Update on "Add preprocess to ci"

1. Run `test_preprocess.py` in ci.
2. Refactor `test_preprocess.py` by creating the model artifacts (eager, exported, et) once and re-use them on different inputs (previously, create model artifacts for each test).

Test Plan:
```
pytest -c /dev/null -v -n auto examples/models/llama3_2_vision/preprocess/
```

[ghstack-poisoned]

Author: lucylq

examples/models/llama3_2_vision/preprocess/test_preprocess.py

@@ -237,7 +237,7 @@ def run_preprocess(
             image_tensor, inscribed_size, best_resolution
         )
         eager_ar = eager_ar.tolist()
-        assert torch.allclose(reference_image, eager_image)
+        assert torch.allclose(reference_image, eager_image, rtol=1e-4, atol=1e-4)
         assert (
             reference_ar == eager_ar
         ), f"Eager model: expected {reference_ar} but got {eager_ar}"
@@ -248,7 +248,7 @@ def run_preprocess(
             image_tensor, inscribed_size, best_resolution
         )
         exported_ar = exported_ar.tolist()
-        assert torch.allclose(reference_image, exported_image)
+        assert torch.allclose(reference_image, exported_image, rtol=1e-4, atol=1e-4)
         assert (
             reference_ar == exported_ar
         ), f"Exported model: expected {reference_ar} but got {exported_ar}"
@@ -259,7 +259,7 @@ def run_preprocess(
         et_image, et_ar = executorch_module.forward(
             (image_tensor, inscribed_size, best_resolution)
         )
-        assert torch.allclose(reference_image, et_image)
+        assert torch.allclose(reference_image, et_image, rtol=1e-4, atol=1e-4)
         assert (
             reference_ar == et_ar.tolist()
         ), f"Executorch model: expected {reference_ar} but got {et_ar.tolist()}"