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_2/test_modeling_blip_2.py

@@ -882,6 +882,22 @@ class Blip2ModelIntegrationTest(unittest.TestCase):
         )
         self.assertEqual(generated_text, "it's not a city, it's a beach")
 
+    def test_inference_interpolate_pos_encoding(self):
+        processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
+        model = Blip2ForConditionalGeneration.from_pretrained(
+            "Salesforce/blip2-opt-2.7b", torch_dtype=torch.float16
+        ).to(torch_device)
+        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(), [2, 102, 693, 8, 2335, 15, 5, 4105, 50118])
+        self.assertEqual(generated_text, "a woman and dog on the beach")
+
     def test_inference_opt_batched_beam_search(self):
         processor = Blip2Processor.from_pretrained("Salesforce/blip2-opt-2.7b")
         model = Blip2ForConditionalGeneration.from_pretrained(