Make HF interface compatible

hf_model.py

@@ -124,14 +124,38 @@ class RADIOModel(PreTrainedModel):
     def input_conditioner(self) -> InputConditioner:
         return self.radio_model.input_conditioner
 
-    @input_conditioner.setter
-    def input_conditioner(self, v: InputConditioner):
-        self.radio_model.input_conditioner = v
+    @property
+    def num_summary_tokens(self) -> int:
+        return self.radio_model.num_summary_tokens
+
+    @property
+    def patch_size(self) -> int:
+        return self.radio_model.patch_size
+
+    @property
+    def max_resolution(self) -> int:
+        return self.radio_model.max_resolution
+
+    @property
+    def preferred_resolution(self) -> Resolution:
+        return self.radio_model.preferred_resolution
+
+    @property
+    def window_size(self) -> int:
+        return self.radio_model.window_size
+
+    @property
+    def min_resolution_step(self) -> int:
+        return self.radio_model.min_resolution_step
 
     def make_preprocessor_external(self) -> Callable[[torch.Tensor], torch.Tensor]:
-        ret = self.input_conditioner
-        self.input_conditioner = nn.Identity()
-        return ret
+        return self.radio_model.make_preprocessor_external()
+
+    def get_nearest_supported_resolution(self, height: int, width: int) -> Resolution:
+        return self.radio_model.get_nearest_supported_resolution(height, width)
+
+    def switch_to_deploy(self):
+        return self.radio_model.switch_to_deploy()
 
     def forward(self, x: torch.Tensor):
         return self.radio_model.forward(x)