Backbone add mixin tests (#22542)

* Add out_indices to backbones, deprecate out_features

* Update - can specify both out_features and out_indices but not both

* Add backbone mixin tests

* Test tidy up

* Add test_backbone for convnext

* Remove redefinition of method

* Update for Dinat and Nat backbones

* Update tests

* Smarter indexing

* Add checks on config creation for backbone

* PR comments

tests/models/resnet/test_modeling_resnet.py

@@ -22,6 +22,7 @@ from transformers import ResNetConfig
 from transformers.testing_utils import require_torch, require_vision, slow, torch_device
 from transformers.utils import cached_property, is_torch_available, is_vision_available
 
+from ...test_backbone_common import BackboneTesterMixin
 from ...test_configuration_common import ConfigTester
 from ...test_modeling_common import ModelTesterMixin, floats_tensor, ids_tensor
 from ...test_pipeline_mixin import PipelineTesterMixin
@@ -57,6 +58,7 @@ class ResNetModelTester:
         num_labels=3,
         scope=None,
         out_features=["stage2", "stage3", "stage4"],
+        out_indices=[2, 3, 4],
     ):
         self.parent = parent
         self.batch_size = batch_size
@@ -72,6 +74,7 @@ class ResNetModelTester:
         self.scope = scope
         self.num_stages = len(hidden_sizes)
         self.out_features = out_features
+        self.out_indices = out_indices
 
     def prepare_config_and_inputs(self):
         pixel_values = floats_tensor([self.batch_size, self.num_channels, self.image_size, self.image_size])
@@ -93,6 +96,7 @@ class ResNetModelTester:
             hidden_act=self.hidden_act,
             num_labels=self.num_labels,
             out_features=self.out_features,
+            out_indices=self.out_indices,
         )
 
     def create_and_check_model(self, config, pixel_values, labels):
@@ -323,3 +327,13 @@ class ResNetModelIntegrationTest(unittest.TestCase):
         expected_slice = torch.tensor([-11.1069, -9.7877, -8.3777]).to(torch_device)
 
         self.assertTrue(torch.allclose(outputs.logits[0, :3], expected_slice, atol=1e-4))
+
+
+@require_torch
+class ResNetBackboneTest(BackboneTesterMixin, unittest.TestCase):
+    all_model_classes = (ResNetBackbone,) if is_torch_available() else ()
+    has_attentions = False
+    config_class = ResNetConfig
+
+    def setUp(self):
+        self.model_tester = ResNetModelTester(self)