[TensorFlow] Adding GroupViT (#18020)

* chore: initial commit

* chore: adding util methods

yet to work on the nn.functional.interpolate port with align_corener=True

* chore: refactor the utils

* used tf.compat.v1.image.resize to align the F.interpolate function
* added type hints to the method signatures
* added references to the gists where one 2 one alignment of torch and tf has been shown

* chore: adding the layers

* chore: porting all the layers from torch to tf

This is the initial draft, nothing is tested yet.

* chore: aligning the layers with reference to tf clip

* chore: aligning the modules

* added demaraction comments
* added copied and adapted from comments

* chore: aligning with CLIP

* chore: wrangling the layers to keep it tf compatible

* chore: aligning the names of the layers for porting

* chore: style changes

* chore: adding docs and inits

* chore: adding tfp dependencis

the code is taken from TAPAS

* chore: initial commit for testing

* chore: aligning the vision embeddings with the vit implementatino

* chore: changing model prefix

* chore: fixing the name of the model and the layer normalization test case

* chore: every test passes but the slow ones

* chore: fix style and integration test

* chore: moving comments below decorators

* chore: make fixup and fix-copies changes

* chore: adding the Vision and Text Model to check_repo

* chore: modifying the prefix name to align it with the torch implementation

* chore: fix typo in configuration

* choer: changing the name of the model variable

* chore: adding segmentation flag

* chore: gante's review

* chore: style refactor

* chore: amy review

* chore: adding shape_list to parts that have been copied from other snippets

* chore: init batchnorm with torch defaults

* chore: adding shape_list to pass the tests

* test fix: adding seed as 0

* set seed

* chore: changing the straight through trick to fix -ve dimensinos

* chore: adding a dimension to the loss

* chore: adding reviewers and contributors names to the docs

* chore: added changes after review

* chore: code quality fixup

* chore: fixing the segmentation snippet

* chore: adding  to the layer calls

* chore: changing int32 to int64 for inputs of serving

* chore: review changes

* chore: style changes

* chore: remove from_pt=True

* fix: repo consistency

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

docs/source/en/model_doc/groupvit.mdx

@@ -26,7 +26,7 @@ Tips:
 - You may specify `output_segmentation=True` in the forward of `GroupViTModel` to get the segmentation logits of input texts. 
 - The quickest way to get started with GroupViT is by checking the [example notebooks](https://github.com/xvjiarui/GroupViT/blob/main/demo/GroupViT_hf_inference_notebook.ipynb) (which showcase zero-shot segmentation inference). One can also check out the [HuggingFace Spaces demo](https://huggingface.co/spaces/xvjiarui/GroupViT) to play with GroupViT. 
 
-This model was contributed by [xvjiarui](https://huggingface.co/xvjiarui).
+This model was contributed by [xvjiarui](https://huggingface.co/xvjiarui). The TensorFlow version was contributed by [ariG23498](https://huggingface.co/ariG23498) with the help of [Yih-Dar SHIEH](https://huggingface.co/ydshieh), [Amy Roberts](https://huggingface.co/amyeroberts), and [Joao Gante](https://huggingface.co/joaogante).
 The original code can be found [here](https://github.com/NVlabs/GroupViT).
 
 
@@ -59,3 +59,20 @@ The original code can be found [here](https://github.com/NVlabs/GroupViT).
 
 [[autodoc]] GroupViTVisionModel
     - forward
+
+## TFGroupViTModel
+
+[[autodoc]] TFGroupViTModel
+    - call
+    - get_text_features
+    - get_image_features
+
+## TFGroupViTTextModel
+
+[[autodoc]] TFGroupViTTextModel
+    - call
+
+## TFGroupViTVisionModel
+
+[[autodoc]] TFGroupViTVisionModel
+    - call