Files
HuggingFace_transformer/transformers/tests/modeling_encoder_decoder_test.py
Aymeric Augustin 35401fe50f Remove dependency on pytest for running tests (#2055)
* Switch to plain unittest for skipping slow tests.

Add a RUN_SLOW environment variable for running them.

* Switch to plain unittest for PyTorch dependency.

* Switch to plain unittest for TensorFlow dependency.

* Avoid leaking open files in the test suite.

This prevents spurious warnings when running tests.

* Fix unicode warning on Python 2 when running tests.

The warning was:

    UnicodeWarning: Unicode equal comparison failed to convert both arguments to Unicode - interpreting them as being unequal

* Support running PyTorch tests on a GPU.

Reverts 27e015bd.

* Tests no longer require pytest.

* Make tests pass on cuda
2019-12-06 13:57:38 -05:00

53 lines
1.9 KiB
Python

# coding=utf-8
# Copyright 2018 The Hugging Face Inc. Team
#
# Licensed under the Apache License, Version 2.0 (the "License");
# you may not use this file except in compliance with the License.
# You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing, software
# distributed under the License is distributed on an "AS IS" BASIS,
# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
# See the License for the specific language governing permissions and
# limitations under the License.
import logging
import unittest
from transformers import is_torch_available
from .utils import require_torch, slow
if is_torch_available():
from transformers import BertModel, BertForMaskedLM, Model2Model
from transformers.modeling_bert import BERT_PRETRAINED_MODEL_ARCHIVE_MAP
@require_torch
class EncoderDecoderModelTest(unittest.TestCase):
@slow
def test_model2model_from_pretrained(self):
logging.basicConfig(level=logging.INFO)
for model_name in list(BERT_PRETRAINED_MODEL_ARCHIVE_MAP.keys())[:1]:
model = Model2Model.from_pretrained(model_name)
self.assertIsInstance(model.encoder, BertModel)
self.assertIsInstance(model.decoder, BertForMaskedLM)
self.assertEqual(model.decoder.config.is_decoder, True)
self.assertEqual(model.encoder.config.is_decoder, False)
def test_model2model_from_pretrained_not_bert(self):
logging.basicConfig(level=logging.INFO)
with self.assertRaises(ValueError):
_ = Model2Model.from_pretrained('roberta')
with self.assertRaises(ValueError):
_ = Model2Model.from_pretrained('distilbert')
with self.assertRaises(ValueError):
_ = Model2Model.from_pretrained('does-not-exist')
if __name__ == "__main__":
unittest.main()