Test
# methods overwrite method in `test_modeling_common.py`
def test_attention_outputs(self):
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
config.return_dict = True
seq_len = getattr(self.model_tester, "seq_length", None)
decoder_seq_length = getattr(self.model_tester, "decoder_seq_length", seq_len)
@@ -933,7 +919,6 @@ class ProphetNetModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.Test
for model_class in self.all_model_classes:
inputs_dict["output_attentions"] = True
inputs_dict["output_hidden_states"] = False
config.return_dict = True
model = model_class(config)
model.to(torch_device)
model.eval()
@@ -1121,7 +1106,6 @@ class ProphetNetModelIntegrationTest(unittest.TestCase):
attention_mask=None,
encoder_outputs=None,
decoder_input_ids=decoder_prev_ids,
return_dict=True,
)
output_predited_logits = output[0]
expected_shape = torch.Size((1, 12, 30522))
@@ -1143,9 +1127,7 @@ class ProphetNetModelIntegrationTest(unittest.TestCase):
assert torch.allclose(encoder_outputs[:, :3, :3], expected_encoder_outputs_slice, atol=1e-4)
# decoder outputs
decoder_outputs = model.prophetnet.decoder(
decoder_prev_ids, encoder_hidden_states=encoder_outputs, return_dict=True
)
decoder_outputs = model.prophetnet.decoder(decoder_prev_ids, encoder_hidden_states=encoder_outputs)
predicting_streams = decoder_outputs[1].view(1, model.config.ngram, 12, -1)
predicting_streams_logits = model.lm_head(predicting_streams)
next_first_stream_logits = predicting_streams_logits[:, 0]