Save code of registered custom models (#15379)

* Allow dynamic modules to use relative imports

* Work for configs

* Fix last merge conflict

* Save code of registered custom objects

* Map strings to strings

* Fix test

* Add tokenizer

* Rework tests

* Tests

* Ignore fixtures py files for tests

* Tokenizer test + fix collection

* With full path

* Rework integration

* Fix typo

* Remove changes in conftest

* Test for tokenizers

* Add documentation

* Update docs/source/custom_models.mdx
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Add file structure and file content

* Add more doc

* Style

* Update docs/source/custom_models.mdx
Co-authored-by: Suraj Patil <surajp815@gmail.com>

* Address review comments
Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Suraj Patil <surajp815@gmail.com>

utils/test_module/custom_modeling.py

+import torch
+
+from transformers import PreTrainedModel
+
+from .custom_configuration import CustomConfig
+
+
+class CustomModel(PreTrainedModel):
+    config_class = CustomConfig
+    base_model_prefix = "custom"
+
+    def __init__(self, config):
+        super().__init__(config)
+        self.linear = torch.nn.Linear(config.hidden_size, config.hidden_size)
+
+    def forward(self, x):
+        return self.linear(x)
+
+    def _init_weights(self, module):
+        pass

utils/test_module/custom_tokenization.py

+from transformers import BertTokenizer
+
+
+class CustomTokenizer(BertTokenizer):
+    pass

utils/test_module/custom_tokenization_fast.py

+from transformers import BertTokenizerFast
+
+from .custom_tokenization import CustomTokenizer
+
+
+class CustomTokenizerFast(BertTokenizerFast):
+    slow_tokenizer_class = CustomTokenizer
+    pass