Mark models according to last validation and fix some problems in models (#20324)

* Mark models according to last validation and fix some problems in models

* Update tests/model_hub_tests/torch_tests/hf_transformers_models

tests/model_hub_tests/torch_tests/detectron2_models

@@ -1,4 +1,4 @@
-COCO-Detection/fast_rcnn_R_50_FPN_1x,none
+COCO-Detection/fast_rcnn_R_50_FPN_1x,none,xfail,Tracing problem
 COCO-Detection/faster_rcnn_R_101_C4_3x,none
 COCO-Detection/faster_rcnn_R_101_DC5_3x,none
 COCO-Detection/faster_rcnn_R_101_FPN_3x,none

tests/model_hub_tests/torch_tests/hf_transformers_models

@@ -3,7 +3,7 @@ abcp4/mymodel-test,mymodel,skip,Load problem
 abeja/gpt-neox-japanese-2.7b,gpt_neox_japanese
 acl-submission-anonym/EAM-spectral,examuse,skip,Load problem
 adalbertojunior/modular-test,modular,skip,Load problem
-aerner/lm-v2,open-llama
+aerner/lm-v2,open-llama,xfail,Example input problem
 afonsosamarques/ardt-vanilla-combo_train_hopper_v2-2508_1336-33,decision_transformer,xfail,Tracing problem
 aihijo/gec-zh-gector-bert-large,gector,skip,Load problem
 albert-base-v2,albert
@@ -21,7 +21,7 @@ ArthurZ/jukebox-vqvae,jukebox_vqvae,skip,Load problem
 ArthurZ/persimmon-8b-base,persimmon,skip,Load problem
 ashishpatel26/span-marker-bert-base-fewnerd-coarse-super,span-marker,skip,Load problem
 asi/albert-act-tiny,albert_act,skip,Load problem
-BAAI/AltCLIP,altclip,xfail,Unsupported op aten::numpy_T
+BAAI/AltCLIP,altclip
 BAAI/AquilaCode-py,aquila,skip,Load problem
 bana513/opennmt-translator-en-hu,opennmt-translator,skip,Load problem
 benjamin/wtp-bert-mini,bert-char,skip,Load problem
@@ -79,7 +79,7 @@ facebook/musicgen-small,musicgen,skip,Load problem
 facebook/opt-125m,opt
 facebook/rag-token-nq,rag,skip,Load problem
 facebook/sam-vit-large,sam,xfail,No node with name original_sizes
-facebook/timesformer-base-finetuned-k400,timesformer,xfail,Shape inference of Add node failed: Eltwise shape infer input shapes dim index: 1 mismatch
+facebook/timesformer-base-finetuned-k400,timesformer
 facebook/vit-mae-base,vit_mae,xfail,Accuracy validation failed
 facebook/wmt19-ru-en,fsmt,xfail,Tracing problem
 facebook/xlm-roberta-xl,xlm-roberta-xl
@@ -199,7 +199,7 @@ kiddothe2b/hierarchical-transformer-base-4096-v2,hat,skip,Load problem
 k-l-lambda/clip-text-generator,clip_text_generator,skip,Load problem
 k-l-lambda/stable-diffusion-v1-4-inv-embed,inv_word_embed,skip,Load problem
 KoboldAI/fairseq-dense-13B-Janeway,xglm,skip,Large Model
-konverner/qdq-camembert-apolliner,qdqbert
+konverner/qdq-camembert-apolliner,qdqbert,xfail,Repository not found
 krasserm/perceiver-ar-clm-base,perceiver-ar-causal-language-model,skip,Load problem
 krasserm/perceiver-ar-sam-giant-midi,perceiver-ar-symbolic-audio-model,skip,Load problem
 krasserm/perceiver-io-img-clf,perceiver-io-image-classifier,skip,Load problem
@@ -309,7 +309,7 @@ regisss/bridgetower-newyorker-a100-8x,bridgetower
 rinna/japanese-cloob-vit-b-16,cloob,skip,Load problem
 Rocketknight1/tiny-random-falcon-7b,falcon
 RUCAIBox/mass-base-uncased,mass,skip,Load problem
-RWKV/rwkv-4-169m-pile,rwkv,xfail,Unsupported op aten::maximum
+RWKV/rwkv-4-169m-pile,rwkv
 sahasrarjn/interbert,BERT,skip,Load problem
 saibo/genkalm-medium-gpt2,genkalm,skip,Load problem
 SajjadAyoubi/clip-fa-vision,clip_vision_model

