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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

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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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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()