Add MLFLOW_FLATTEN_PARAMS support in MLflowCallback (#17148)

* add support for MLFLOW_FLATTEN_PARAMS

* ensure key is str

* fix style and update warning msg

* Empty commit to trigger CI

* fix bug in check_inits.py

* add unittest for flatten_dict utils

* fix 'NoneType' object is not callable on __del__

* add generic flatten_dict unittest to SPECIAL_MODULE_TO_TEST_MAP

* fix style

tests/utils/test_generic.py

@@ -0,0 +1,45 @@
+# coding=utf-8
+# Copyright 2019-present, the HuggingFace 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 unittest
+
+from transformers.utils import flatten_dict
+
+
+class GenericTester(unittest.TestCase):
+    def test_flatten_dict(self):
+        input_dict = {
+            "task_specific_params": {
+                "summarization": {"length_penalty": 1.0, "max_length": 128, "min_length": 12, "num_beams": 4},
+                "summarization_cnn": {"length_penalty": 2.0, "max_length": 142, "min_length": 56, "num_beams": 4},
+                "summarization_xsum": {"length_penalty": 1.0, "max_length": 62, "min_length": 11, "num_beams": 6},
+            }
+        }
+        expected_dict = {
+            "task_specific_params.summarization.length_penalty": 1.0,
+            "task_specific_params.summarization.max_length": 128,
+            "task_specific_params.summarization.min_length": 12,
+            "task_specific_params.summarization.num_beams": 4,
+            "task_specific_params.summarization_cnn.length_penalty": 2.0,
+            "task_specific_params.summarization_cnn.max_length": 142,
+            "task_specific_params.summarization_cnn.min_length": 56,
+            "task_specific_params.summarization_cnn.num_beams": 4,
+            "task_specific_params.summarization_xsum.length_penalty": 1.0,
+            "task_specific_params.summarization_xsum.max_length": 62,
+            "task_specific_params.summarization_xsum.min_length": 11,
+            "task_specific_params.summarization_xsum.num_beams": 6,
+        }
+
+        self.assertEqual(flatten_dict(input_dict), expected_dict)