SUMIN/HuggingFace_transformer
1
0
Fork 0
Code Issues Pull Requests Actions 7 Packages Projects Releases Wiki Activity

correct opt (#17301)

Browse Source
This commit is contained in:
Patrick von Platen
2022-05-17 15:48:23 +02:00
committed by GitHub
parent 349f1c85d3
commit 1f13ba818e
1 changed files with 3 additions and 7 deletions
Download Patch File Download Diff File Expand all files Collapse all files

10
tests/models/opt/test_modeling_opt.py
View File

@@ -22,7 +22,7 @@ import unittest
import timeout_decorator # noqa import timeout_decorator # noqa
from transformers import OPTConfig, is_torch_available from transformers import OPTConfig, is_torch_available
from transformers.testing_utils import require_sentencepiece, require_tokenizers, require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from ...generation.test_generation_utils import GenerationTesterMixin from ...generation.test_generation_utils import GenerationTesterMixin
from ...test_configuration_common import ConfigTester from ...test_configuration_common import ConfigTester
@@ -266,25 +266,21 @@ def _long_tensor(tok_lst):
@require_torch @require_torch
@require_sentencepiece
@require_tokenizers
class OPTModelIntegrationTests(unittest.TestCase): class OPTModelIntegrationTests(unittest.TestCase):
@slow @slow
def test_inference_no_head(self): def test_inference_no_head(self):
model = OPTModel.from_pretrained("facebook/opt-350m").to(torch_device) model = OPTModel.from_pretrained("facebook/opt-350m").to(torch_device)
input_ids = _long_tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]]) input_ids = _long_tensor([[0, 31414, 232, 328, 740, 1140, 12695, 69, 46078, 1588, 2]])
attention_mask = input_ids.ne(model.config.pad_token_id)
with torch.no_grad(): with torch.no_grad():
output = model(input_ids=input_ids, attention_mask=attention_mask).last_hidden_state output = model(input_ids=input_ids).last_hidden_state
expected_shape = torch.Size((1, 11, 512)) expected_shape = torch.Size((1, 11, 512))
self.assertEqual(output.shape, expected_shape) self.assertEqual(output.shape, expected_shape)
expected_slice = torch.tensor( expected_slice = torch.tensor(
[[-0.2873, -1.9218, -0.3033], [-1.2710, -0.1338, -0.1902], [0.4095, 0.1214, -1.3121]], device=torch_device [[-0.2867, -1.9256, -0.3062], [-1.2711, -0.1337, -0.1897], [0.4109, 0.1187, -1.3142]], device=torch_device
) )
self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-3)) self.assertTrue(torch.allclose(output[:, :3, :3], expected_slice, atol=1e-3))
@require_tokenizers
@require_torch @require_torch
@slow @slow
class OPTEmbeddingsTest(unittest.TestCase): class OPTEmbeddingsTest(unittest.TestCase):