[PT FE] Retry hf hub model load up to 3 times if http error (openvinotoolkit#25648)

### Details:
 - *item1*
 - *...*

### Tickets:
 - *CVS-143832*

Author: mvafin

tests/model_hub_tests/models_hub_common/utils.py

@@ -1,6 +1,7 @@
 # Copyright (C) 2018-2024 Intel Corporation
 # SPDX-License-Identifier: Apache-2.0
 
+import functools
 import itertools
 import os
 import shutil
@@ -145,3 +146,20 @@ def call_with_timer(timer_label: str, func, args):
 
 def print_stat(s: str, value: float):
     print(s.format(round_num(value)))
+
+
+def retry(max_retries=3, exceptions=(Exception,), delay=None):
+    def retry_decorator(func):
+        @functools.wraps(func)
+        def wrapper(*args, **kwargs):
+            for attempt in range(max_retries):
+                try:
+                    return func(*args, **kwargs)
+                except exceptions as e:
+                    print(f"Attempt {attempt + 1} of {max_retries} failed: {e}")
+                    if attempt < max_retries - 1 and delay is not None:
+                        time.sleep(delay)
+                    else:
+                        raise e
+        return wrapper
+    return retry_decorator

tests/model_hub_tests/pytorch/test_hf_transformers.py

@@ -6,8 +6,9 @@
 import pytest
 import torch
 from huggingface_hub import model_info
+from huggingface_hub.utils import HfHubHTTPError
 from models_hub_common.constants import hf_hub_cache_dir
-from models_hub_common.utils import cleanup_dir
+from models_hub_common.utils import cleanup_dir, retry
 import transformers
 from transformers import AutoConfig, AutoModel, AutoProcessor, AutoTokenizer, AutoFeatureExtractor, AutoModelForTextToWaveform, \
     CLIPFeatureExtractor, XCLIPVisionModel, T5Tokenizer, VisionEncoderDecoderModel, ViTImageProcessor, BlipProcessor, BlipForConditionalGeneration, \
@@ -101,6 +102,7 @@ def setup_class(self):
         self.image = Image.open(requests.get(url, stream=True).raw)
         self.cuda_available, self.gptq_postinit = None, None
 
+    @retry(3, exceptions=(HfHubHTTPError,), delay=1)
     def load_model(self, name, type):
         name_suffix = ''
         if name.find(':') != -1: