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Add support for multiple models for one config in auto classes (#11150)

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* Add support for multiple models for one config in auto classes

* Use get_values everywhere

* Prettier doc
This commit is contained in:
Sylvain Gugger
2021-04-08 18:41:36 -04:00
committed by GitHub
parent 97ccf67bb3
commit ba8b1f4754
26 changed files with 188 additions and 72 deletions
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5
tests/test_modeling_lxmert.py
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@@ -18,6 +18,7 @@ import copy
import unittest
from transformers import is_torch_available
from transformers.models.auto import get_values
from transformers.testing_utils import require_torch, slow, torch_device
from .test_configuration_common import ConfigTester
@@ -532,11 +533,11 @@ class LxmertModelTest(ModelTesterMixin, unittest.TestCase):
inputs_dict = copy.deepcopy(inputs_dict)
if return_labels:
if model_class in MODEL_FOR_QUESTION_ANSWERING_MAPPING.values():
if model_class in get_values(MODEL_FOR_QUESTION_ANSWERING_MAPPING):
inputs_dict["labels"] = torch.zeros(
self.model_tester.batch_size, dtype=torch.long, device=torch_device
)
elif model_class in MODEL_FOR_PRETRAINING_MAPPING.values():
elif model_class in get_values(MODEL_FOR_PRETRAINING_MAPPING):
# special case for models like BERT that use multi-loss training for PreTraining
inputs_dict["labels"] = torch.zeros(
(self.model_tester.batch_size, self.model_tester.seq_length), dtype=torch.long, device=torch_device