Adding the LXMERT pretraining model (MultiModal languageXvision) to HuggingFace's suite of models (#5793)

* added template files for LXMERT and competed the configuration_lxmert.py

* added modeling, tokization, testing, and finishing touched for lxmert [yet to be tested]

* added model card for lxmert

* cleaning up lxmert code

* Update src/transformers/modeling_lxmert.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_tf_lxmert.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_tf_lxmert.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/modeling_lxmert.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* tested torch lxmert, changed documtention, updated outputs, and other small fixes

* Update src/transformers/convert_pytorch_checkpoint_to_tf2.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/convert_pytorch_checkpoint_to_tf2.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* Update src/transformers/convert_pytorch_checkpoint_to_tf2.py

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>

* renaming, other small issues, did not change TF code in this commit

* added lxmert question answering model in pytorch

* added capability to edit number of qa labels for lxmert

* made answer optional for lxmert question answering

* add option to return hidden_states for lxmert

* changed default qa labels for lxmert

* changed config archive path

* squshing 3 commits: merged UI + testing improvments + more UI and testing

* changed some variable names for lxmert

* TF LXMERT

* Various fixes to LXMERT

* Final touches to LXMERT

* AutoTokenizer order

* Add LXMERT to index.rst and README.md

* Merge commit test fixes + Style update

* TensorFlow 2.3.0 sequential model changes variable names

Remove inherited test

* Update src/transformers/modeling_tf_pytorch_utils.py

* Update docs/source/model_doc/lxmert.rst

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update docs/source/model_doc/lxmert.rst

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* Update src/transformers/modeling_tf_lxmert.py

Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

* added suggestions

* Fixes

* Final fixes for TF model

* Fix docs

Co-authored-by: Lysandre Debut <lysandre@huggingface.co>
Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>
Co-authored-by: Sylvain Gugger <35901082+sgugger@users.noreply.github.com>

model_cards/uncnlp/lxmert-base-uncased/LICENSE

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+MIT License
+
+Copyright (c) 2019 Hao Tan
+
+Permission is hereby granted, free of charge, to any person obtaining a copy
+of this software and associated documentation files (the "Software"), to deal
+in the Software without restriction, including without limitation the rights
+to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
+copies of the Software, and to permit persons to whom the Software is
+furnished to do so, subject to the following conditions:
+
+The above copyright notice and this permission notice shall be included in all
+copies or substantial portions of the Software.
+
+THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
+IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
+FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
+AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
+LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
+OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
+SOFTWARE.

model_cards/uncnlp/lxmert-base-uncased/README.md

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+# LXMERT
+
+## Model Description
+
+[LXMERT](https://arxiv.org/abs/1908.07490) is a pre-trained multimodal transformer. The model takes an image and a sentence as input and compute cross-modal representions. The model is converted from [LXMERT github](https://github.com/airsplay/lxmert) by [Antonio Mendoza](https://avmendoza.info/) and is authored by [Hao Tan](https://www.cs.unc.edu/~airsplay/).
+
+![](./lxmert_model-1.jpg?raw=True)
+
+## Usage
+
+
+## Training Data and Prodcedure
+The model is jointly trained on multiple vision-and-language datasets.
+We included two image captioning datsets (i.e., [MS COCO](http://cocodataset.org/#home), [Visual Genome](https://visualgenome.org/)) and three image-question answering datasets (i.e.,  [VQA](https://visualqa.org/), [GQA](https://cs.stanford.edu/people/dorarad/gqa/), [VG QA](https://github.com/yukezhu/visual7w-toolkit)). The model is pre-trained on the above datasets  for 20 epochs (roughly 670K iterations with batch size 256), which takes around 8 days on 4 Titan V cards. The details of training could be found in the [LXMERT paper](https://arxiv.org/pdf/1908.07490.pdf).
+
+## Eval Results
+| Split            | [VQA](https://visualqa.org/)     | [GQA](https://cs.stanford.edu/people/dorarad/gqa/)     | [NLVR2](http://lil.nlp.cornell.edu/nlvr/)  |
+|-----------       |:----:   |:---:    |:------:|
+| Local Validation | 69.90%  | 59.80%  | 74.95% |
+| Test-Dev         | 72.42%  | 60.00%  | 74.45% (Test-P) |
+| Test-Standard    | 72.54%  | 60.33%  | 76.18% (Test-U) |
+
+
+## Reference
+```bibtex
+@inproceedings{tan2019lxmert,
+  title={LXMERT: Learning Cross-Modality Encoder Representations from Transformers},
+  author={Tan, Hao and Bansal, Mohit},
+  booktitle={Proceedings of the 2019 Conference on Empirical Methods in Natural Language Processing},
+  year={2019}
+}
+```
+
+