Enable HF pretrained backbones (#31145)

* Enable load HF or tim backbone checkpoints

* Fix up

* Fix test - pass in proper out_indices

* Update docs

* Fix tvp tests

* Fix doc examples

* Fix doc examples

* Try to resolve DPT backbone param init

* Don't conditionally set to None

* Add condition based on whether backbone is defined

* Address review comments

tests/models/dpt/test_modeling_dpt.py

@@ -276,6 +276,34 @@ class DPTModelTest(ModelTesterMixin, PipelineTesterMixin, unittest.TestCase):
                         msg=f"Parameter {name} of model {model_class} seems not properly initialized",
                     )
 
+    def test_backbone_selection(self):
+        def _validate_backbone_init():
+            for model_class in self.all_model_classes:
+                model = model_class(config)
+                model.to(torch_device)
+                model.eval()
+
+                if model.__class__.__name__ == "DPTForDepthEstimation":
+                    # Confirm out_indices propogated to backbone
+                    self.assertEqual(len(model.backbone.out_indices), 2)
+
+        config, inputs_dict = self.model_tester.prepare_config_and_inputs_for_common()
+        config.use_pretrained_backbone = True
+        config.backbone_config = None
+        config.backbone_kwargs = {"out_indices": [-2, -1]}
+        # Force load_backbone path
+        config.is_hybrid = False
+
+        # Load a timm backbone
+        config.backbone = "resnet18"
+        config.use_timm_backbone = True
+        _validate_backbone_init()
+
+        # Load a HF backbone
+        config.backbone = "facebook/dinov2-small"
+        config.use_timm_backbone = False
+        _validate_backbone_init()
+
     @slow
     def test_model_from_pretrained(self):
         model_name = "Intel/dpt-large"