riaz.somc/transformers
1
0
Fork 0
mirror of https://github.com/huggingface/transformers.git synced 2025-07-31 02:02:21 +06:00
Code Issues Actions 33 Packages Projects Releases Wiki Activity

[tests] Flag to test on cuda

Browse Source
This commit is contained in:
Julien Chaumond 2019-11-06 15:56:12 +00:00
parent 13d9135fa5
commit 27e015bd54
2 changed files with 22 additions and 7 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

8
transformers/tests/conftest.py
View File

@ -7,6 +7,9 @@ def pytest_addoption(parser):
parser.addoption(
"--runslow", action="store_true", default=False, help="run slow tests"
)
parser.addoption(
"--use_cuda", action="store_true", default=False, help="run tests on gpu"
)
def pytest_configure(config):
@ -21,3 +24,8 @@ def pytest_collection_modifyitems(config, items):
for item in items:
if "slow" in item.keywords:
item.add_marker(skip_slow)
@pytest.fixture
def use_cuda(request):
""" Run test on gpu """
return request.config.getoption("--use_cuda")

21
transformers/tests/modeling_bert_test.py
View File

@ -35,6 +35,7 @@ else:
pytestmark = pytest.mark.skip("Require Torch")
@pytest.mark.usefixtures("use_cuda")
class BertModelTest(CommonTestCases.CommonModelTester):
all_model_classes = (BertModel, BertForMaskedLM, BertForNextSentencePrediction,
@ -66,6 +67,7 @@ class BertModelTest(CommonTestCases.CommonModelTester):
num_labels=3,
num_choices=4,
scope=None,
device='cpu',
):
self.parent = parent
self.batch_size = batch_size
@ -89,25 +91,26 @@ class BertModelTest(CommonTestCases.CommonModelTester):
self.num_labels = num_labels
self.num_choices = num_choices
self.scope = scope
self.device = device
def prepare_config_and_inputs(self):
input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
input_ids = ids_tensor([self.batch_size, self.seq_length], self.vocab_size).to(self.device)
input_mask = None
if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2)
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2).to(self.device)
token_type_ids = None
if self.use_token_type_ids:
token_type_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size)
token_type_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size).to(self.device)
sequence_labels = None
token_labels = None
choice_labels = None
if self.use_labels:
sequence_labels = ids_tensor([self.batch_size], self.type_sequence_label_size)
token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels)
choice_labels = ids_tensor([self.batch_size], self.num_choices)
sequence_labels = ids_tensor([self.batch_size], self.type_sequence_label_size).to(self.device)
token_labels = ids_tensor([self.batch_size, self.seq_length], self.num_labels).to(self.device)
choice_labels = ids_tensor([self.batch_size], self.num_choices).to(self.device)
config = BertConfig(
vocab_size_or_config_json_file=self.vocab_size,
@ -141,6 +144,7 @@ class BertModelTest(CommonTestCases.CommonModelTester):
def create_and_check_bert_model(self, config, input_ids, token_type_ids, input_mask, sequence_labels, token_labels, choice_labels):
model = BertModel(config=config)
model.to(input_ids.device)
model.eval()
sequence_output, pooled_output = model(input_ids, attention_mask=input_mask, token_type_ids=token_type_ids)
sequence_output, pooled_output = model(input_ids, token_type_ids=token_type_ids)
@ -309,7 +313,10 @@ class BertModelTest(CommonTestCases.CommonModelTester):
def test_config(self):
self.config_tester.run_common_tests()
def test_bert_model(self):
def test_bert_model(self, use_cuda=False):
# ^^ This could be a real fixture
if use_cuda:
self.model_tester.device = "cuda"
config_and_inputs = self.model_tester.prepare_config_and_inputs()
self.model_tester.create_and_check_bert_model(*config_and_inputs)