tests/model_hub_tests/torch_tests/test_detectron2.py

@@ -20,7 +20,7 @@ class TestDetectron2ConvertModel(TestConvertModel):
 
     def load_model(self, model_name, model_link):
         from detectron2 import model_zoo, export
-        from detectron2.modeling import build_model
+        from detectron2.modeling import build_model, PanopticFPN
         from detectron2.checkpoint import DetectionCheckpointer
         from detectron2.config import CfgNode
         import torchvision.transforms as transforms
@@ -32,13 +32,23 @@ class TestDetectron2ConvertModel(TestConvertModel):
         assert isinstance(cfg, CfgNode), "Unexpected config"
         cfg.MODEL.DEVICE = "cpu"
         model = build_model(cfg)
-        DetectionCheckpointer(model, save_to_disk=False).load(cfg.MODEL.WEIGHTS)
+        DetectionCheckpointer(
-        
+            model, save_to_disk=False).load(cfg.MODEL.WEIGHTS)
+
         model.eval()
         inputs = [{"image": image,
                    "height": torch.tensor(image.shape[1]),
                    "width": torch.tensor(image.shape[2])}]
-        adapter = export.TracingAdapter(model, inputs)
+        # https://github.com/facebookresearch/detectron2/blob/4e80df1e58901557e2824ce3b488d30209a9be33/tools/deploy/export_model.py#L123
+        # This is done only for Panoptic models, but it may be incorrect to do that, because one of outputs of panoptic model is getting lost
+        if isinstance(model, PanopticFPN):
+            def inference(model, inputs):
+                # use do_postprocess=False so it returns ROI mask
+                inst = model.inference(inputs, do_postprocess=False)[0]
+                return [{"instances": inst}]
+        else:
+            inference = None  # assume that we just call the model directly
+        adapter = export.TracingAdapter(model, inputs, inference)
 
         self.example = adapter.flattened_inputs
         return adapter
@@ -75,7 +85,8 @@ class TestDetectron2ConvertModel(TestConvertModel):
             cur_fw_res = fw_outputs[i]
             cur_ov_res = ov_outputs[i]
             l = min(len(cur_fw_res), len(cur_ov_res))
-            assert l > 0 or len(cur_fw_res) == len(cur_ov_res), "No boxes were selected."
+            assert l > 0 or len(cur_fw_res) == len(
+                cur_ov_res), "No boxes were selected."
             print(f"fw_re: {cur_fw_res};\n ov_res: {cur_ov_res}")
             is_ok = compare_two_tensors(cur_ov_res[:l], cur_fw_res[:l], fw_eps)
         assert is_ok, "Accuracy validation failed"
@@ -86,8 +97,8 @@ class TestDetectron2ConvertModel(TestConvertModel):
     def test_detectron2_precommit(self, name, type, mark, reason, ie_device):
         self.run(name, None, ie_device)
 
-    @pytest.mark.parametrize("name,type,mark,reason",
+    @pytest.mark.parametrize("name",
-                             get_models_list(os.path.join(os.path.dirname(__file__), "detectron2_models")))
+                             [pytest.param(n, marks=pytest.mark.xfail(reason=r)) if m == "xfail" else n for n, _, m, r in get_models_list(os.path.join(os.path.dirname(__file__), "detectron2_models"))])
     @pytest.mark.nightly
-    def test_detectron2_all_models(self, name, type, mark, reason, ie_device):
+    def test_detectron2_all_models(self, name, ie_device):
         self.run(name, None, ie_device)

tests/model_hub_tests/torch_tests/test_torchvision_models.py

@@ -114,7 +114,7 @@ class TestTorchHubConvertModel(TestConvertModel):
         self.run(model_name, None, ie_device)
 
     @pytest.mark.parametrize("name",
-                             [pytest.param(n, marks=pytest.mark.xfail) if m == "xfail" else n for n, _, m, r in get_models_list(os.path.join(os.path.dirname(__file__), "torchvision_models"))])
+                             [pytest.param(n, marks=pytest.mark.xfail(reason=r)) if m == "xfail" else n for n, _, m, r in get_models_list(os.path.join(os.path.dirname(__file__), "torchvision_models"))])
     @pytest.mark.nightly
     def test_convert_model_all_models(self, name, ie_device):
         self.run(name, None, ie_device)