Merge branch 'fx_model_test_stable_diffusion' of https://github.com/a…

…nzr299/nncf into fx_model_test_stable_diffusion

tests/torch/fx/test_models.py

@@ -27,6 +27,7 @@
 import torch.utils.data.distributed
 import torchvision.models as models
 from diffusers import StableDiffusionPipeline
+from diffusers import StableDiffusionPipeline
 from torch._export import capture_pre_autograd_graph
 
 from nncf.common.graph.graph import NNCFNodeName
@@ -88,13 +89,19 @@ def get_full_path_to_json(model_json_name: str) -> str:
 
 def get_ref_metatypes_from_json(
     model_name: str, model_metatypes: Dict[NNCFNodeName, Type[OperatorMetatype]], fx_dir: str
+    model_name: str, model_metatypes: Dict[NNCFNodeName, Type[OperatorMetatype]], fx_dir: str
 ) -> Dict[NNCFNodeName, Type[OperatorMetatype]]:
 
     model_json_name = get_json_filename(model_name)
     complete_path = get_full_path_to_json(model_json_name)
 
     json_parent_dir = Path(complete_path).parent
 
+    pipeline_model_dir = fx_dir.split("/")
+    if len(pipeline_model_dir) > 1:
+        json_parent_dir = json_parent_dir / "/".join(pipeline_model_dir[1:])
+        complete_path = json_parent_dir / model_json_name
+
     pipeline_model_dir = fx_dir.split("/")
     if len(pipeline_model_dir) > 1:
         json_parent_dir = json_parent_dir / "/".join(pipeline_model_dir[1:])
@@ -117,6 +124,7 @@ def test_models(test_case: ModelCase):
         model = test_case.model_builder()
         model.to(device)
         model.eval()
+        model.eval()
 
         with torch.no_grad():
             ex_input = torch.ones(test_case.input_shape)