SUMIN/HuggingFace_transformer
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Replace legacy tensor.Tensor with torch.tensor/torch.empty (#12027)

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* Replace legacy torch.Tensor constructor with torch.{tensor, empty}

* Remove torch.Tensor in examples
This commit is contained in:
Mario Šaško
2021-06-08 05:58:38 -07:00
committed by GitHub
parent e33085d648
commit f5eec0d8e9
13 changed files with 26 additions and 22 deletions
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4
tests/test_modeling_fsmt.py
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@@ -305,7 +305,7 @@ class FSMTHeadTests(unittest.TestCase):
return config, input_ids, batch_size
def test_generate_beam_search(self):
input_ids = torch.Tensor([[71, 82, 2], [68, 34, 2]]).long().to(torch_device)
input_ids = torch.tensor([[71, 82, 2], [68, 34, 2]], dtype=torch.long, device=torch_device)
config = self._get_config()
lm_model = FSMTForConditionalGeneration(config).to(torch_device)
lm_model.eval()
@@ -322,7 +322,7 @@ class FSMTHeadTests(unittest.TestCase):
self.assertEqual(new_input_ids.shape, (input_ids.shape[0], max_length))
def test_shift_tokens_right(self):
input_ids = torch.Tensor([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]]).long()
input_ids = torch.tensor([[71, 82, 18, 33, 2, 1, 1], [68, 34, 26, 58, 30, 82, 2]], dtype=torch.long)
shifted = shift_tokens_right(input_ids, 1)
n_pad_before = input_ids.eq(1).float().sum()
n_pad_after = shifted.eq(1).float().sum()