[PyOV] Set inference precision explicitly to fp32 for torchvision tests (#20713)

* Set fp32

* Fix flake

* use properties api

src/bindings/python/tests/test_torchvision_to_ov/test_preprocessor.py

@@ -12,8 +12,10 @@ import torch
 import torch.nn.functional as f
 import torchvision.transforms as transforms
 
+from openvino import Type
 from openvino.runtime import Core, Tensor
 from openvino.tools.mo import convert_model
+from openvino.properties.hint import inference_precision
 
 from openvino.preprocess.torchvision import PreprocessConverter
 
@@ -38,7 +40,8 @@ def _infer_pipelines(test_input, preprocess_pipeline, input_channels=3):
     ov_model = PreprocessConverter.from_torchvision(
         model=ov_model, transform=preprocess_pipeline, input_example=Image.fromarray(test_input.astype("uint8"), "RGB"),
     )
-    ov_model = core.compile_model(ov_model, "CPU")
+    infer_config = {inference_precision: Type.f32}
+    ov_model = core.compile_model(ov_model, "CPU", infer_config)
 
     # Torch results
     torch_input = copy.deepcopy(test_input)