SUMIN/HuggingFace_transformer
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fix (#6946)

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This commit is contained in:
Patrick von Platen
2020-09-04 16:08:54 +02:00
committed by GitHub
parent a75e319819
commit e3990d137a
1 changed files with 5 additions and 4 deletions
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9
tests/test_modeling_lxmert.py
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@@ -120,8 +120,8 @@ class LxmertModelTester:
output_attentions = self.output_attentions output_attentions = self.output_attentions
input_ids = ids_tensor([self.batch_size, self.seq_length], vocab_size=self.vocab_size) input_ids = ids_tensor([self.batch_size, self.seq_length], vocab_size=self.vocab_size)
visual_feats = torch.rand(self.batch_size, self.num_visual_features, self.visual_feat_dim) visual_feats = torch.rand(self.batch_size, self.num_visual_features, self.visual_feat_dim, device=torch_device)
bounding_boxes = torch.rand(self.batch_size, self.num_visual_features, 4) bounding_boxes = torch.rand(self.batch_size, self.num_visual_features, 4, device=torch_device)
input_mask = None input_mask = None
if self.use_lang_mask: if self.use_lang_mask:
@@ -407,8 +407,8 @@ class LxmertModelTester:
num_small_labels = int(config.num_qa_labels * 2) num_small_labels = int(config.num_qa_labels * 2)
less_labels_ans = ids_tensor([self.batch_size], num_small_labels) less_labels_ans = ids_tensor([self.batch_size], num_small_labels)
more_labels_ans = ids_tensor([self.batch_size], num_large_labels) more_labels_ans = ids_tensor([self.batch_size], num_large_labels)
model_pretrain = LxmertForPreTraining(config=config) model_pretrain = LxmertForPreTraining(config=config).to(torch_device)
model_qa = LxmertForQuestionAnswering(config=config) model_qa = LxmertForQuestionAnswering(config=config).to(torch_device)
config.num_labels = num_small_labels config.num_labels = num_small_labels
end_labels = config.num_labels end_labels = config.num_labels
@@ -560,6 +560,7 @@ class LxmertModelTest(ModelTesterMixin, unittest.TestCase):
def test_model_from_pretrained(self): def test_model_from_pretrained(self):
for model_name in LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]: for model_name in LXMERT_PRETRAINED_MODEL_ARCHIVE_LIST[:1]:
model = LxmertModel.from_pretrained(model_name) model = LxmertModel.from_pretrained(model_name)
model.to(torch_device)
self.assertIsNotNone(model) self.assertIsNotNone(model)
def test_attention_outputs(self): def test_attention_outputs(self):