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[Tests] fix attention masks in Tests (#6621)

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* fix distilbert

* fix typo
This commit is contained in:
Patrick von Platen
2020-08-20 19:23:47 +02:00
committed by GitHub
parent c9454507cf
commit 505f2d749e
15 changed files with 35 additions and 31 deletions
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4
tests/test_modeling_albert.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -71,7 +71,7 @@ class AlbertModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_bert.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -93,7 +93,7 @@ class BertModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

10
tests/test_modeling_common.py
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@@ -704,9 +704,6 @@ class ModelTesterMixin:
recursive_check(tuple_iterable_value, dict_iterable_value) recursive_check(tuple_iterable_value, dict_iterable_value)
elif tuple_object is None: elif tuple_object is None:
return return
elif torch.isinf(tuple_object).any() and torch.isinf(dict_object).any():
# TODO: (Lysandre) - maybe take a look if that's ok here
return
else: else:
self.assertTrue( self.assertTrue(
torch.allclose(tuple_object, dict_object, atol=1e-5), torch.allclose(tuple_object, dict_object, atol=1e-5),
@@ -937,6 +934,13 @@ def ids_tensor(shape, vocab_size, rng=None, name=None):
return torch.tensor(data=values, dtype=torch.long, device=torch_device).view(shape).contiguous() return torch.tensor(data=values, dtype=torch.long, device=torch_device).view(shape).contiguous()
def random_attention_mask(shape, rng=None, name=None):
attn_mask = ids_tensor(shape, vocab_size=2, rng=None, name=None)
# make sure that at least one token is attended to for each batch
attn_mask[:, -1] = 1
return attn_mask
def floats_tensor(shape, scale=1.0, rng=None, name=None): def floats_tensor(shape, scale=1.0, rng=None, name=None):
"""Creates a random float32 tensor""" """Creates a random float32 tensor"""
if rng is None: if rng is None:

4
tests/test_modeling_ctrl.py
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@@ -19,7 +19,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -60,7 +60,7 @@ class CTRLModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_distilbert.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -89,7 +89,7 @@ if is_torch_available():
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
sequence_labels = None sequence_labels = None
token_labels = None token_labels = None

4
tests/test_modeling_dpr.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -88,7 +88,7 @@ class DPRModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_electra.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -69,7 +69,7 @@ class ElectraModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_flaubert.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -72,7 +72,7 @@ class FlaubertModelTester(object):
def prepare_config_and_inputs(self): 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)
input_mask = ids_tensor([self.batch_size, self.seq_length], 2).float() input_mask = random_attention_mask([self.batch_size, self.seq_length])
input_lengths = None input_lengths = None
if self.use_input_lengths: if self.use_input_lengths:

4
tests/test_modeling_gpt2.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -92,7 +92,7 @@ class GPT2ModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_longformer.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -82,7 +82,7 @@ class LongformerModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_mobilebert.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -94,7 +94,7 @@ class MobileBertModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_reformer.py
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@@ -19,7 +19,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_multigpu, require_torch, slow, torch_device from transformers.testing_utils import require_multigpu, require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -133,7 +133,7 @@ class ReformerModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
choice_labels = None choice_labels = None
if self.use_labels: if self.use_labels:

4
tests/test_modeling_roberta.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor from .test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -71,7 +71,7 @@ class RobertaModelTester:
input_mask = None input_mask = None
if self.use_input_mask: if self.use_input_mask:
input_mask = ids_tensor([self.batch_size, self.seq_length], vocab_size=2) input_mask = random_attention_mask([self.batch_size, self.seq_length])
token_type_ids = None token_type_ids = None
if self.use_token_type_ids: if self.use_token_type_ids:

4
tests/test_modeling_xlm.py
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@@ -20,7 +20,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -73,7 +73,7 @@ class XLMModelTester:
def prepare_config_and_inputs(self): 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)
input_mask = ids_tensor([self.batch_size, self.seq_length], 2).float() input_mask = random_attention_mask([self.batch_size, self.seq_length])
input_lengths = None input_lengths = None
if self.use_input_lengths: if self.use_input_lengths:

4
tests/test_modeling_xlnet.py
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@@ -21,7 +21,7 @@ from transformers import is_torch_available
from transformers.testing_utils import require_torch, slow, torch_device from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester from .test_configuration_common import ConfigTester
from .test_modeling_common import ModelTesterMixin, ids_tensor from .test_modeling_common import ModelTesterMixin, ids_tensor, random_attention_mask
if is_torch_available(): if is_torch_available():
@@ -100,7 +100,7 @@ class XLNetModelTester:
input_ids_1 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size) input_ids_1 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
input_ids_2 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size) input_ids_2 = ids_tensor([self.batch_size, self.seq_length], self.vocab_size)
segment_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size) segment_ids = ids_tensor([self.batch_size, self.seq_length], self.type_vocab_size)
input_mask = ids_tensor([self.batch_size, self.seq_length], 2).float() input_mask = random_attention_mask([self.batch_size, self.seq_length])
input_ids_q = ids_tensor([self.batch_size, self.seq_length + 1], self.vocab_size) input_ids_q = ids_tensor([self.batch_size, self.seq_length + 1], self.vocab_size)
perm_mask = torch.zeros( perm_mask = torch.zeros(