Add DETR (#11653)

* Squash all commits of modeling_detr_v7 branch into one

* Improve docs

* Fix tests

* Style

* Improve docs some more and fix most tests

* Fix slow tests of ViT, DeiT and DETR

* Improve replacement of batch norm

* Restructure timm backbone forward

* Make DetrForSegmentation support any timm backbone

* Fix name of output

* Address most comments by @LysandreJik

* Give better names for variables

* Conditional imports + timm in setup.py

* Address additional comments by @sgugger

* Make style, add require_timm and require_vision to testsé

* Remove train_backbone attribute of DetrConfig, add methods to freeze/unfreeze backbone

* Add png files to fixtures

* Fix type hint

* Add timm to workflows

* Add `BatchNorm2d` to the weight initialization

* Fix retain_grad test

* Replace model checkpoints by Facebook namespace

* Fix name of checkpoint in test

* Add user-friendly message when scipy is not available

* Address most comments by @patrickvonplaten

* Remove return_intermediate_layers attribute of DetrConfig and simplify Joiner

* Better initialization

* Scipy is necessary to get sklearn metrics

* Rename TimmBackbone to DetrTimmConvEncoder and rename DetrJoiner to DetrConvModel

* Make style

* Improve docs and add 2 community notebooks

Co-authored-by: Lysandre <lysandre.debut@reseau.eseo.fr>

src/transformers/testing_utils.py

@@ -39,6 +39,7 @@ from .file_utils import (
     is_sentencepiece_available,
     is_soundfile_availble,
     is_tf_available,
+    is_timm_available,
     is_tokenizers_available,
     is_torch_available,
     is_torch_tpu_available,
@@ -229,6 +230,19 @@ def require_onnx(test_case):
         return test_case
 
 
+def require_timm(test_case):
+    """
+    Decorator marking a test that requires Timm.
+
+    These tests are skipped when Timm isn't installed.
+
+    """
+    if not is_timm_available():
+        return unittest.skip("test requires Timm")(test_case)
+    else:
+        return test_case
+
+
 def require_torch(test_case):
     """
     Decorator marking a test that requires PyTorch.