Move test model folders (#17034)

* move test model folders (TODO: fix imports and others)

* fix (potentially partially) imports (in model test modules)

* fix (potentially partially) imports (in tokenization test modules)

* fix (potentially partially) imports (in feature extraction test modules)

* fix import utils.test_modeling_tf_core

* fix path ../fixtures/

* fix imports about generation.test_generation_flax_utils

* fix more imports

* fix fixture path

* fix get_test_dir

* update module_to_test_file

* fix get_tests_dir from wrong transformers.utils

* update config.yml (CircleCI)

* fix style

* remove missing imports

* update new model script

* update check_repo

* update SPECIAL_MODULE_TO_TEST_MAP

* fix style

* add __init__

* update self-scheduled

* fix add_new_model scripts

* check one way to get location back

* python setup.py build install

* fix import in test auto

* update self-scheduled.yml

* update slack notification script

* Add comments about artifact names

* fix for yolos

Co-authored-by: ydshieh <ydshieh@users.noreply.github.com>

tests/models/mt5/test_modeling_flax_mt5.py

@@ -0,0 +1,61 @@
+# Copyright 2021 The HuggingFace Team. All rights reserved.
+#
+# 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 unittest
+
+from transformers import is_flax_available
+from transformers.testing_utils import require_flax, require_sentencepiece, require_tokenizers, require_torch, slow
+
+
+if is_flax_available():
+    import optax
+    from flax.training.common_utils import onehot
+    from transformers import AutoTokenizer, FlaxMT5ForConditionalGeneration
+    from transformers.models.t5.modeling_flax_t5 import shift_tokens_right
+
+
+@require_torch
+@require_sentencepiece
+@require_tokenizers
+@require_flax
+class MT5IntegrationTest(unittest.TestCase):
+    @slow
+    def test_small_integration_test(self):
+        """
+        For comparision run:
+        >>> import t5  # pip install t5==0.7.1
+        >>> from t5.data.sentencepiece_vocabulary import SentencePieceVocabulary
+
+        >>> path_to_mtf_small_mt5_checkpoint = '<fill_in>'
+        >>> path_to_mtf_small_mt5_spm_model_path = '<fill_in>'
+        >>> t5_model = t5.models.MtfModel(model_dir=path_to_mtf_small_mt5_checkpoint, batch_size=1, tpu=None)
+        >>> vocab = SentencePieceVocabulary(path_to_mtf_small_mt5_spm_model_path)
+        >>> score = t5_model.score(inputs=["Hello there"], targets=["Hi I am"], vocabulary=vocab)
+        """
+
+        model = FlaxMT5ForConditionalGeneration.from_pretrained("google/mt5-small")
+        tokenizer = AutoTokenizer.from_pretrained("google/mt5-small")
+
+        input_ids = tokenizer("Hello there", return_tensors="np").input_ids
+        labels = tokenizer("Hi I am", return_tensors="np").input_ids
+
+        decoder_input_ids = shift_tokens_right(labels, model.config.pad_token_id, model.config.decoder_start_token_id)
+
+        logits = model(input_ids, decoder_input_ids=decoder_input_ids).logits
+        loss = optax.softmax_cross_entropy(logits, onehot(labels, logits.shape[-1])).mean()
+
+        mtf_score = -(labels.shape[-1] * loss.item())
+
+        EXPECTED_SCORE = -84.9127
+        self.assertTrue(abs(mtf_score - EXPECTED_SCORE) < 1e-4)