BUG: replace cache_dir wirh local_dir for specify the saving directory

Author: mostafajahanifar

tests/test_utils.py

@@ -1618,21 +1618,25 @@ def test_from_multi_head_dat_type_dict(tmp_path: Path) -> None:
 
 def test_fetch_pretrained_weights(tmp_path: Path) -> None:
     """Test fetching pretrained weights for a model."""
-    file_path = tmp_path / "test_fetch_pretrained_weights.pth"
+    model_name = "mobilenet_v3_small-pcam"
+    file_path = tmp_path / f"{model_name}.pth"
     if file_path.exists():
         file_path.unlink()
 
-    fetch_pretrained_weights(model_name="mobilenet_v3_small-pcam", save_path=file_path)
+    print("tmp_path: ", tmp_path)
+    mosi = fetch_pretrained_weights(model_name="mobilenet_v3_small-pcam", save_path=tmp_path)
+    print("returned path: ", mosi)
+    print("desired path: ", file_path)
+    print(file_path.exists())
     assert file_path.exists()
     assert file_path.stat().st_size > 0
     file_path.unlink()
 
     with pytest.raises(ValueError, match="does not exist"):
-        fetch_pretrained_weights("abc", file_path)
+        fetch_pretrained_weights("abc", tmp_path)
 
     # Test save_path is str
-    file_path_str = str(file_path)
-    file_path = fetch_pretrained_weights("mobilenet_v3_small-pcam", file_path_str)
+    file_path = fetch_pretrained_weights(model_name, str(tmp_path))
     assert Path(file_path).exists()
     assert Path(file_path).stat().st_size > 0
 

tiatoolbox/models/architecture/__init__.py

@@ -33,8 +33,7 @@ def fetch_pretrained_weights(
             Refer to `::py::meth:get_pretrained_model` for all supported
             model names.
         save_path (str | Path):
-            Path to save the weight of the
-          corresponding `model_name`.
+            Path to the directory in which the pretrained weight will be cached.
         overwrite (bool):
             Overwrite existing downloaded weights (force downloading).
 
@@ -60,7 +59,7 @@ def fetch_pretrained_weights(
     return hf_hub_download(
         repo_id="TIACentre/TIAToolbox_pretrained_weights",
         filename=file_name,
-        cache_dir=cache_dir,
+        local_dir=cache_dir,
         force_download=overwrite,
     )
 

tiatoolbox/models/architecture/vanilla.py

@@ -33,7 +33,8 @@ def _get_architecture(
             Name of the architecture (e.g. 'resnet50', 'alexnet').
         weights (str or WeightsEnum):
             Pretrained torchvision model weights to use (get_model_weights).
-            Defaults to "DEFAULT".
+            Defaults is None to avoid downloading ImageNet weights.
+            To initiate the models with ImageNet weights, use "DEFAULT".
         **kwargs (dict):
             Key-word arguments.