Delete all mentions of Model2Model (#3019)

tests/test_modeling_encoder_decoder.py

@@ -1,50 +0,0 @@
-# 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")