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/auto/test_modeling_flax_auto.py

@@ -0,0 +1,101 @@
+# Copyright 2020 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 AutoConfig, AutoTokenizer, BertConfig, TensorType, is_flax_available
+from transformers.testing_utils import DUMMY_UNKNOWN_IDENTIFIER, require_flax, slow
+
+
+if is_flax_available():
+    import jax
+    from transformers.models.auto.modeling_flax_auto import FlaxAutoModel
+    from transformers.models.bert.modeling_flax_bert import FlaxBertModel
+    from transformers.models.roberta.modeling_flax_roberta import FlaxRobertaModel
+
+
+@require_flax
+class FlaxAutoModelTest(unittest.TestCase):
+    @slow
+    def test_bert_from_pretrained(self):
+        for model_name in ["bert-base-cased", "bert-large-uncased"]:
+            with self.subTest(model_name):
+                config = AutoConfig.from_pretrained(model_name)
+                self.assertIsNotNone(config)
+                self.assertIsInstance(config, BertConfig)
+
+                model = FlaxAutoModel.from_pretrained(model_name)
+                self.assertIsNotNone(model)
+                self.assertIsInstance(model, FlaxBertModel)
+
+    @slow
+    def test_roberta_from_pretrained(self):
+        for model_name in ["roberta-base", "roberta-large"]:
+            with self.subTest(model_name):
+                config = AutoConfig.from_pretrained(model_name)
+                self.assertIsNotNone(config)
+                self.assertIsInstance(config, BertConfig)
+
+                model = FlaxAutoModel.from_pretrained(model_name)
+                self.assertIsNotNone(model)
+                self.assertIsInstance(model, FlaxRobertaModel)
+
+    @slow
+    def test_bert_jax_jit(self):
+        for model_name in ["bert-base-cased", "bert-large-uncased"]:
+            tokenizer = AutoTokenizer.from_pretrained(model_name)
+            model = FlaxBertModel.from_pretrained(model_name)
+            tokens = tokenizer("Do you support jax jitted function?", return_tensors=TensorType.JAX)
+
+            @jax.jit
+            def eval(**kwargs):
+                return model(**kwargs)
+
+            eval(**tokens).block_until_ready()
+
+    @slow
+    def test_roberta_jax_jit(self):
+        for model_name in ["roberta-base", "roberta-large"]:
+            tokenizer = AutoTokenizer.from_pretrained(model_name)
+            model = FlaxRobertaModel.from_pretrained(model_name)
+            tokens = tokenizer("Do you support jax jitted function?", return_tensors=TensorType.JAX)
+
+            @jax.jit
+            def eval(**kwargs):
+                return model(**kwargs)
+
+            eval(**tokens).block_until_ready()
+
+    def test_repo_not_found(self):
+        with self.assertRaisesRegex(
+            EnvironmentError, "bert-base is not a local folder and is not a valid model identifier"
+        ):
+            _ = FlaxAutoModel.from_pretrained("bert-base")
+
+    def test_revision_not_found(self):
+        with self.assertRaisesRegex(
+            EnvironmentError, r"aaaaaa is not a valid git identifier \(branch name, tag name or commit id\)"
+        ):
+            _ = FlaxAutoModel.from_pretrained(DUMMY_UNKNOWN_IDENTIFIER, revision="aaaaaa")
+
+    def test_model_file_not_found(self):
+        with self.assertRaisesRegex(
+            EnvironmentError,
+            "hf-internal-testing/config-no-model does not appear to have a file named flax_model.msgpack",
+        ):
+            _ = FlaxAutoModel.from_pretrained("hf-internal-testing/config-no-model")
+
+    def test_model_from_pt_suggestion(self):
+        with self.assertRaisesRegex(EnvironmentError, "Use `from_pt=True` to load this model"):
+            _ = FlaxAutoModel.from_pretrained("hf-internal-testing/tiny-bert-pt-only")