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Fix ignore_mismatched_sizes (#14085)

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* Fix

* Style

* Name

* Fix tests

* Style

* Remove embed sizes checking

* Disable some tests

* Fix

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This commit is contained in:
Li-Huai (Allan) Lin
2021-10-22 00:31:29 +08:00
committed by GitHub
parent e03544a138
commit 234cfefbb0
9 changed files with 64 additions and 6 deletions
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1
tests/test_modeling_canine.py
View File

@@ -220,6 +220,7 @@ class CanineModelTest(ModelTesterMixin, unittest.TestCase):
)
test_torchscript = False
test_mismatched_shapes = False
test_resize_embeddings = False
test_pruning = False

22
tests/test_modeling_common.py
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@@ -98,6 +98,7 @@ class ModelTesterMixin:
test_resize_embeddings = True
test_resize_position_embeddings = False
test_head_masking = True
test_mismatched_shapes = True
test_missing_keys = True
test_model_parallel = False
is_encoder_decoder = False
@@ -1638,6 +1639,8 @@ class ModelTesterMixin:
loss.backward()
def test_load_with_mismatched_shapes(self):
if not self.test_mismatched_shapes:
return
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
@@ -1650,22 +1653,35 @@ class ModelTesterMixin:
model.save_pretrained(tmp_dir)
# Fails when we don't set ignore_mismatched_sizes=True
with self.assertRaises(RuntimeError) as e:
print(type(e))
with self.assertRaises(RuntimeError):
new_model = AutoModelForSequenceClassification.from_pretrained(tmp_dir, num_labels=42)
with self.assertRaises(RuntimeError):
new_model_without_prefix = AutoModel.from_pretrained(tmp_dir, vocab_size=10)
logger = logging.get_logger("transformers.modeling_utils")
with CaptureLogger(logger) as cl:
new_model = AutoModelForSequenceClassification.from_pretrained(
tmp_dir, num_labels=42, ignore_mismatched_sizes=True
)
self.assertIn("the shapes did not match", cl.out)
new_model.to(torch_device)
inputs = self._prepare_for_class(inputs_dict, model_class)
logits = new_model(**inputs).logits
self.assertEqual(logits.shape[1], 42)
with CaptureLogger(logger) as cl:
new_model_without_prefix = AutoModel.from_pretrained(
tmp_dir, vocab_size=10, ignore_mismatched_sizes=True
)
self.assertIn("the shapes did not match", cl.out)
input_ids = ids_tensor((2, 8), 10)
new_model_without_prefix.to(torch_device)
if self.is_encoder_decoder:
new_model_without_prefix(input_ids, decoder_input_ids=input_ids)
else:
new_model_without_prefix(input_ids)
global_rng = random.Random()

1
tests/test_modeling_flax_big_bird.py
View File

@@ -149,6 +149,7 @@ class FlaxBigBirdModelTest(FlaxModelTesterMixin, unittest.TestCase):
)
test_attn_probs = False
test_mismatched_shapes = False
def setUp(self):
self.model_tester = FlaxBigBirdModelTester(self)

17
tests/test_modeling_flax_common.py
View File

@@ -49,6 +49,7 @@ if is_flax_available():
FLAX_MODEL_FOR_QUESTION_ANSWERING_MAPPING,
FLAX_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
FLAX_MODEL_MAPPING,
FlaxAutoModel,
FlaxAutoModelForSequenceClassification,
FlaxBertModel,
)
@@ -116,6 +117,7 @@ def random_attention_mask(shape, rng=None):
class FlaxModelTesterMixin:
model_tester = None
all_model_classes = ()
test_mismatched_shapes = True
is_encoder_decoder = False
def _prepare_for_class(self, inputs_dict, model_class):
@@ -579,6 +581,8 @@ class FlaxModelTesterMixin:
)
def test_load_with_mismatched_shapes(self):
if not self.test_mismatched_shapes:
return
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
@@ -593,6 +597,8 @@ class FlaxModelTesterMixin:
# Fails when we don't set ignore_mismatched_sizes=True
with self.assertRaises(ValueError):
new_model = FlaxAutoModelForSequenceClassification.from_pretrained(tmp_dir, num_labels=42)
with self.assertRaises(ValueError):
new_model_without_prefix = FlaxAutoModel.from_pretrained(tmp_dir, vocab_size=10)
logger = logging.get_logger("transformers.modeling_flax_utils")
with CaptureLogger(logger) as cl:
@@ -604,6 +610,17 @@ class FlaxModelTesterMixin:
logits = new_model(**inputs_dict)["logits"]
self.assertEqual(logits.shape[1], 42)
with CaptureLogger(logger) as cl:
new_model_without_prefix = FlaxAutoModel.from_pretrained(
tmp_dir, vocab_size=10, ignore_mismatched_sizes=True
)
self.assertIn("the shapes did not match", cl.out)
input_ids = ids_tensor((2, 8), 10)
if self.is_encoder_decoder:
new_model_without_prefix(input_ids, decoder_input_ids=input_ids)
else:
new_model_without_prefix(input_ids)
@require_flax
@is_staging_test

