Blip dynamic input resolution (#30722)

* blip with interpolated pos encoding

* feat: Add interpolate_pos_encoding option to other models from `BLIP` family.

* include check for textual generated content in tests

tests/models/blip/test_modeling_blip.py

@@ -1381,6 +1381,20 @@ class BlipModelIntegrationTest(unittest.TestCase):
             [30522, 1037, 3861, 1997, 1037, 2450, 1998, 2014, 3899, 2006, 1996, 3509, 102],
         )
 
+    def test_inference_interpolate_pos_encoding(self):
+        model = BlipForConditionalGeneration.from_pretrained("Salesforce/blip-image-captioning-base").to(torch_device)
+        processor = BlipProcessor.from_pretrained("Salesforce/blip-image-captioning-base")
+        processor.image_processor.size = {"height": 500, "width": 500}
+
+        image = prepare_img()
+        inputs = processor(images=image, return_tensors="pt").to(torch_device)
+
+        predictions = model.generate(**inputs, interpolate_pos_encoding=True)
+        generated_text = processor.batch_decode(predictions, skip_special_tokens=True)[0].strip()
+
+        self.assertEqual(predictions[0].tolist(), [30522, 1037, 2450, 3564, 2006, 1996, 3509, 2007, 1037, 3899, 102])
+        self.assertEqual(generated_text, "a woman sitting on the beach with a dog")
+
     def test_inference_vqa(self):
         model = BlipForQuestionAnswering.from_pretrained("Salesforce/blip-vqa-base").to(torch_device)
         processor = BlipProcessor.from_pretrained("Salesforce/blip-vqa-base")