make adapter import error messages more informative

Author: FynnBe

bioimageio/core/model_adapters/_keras_model_adapter.py

@@ -26,10 +26,14 @@
 except Exception:
     try:
         import keras  # pyright: ignore[reportMissingImports]
-    except Exception:
+    except Exception as e:
         keras = None
-
+        keras_error = str(e)
+    else:
+        keras_error = None
     tf_version = None
+else:
+    keras_error = None
 
 
 class KerasModelAdapter(ModelAdapter):
@@ -40,7 +44,7 @@ def __init__(
         devices: Optional[Sequence[str]] = None,
     ) -> None:
         if keras is None:
-            raise ImportError("keras")
+            raise ImportError(f"failed to import keras: {keras_error}")
 
         super().__init__()
         if model_description.weights.keras_hdf5 is None:

bioimageio/core/model_adapters/_model_adapter.py

@@ -77,7 +77,7 @@ def create(
                         devices=devices,
                     )
                 except Exception as e:
-                    errors.append(f"{wf}: {e}\n{traceback.format_stack()}")
+                    errors.append(f"{wf}: {e}")
             elif (
                 wf == "tensorflow_saved_model_bundle"
                 and weights.tensorflow_saved_model_bundle is not None
@@ -89,7 +89,7 @@ def create(
                         model_description=model_description, devices=devices
                     )
                 except Exception as e:
-                    errors.append(f"{wf}: {e}\n{traceback.format_stack()}")
+                    errors.append(f"{wf}: {e}")
             elif wf == "onnx" and weights.onnx is not None:
                 try:
                     from ._onnx_model_adapter import ONNXModelAdapter
@@ -98,7 +98,7 @@ def create(
                         model_description=model_description, devices=devices
                     )
                 except Exception as e:
-                    errors.append(f"{wf}: {e}\n{traceback.format_stack()}")
+                    errors.append(f"{wf}: {e}")
             elif wf == "torchscript" and weights.torchscript is not None:
                 try:
                     from ._torchscript_model_adapter import TorchscriptModelAdapter
@@ -107,7 +107,7 @@ def create(
                         model_description=model_description, devices=devices
                     )
                 except Exception as e:
-                    errors.append(f"{wf}: {e}\n{traceback.format_stack()}")
+                    errors.append(f"{wf}: {e}")
             elif wf == "keras_hdf5" and weights.keras_hdf5 is not None:
                 # keras can either be installed as a separate package or used as part of tensorflow
                 # we try to first import the keras model adapter using the separate package and,
@@ -125,7 +125,7 @@ def create(
                         model_description=model_description, devices=devices
                     )
                 except Exception as e:
-                    errors.append(f"{wf}: {e}\n{traceback.format_stack()}")
+                    errors.append(f"{wf}: {e}")
 
         assert errors
         error_list = "\n - ".join(errors)

bioimageio/core/model_adapters/_onnx_model_adapter.py

@@ -12,8 +12,11 @@
 
 try:
     import onnxruntime as rt
-except Exception:
+except Exception as e:
     rt = None
+    rt_error = str(e)
+else:
+    rt_error = None
 
 
 class ONNXModelAdapter(ModelAdapter):
@@ -24,7 +27,7 @@ def __init__(
         devices: Optional[Sequence[str]] = None,
     ):
         if rt is None:
-            raise ImportError("onnxruntime")
+            raise ImportError(f"failed to import onnxruntime: {rt_error}")
 
         super().__init__()
         self._internal_output_axes = [

bioimageio/core/model_adapters/_pytorch_model_adapter.py

@@ -12,8 +12,11 @@
 
 try:
     import torch
-except Exception:
+except Exception as e:
     torch = None
+    torch_error = str(e)
+else:
+    torch_error = None
 
 
 class PytorchModelAdapter(ModelAdapter):
@@ -29,7 +32,8 @@ def __init__(
         devices: Optional[Sequence[str]] = None,
     ):
         if torch is None:
-            raise ImportError("failed to import torch")
+            raise ImportError(f"failed to import torch: {torch_error}")
+
         super().__init__()
         self.output_dims = [tuple(a.id for a in get_axes_infos(out)) for out in outputs]
         self._network = self.get_network(weights)

bioimageio/core/model_adapters/_tensorflow_model_adapter.py

@@ -14,8 +14,11 @@
 
 try:
     import tensorflow as tf  # pyright: ignore[reportMissingImports]
-except Exception:
+except Exception as e:
     tf = None
+    tf_error = str(e)
+else:
+    tf_error = None
 
 
 class TensorflowModelAdapterBase(ModelAdapter):
@@ -34,7 +37,7 @@ def __init__(
         model_description: Union[v0_4.ModelDescr, v0_5.ModelDescr],
     ):
         if tf is None:
-            raise ImportError("tensorflow")
+            raise ImportError(f"failed to import tensorflow: {tf_error}")
 
         super().__init__()
         self.model_description = model_description

bioimageio/core/model_adapters/_torchscript_model_adapter.py

@@ -14,8 +14,11 @@
 
 try:
     import torch
-except Exception:
+except Exception as e:
     torch = None
+    torch_error = str(e)
+else:
+    torch_error = None
 
 
 class TorchscriptModelAdapter(ModelAdapter):
@@ -26,7 +29,7 @@ def __init__(
         devices: Optional[Sequence[str]] = None,
     ):
         if torch is None:
-            raise ImportError("torch")
+            raise ImportError(f"failed to import torch: {torch_error}")
 
         super().__init__()
         if model_description.weights.torchscript is None: