Convert formatting to use ruff instead of yapf + isort (#26247)

Signed-off-by: Harry Mellor <19981378+hmellor@users.noreply.github.com>

tests/models/test_terratorch.py

@@ -11,32 +11,33 @@ from tests.conftest import VllmRunner
     "model",
     [
         "ibm-nasa-geospatial/Prithvi-EO-2.0-300M-TL-Sen1Floods11",
-        "mgazz/Prithvi_v2_eo_300_tl_unet_agb"
+        "mgazz/Prithvi_v2_eo_300_tl_unet_agb",
     ],
 )
 def test_inference(
     vllm_runner: type[VllmRunner],
     model: str,
 ) -> None:
-
     pixel_values = torch.full((6, 512, 512), 1.0, dtype=torch.float16)
     location_coords = torch.full((1, 2), 1.0, dtype=torch.float16)
-    prompt = dict(prompt_token_ids=[1],
-                  multi_modal_data=dict(pixel_values=pixel_values,
-                                        location_coords=location_coords))
+    prompt = dict(
+        prompt_token_ids=[1],
+        multi_modal_data=dict(
+            pixel_values=pixel_values, location_coords=location_coords
+        ),
+    )
     with vllm_runner(
-            model,
-            runner="pooling",
-            dtype="half",
-            enforce_eager=True,
-            skip_tokenizer_init=True,
-            # Limit the maximum number of sequences to avoid the
-            # test going OOM during the warmup run
-            max_num_seqs=32,
-            default_torch_num_threads=1,
+        model,
+        runner="pooling",
+        dtype="half",
+        enforce_eager=True,
+        skip_tokenizer_init=True,
+        # Limit the maximum number of sequences to avoid the
+        # test going OOM during the warmup run
+        max_num_seqs=32,
+        default_torch_num_threads=1,
     ) as vllm_model:
-
         vllm_output = vllm_model.llm.encode(prompt)
         assert torch.equal(
-            torch.isnan(vllm_output[0].outputs.data).any(),
-            torch.tensor(False))
+            torch.isnan(vllm_output[0].outputs.data).any(), torch.tensor(False)
+        )