Merge branch 'develop' into feature-extractor-example

Author: adamshephard

tests/test_patch_extraction.py

@@ -663,3 +663,23 @@ def test_mask_based_patch_extractor_ndpi(
     len_region1 = len(patches)
 
     assert len_all > len_region2 > len_region1
+
+
+def test_invalid_points_type() -> None:
+    """Test invalid locations_list type for PointsPatchExtractor."""
+    img = np.zeros((256, 256, 3))
+    coords = [[10, 10]]
+    msg = "Please input correct locations_list. "
+    msg += "Supported types: np.ndarray, DataFrame, str, Path."
+    with pytest.raises(
+        TypeError,
+        match=msg,
+    ):
+        patchextraction.get_patch_extractor(
+            "point", input_img=img, locations_list=coords, patch_size=38
+        )
+
+    patches = patchextraction.get_patch_extractor(
+        "point", input_img=img, locations_list=np.array(coords), patch_size=38
+    )
+    assert len(patches) > 0

tiatoolbox/models/architecture/utils.py

@@ -3,7 +3,6 @@
 from __future__ import annotations
 
 import sys
-from typing import NoReturn
 
 import numpy as np
 import torch
@@ -12,13 +11,17 @@
 from tiatoolbox import logger
 
 
-def is_torch_compile_compatible() -> NoReturn:
+def is_torch_compile_compatible() -> bool:
     """Check if the current GPU is compatible with torch-compile.
 
+    Returns:
+        True if current GPU is compatible with torch-compile, False otherwise.
+
     Raises:
         Warning if GPU is not compatible with `torch.compile`.
 
     """
+    gpu_compatibility = True
     if torch.cuda.is_available():  # pragma: no cover
         device_cap = torch.cuda.get_device_capability()
         if device_cap not in ((7, 0), (8, 0), (9, 0)):
@@ -28,13 +31,17 @@ def is_torch_compile_compatible() -> NoReturn:
                 "Speedup numbers may be lower than expected.",
                 stacklevel=2,
             )
+            gpu_compatibility = False
     else:
         logger.warning(
             "No GPU detected or cuda not installed, "
             "torch.compile is only supported on selected NVIDIA GPUs. "
             "Speedup numbers may be lower than expected.",
             stacklevel=2,
         )
+        gpu_compatibility = False
+
+    return gpu_compatibility
 
 
 def compile_model(
@@ -68,12 +75,24 @@ def compile_model(
         return model
 
     # Check if GPU is compatible with torch.compile
-    is_torch_compile_compatible()
+    gpu_compatibility = is_torch_compile_compatible()
+
+    if not gpu_compatibility:
+        return model
+
+    if sys.platform == "win32":  # pragma: no cover
+        msg = (
+            "`torch.compile` is not supported on Windows. Please see "
+            "https://github.com/pytorch/pytorch/issues/122094."
+        )
+        logger.warning(msg=msg)
+        return model
 
     # This check will be removed when torch.compile is supported in Python 3.12+
     if sys.version_info > (3, 12):  # pragma: no cover
+        msg = "torch-compile is currently not supported in Python 3.12+."
         logger.warning(
-            ("torch-compile is currently not supported in Python 3.12+. ",),
+            msg=msg,
         )
         return model
 

tiatoolbox/tools/patchextraction.py

@@ -10,7 +10,7 @@
 
 from tiatoolbox import logger
 from tiatoolbox.utils import misc
-from tiatoolbox.utils.exceptions import MethodNotSupportedError
+from tiatoolbox.utils.exceptions import FileNotSupportedError, MethodNotSupportedError
 from tiatoolbox.utils.visualization import AnnotationRenderer
 from tiatoolbox.wsicore import wsireader
 
@@ -772,7 +772,12 @@ def __init__(
             pad_constant_values=pad_constant_values,
             within_bound=within_bound,
         )
-        self.locations_df = misc.read_locations(input_table=locations_list)
+        try:
+            self.locations_df = misc.read_locations(input_table=locations_list)
+        except (TypeError, FileNotSupportedError) as exc:
+            msg = "Please input correct locations_list. "
+            msg += "Supported types: np.ndarray, DataFrame, str, Path."
+            raise TypeError(msg) from exc
         self.locations_df["x"] = self.locations_df["x"] - int(
             (self.patch_size[1] - 1) / 2,
         )

tiatoolbox/utils/misc.py

@@ -531,7 +531,7 @@ def read_locations(
             out_table = pd.read_json(input_table)
             return __assign_unknown_class(out_table)
 
-        msg = "File type not supported."
+        msg = "File type not supported. Supported types: .npy, .csv, .json"
         raise FileNotSupportedError(msg)
 
     if isinstance(input_table, np.ndarray):
@@ -540,7 +540,9 @@ def read_locations(
     if isinstance(input_table, pd.DataFrame):
         return __assign_unknown_class(input_table)
 
-    msg = "Please input correct image path or an ndarray image."
+    msg = "File type not supported. "
+    msg += "Supported types: str, Path, PathLike, np.ndarray, pd.DataFrame"
+
     raise TypeError(msg)