SUMIN/HuggingFace_transformer
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add a placeholder test

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This commit is contained in:
Rémi Louf
2019-10-08 15:57:25 +02:00
parent 0700983090
commit 82628b0fc9
2 changed files with 18 additions and 13 deletions
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2
transformers/__init__.py
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@@ -64,7 +64,7 @@ if is_torch_available():
BertForMaskedLM, BertForNextSentencePrediction, BertForMaskedLM, BertForNextSentencePrediction,
BertForSequenceClassification, BertForMultipleChoice, BertForSequenceClassification, BertForMultipleChoice,
BertForTokenClassification, BertForQuestionAnswering, BertForTokenClassification, BertForQuestionAnswering,
load_tf_weights_in_bert, BERT_PRETRAINED_MODEL_ARCHIVE_MAP) load_tf_weights_in_bert, BERT_PRETRAINED_MODEL_ARCHIVE_MAP, Bert2Bert)
from .modeling_openai import (OpenAIGPTPreTrainedModel, OpenAIGPTModel, from .modeling_openai import (OpenAIGPTPreTrainedModel, OpenAIGPTModel,
OpenAIGPTLMHeadModel, OpenAIGPTDoubleHeadsModel, OpenAIGPTLMHeadModel, OpenAIGPTDoubleHeadsModel,
load_tf_weights_in_openai_gpt, OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP) load_tf_weights_in_openai_gpt, OPENAI_GPT_PRETRAINED_MODEL_ARCHIVE_MAP)

19
transformers/tests/modeling_bert_test.py
View File

@@ -29,7 +29,7 @@ if is_torch_available():
from transformers import (BertConfig, BertModel, BertForMaskedLM, from transformers import (BertConfig, BertModel, BertForMaskedLM,
BertForNextSentencePrediction, BertForPreTraining, BertForNextSentencePrediction, BertForPreTraining,
BertForQuestionAnswering, BertForSequenceClassification, BertForQuestionAnswering, BertForSequenceClassification,
BertForTokenClassification, BertForMultipleChoice) BertForTokenClassification, BertForMultipleChoice, Bert2Bert)
from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_MAP from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_MAP
else: else:
pytestmark = pytest.mark.skip("Require Torch") pytestmark = pytest.mark.skip("Require Torch")
@@ -145,7 +145,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, self.seq_length, self.hidden_size]) [self.batch_size, self.seq_length, self.hidden_size])
self.parent.assertListEqual(list(result["pooled_output"].size()), [self.batch_size, self.hidden_size]) self.parent.assertListEqual(list(result["pooled_output"].size()), [self.batch_size, self.hidden_size])
def create_and_check_bert_for_masked_lm(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_masked_lm(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
model = BertForMaskedLM(config=config) model = BertForMaskedLM(config=config)
model.eval() model.eval()
@@ -172,7 +171,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, 2]) [self.batch_size, 2])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert_for_pretraining(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_pretraining(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
model = BertForPreTraining(config=config) model = BertForPreTraining(config=config)
model.eval() model.eval()
@@ -191,7 +189,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, 2]) [self.batch_size, 2])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert_for_question_answering(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_question_answering(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
model = BertForQuestionAnswering(config=config) model = BertForQuestionAnswering(config=config)
model.eval() model.eval()
@@ -210,7 +207,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, self.seq_length]) [self.batch_size, self.seq_length])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert_for_sequence_classification(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_sequence_classification(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
config.num_labels = self.num_labels config.num_labels = self.num_labels
model = BertForSequenceClassification(config) model = BertForSequenceClassification(config)
@@ -225,7 +221,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, self.num_labels]) [self.batch_size, self.num_labels])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert_for_token_classification(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_token_classification(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
config.num_labels = self.num_labels config.num_labels = self.num_labels
model = BertForTokenClassification(config=config) model = BertForTokenClassification(config=config)
@@ -240,7 +235,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, self.seq_length, self.num_labels]) [self.batch_size, self.seq_length, self.num_labels])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert_for_multiple_choice(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels): def create_and_check_bert_for_multiple_choice(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
config.num_choices = self.num_choices config.num_choices = self.num_choices
model = BertForMultipleChoice(config=config) model = BertForMultipleChoice(config=config)
@@ -261,6 +255,16 @@ class BertModelTest(CommonTestCases.CommonModelTester):
[self.batch_size, self.num_choices]) [self.batch_size, self.num_choices])
self.check_loss_output(result) self.check_loss_output(result)
def create_and_check_bert2bert(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
config.num_choices = self.num_choices
model = Bert2Bert(config=config)
model.eval()
bert2bert_inputs_ids = input_ids.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
bert2bert_token_type_ids = token_type_ids.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
bert2bert_input_mask = input_mask.unsqueeze(1).expand(-1, self.num_choices, -1).contiguous()
_ = model(bert2bert_inputs_ids,
attention_mask=bert2bert_input_mask,
token_type_ids=bert2bert_token_type_ids)
def prepare_config_and_inputs_for_common(self): def prepare_config_and_inputs_for_common(self):
config_and_inputs = self.prepare_config_and_inputs() config_and_inputs = self.prepare_config_and_inputs()
@@ -316,5 +320,6 @@ class BertModelTest(CommonTestCases.CommonModelTester):
shutil.rmtree(cache_dir) shutil.rmtree(cache_dir)
self.assertIsNotNone(model) self.assertIsNotNone(model)
if __name__ == "__main__": if __name__ == "__main__":
unittest.main() unittest.main()