1
tests/test_modeling_layoutlmv2.py
View File

@@ -260,6 +260,7 @@ class LayoutLMv2ModelTest(ModelTesterMixin, unittest.TestCase):
test_pruning = False
test_torchscript = False
test_mismatched_shapes = False
all_model_classes = (
(

20
tests/test_modeling_tf_common.py
View File

@@ -59,6 +59,7 @@ if is_tf_available():
TF_MODEL_FOR_SEQUENCE_CLASSIFICATION_MAPPING,
TF_MODEL_FOR_TOKEN_CLASSIFICATION_MAPPING,
BertConfig,
TFAutoModel,
TFAutoModelForSequenceClassification,
TFBertModel,
TFSharedEmbeddings,
@@ -104,6 +105,7 @@ class TFModelTesterMixin:
model_tester = None
all_model_classes = ()
all_generative_model_classes = ()
test_mismatched_shapes = True
test_resize_embeddings = True
test_head_masking = True
is_encoder_decoder = False
@@ -1312,6 +1314,8 @@ class TFModelTesterMixin:
self.assertEqual(sum([tf.reduce_sum(w).numpy() for w in attn_weights]), 0.0)
def test_load_with_mismatched_shapes(self):
if not self.test_mismatched_shapes:
return
config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
for model_class in self.all_model_classes:
@@ -1328,6 +1332,8 @@ class TFModelTesterMixin:
# Fails when we don't set ignore_mismatched_sizes=True
with self.assertRaises(ValueError):
new_model = TFAutoModelForSequenceClassification.from_pretrained(tmp_dir, num_labels=42)
with self.assertRaises(ValueError):
new_model_without_prefix = TFAutoModel.from_pretrained(tmp_dir, vocab_size=10)
logger = logging.get_logger("transformers.modeling_tf_utils")
with CaptureLogger(logger) as cl:
@@ -1339,6 +1345,20 @@ class TFModelTesterMixin:
logits = new_model(**inputs).logits
self.assertEqual(logits.shape[1], 42)
with CaptureLogger(logger) as cl:
new_model_without_prefix = TFAutoModel.from_pretrained(
tmp_dir, vocab_size=10, ignore_mismatched_sizes=True
)
self.assertIn("the shapes did not match", cl.out)
# Although Tf models always have a prefix pointing to `MainLayer`,
# we still add this "without prefix" test to keep a consistency between tf and pt tests.
input_ids = ids_tensor((2, 8), 10)
if self.is_encoder_decoder:
new_model_without_prefix(input_ids, decoder_input_ids=input_ids)
else:
new_model_without_prefix(input_ids)
def _generate_random_bad_tokens(self, num_bad_tokens, model):
# special tokens cannot be bad tokens
special_tokens = []

1
tests/test_modeling_tf_transfo_xl.py
View File

@@ -165,6 +165,7 @@ class TFTransfoXLModelTest(TFModelTesterMixin, unittest.TestCase):
test_resize_embeddings = False
test_head_masking = False
test_onnx = False
test_mismatched_shapes = False
def setUp(self):
self.model_tester = TFTransfoXLModelTester(self)

1
tests/test_modeling_transfo_xl.py
View File

@@ -180,6 +180,7 @@ class TransfoXLModelTest(ModelTesterMixin, GenerationTesterMixin, unittest.TestC
test_pruning = False
test_torchscript = False
test_resize_embeddings = True
test_mismatched_shapes = False
def check_cutoffs_and_n_token(
self, copied_cutoffs, layer, model_embed, model, model_class, resized_value, vocab_size