Merge pull request #706 from bioimage-io/bump_version

Bump library version

Author: FynnBe

.github/workflows/build.yml

@@ -16,6 +16,7 @@ jobs:
         pydantic-version: ["2.10.3", "2.11.0"]
         include:
           - python-version: "3.12"
+            pydantic-version: "2.11.0"
             is-dev-version: true
             run-expensive-tests: true
     steps:

bioimageio/spec/VERSION

@@ -1,3 +1,3 @@
 {
-    "version": "0.5.4.2"
+    "version": "0.5.4.3"
 }

bioimageio/spec/model/v0_4.py

@@ -238,89 +238,6 @@ def file(self):
 ]
 
 
-class WeightsDescr(Node):
-    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
-    onnx: Optional[OnnxWeightsDescr] = None
-    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
-    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
-    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
-        None
-    )
-    torchscript: Optional[TorchscriptWeightsDescr] = None
-
-    @model_validator(mode="after")
-    def check_one_entry(self) -> Self:
-        if all(
-            entry is None
-            for entry in [
-                self.keras_hdf5,
-                self.onnx,
-                self.pytorch_state_dict,
-                self.tensorflow_js,
-                self.tensorflow_saved_model_bundle,
-                self.torchscript,
-            ]
-        ):
-            raise ValueError("Missing weights entry")
-
-        return self
-
-    def __getitem__(
-        self,
-        key: WeightsFormat,
-    ):
-        if key == "keras_hdf5":
-            ret = self.keras_hdf5
-        elif key == "onnx":
-            ret = self.onnx
-        elif key == "pytorch_state_dict":
-            ret = self.pytorch_state_dict
-        elif key == "tensorflow_js":
-            ret = self.tensorflow_js
-        elif key == "tensorflow_saved_model_bundle":
-            ret = self.tensorflow_saved_model_bundle
-        elif key == "torchscript":
-            ret = self.torchscript
-        else:
-            raise KeyError(key)
-
-        if ret is None:
-            raise KeyError(key)
-
-        return ret
-
-    @property
-    def available_formats(self):
-        return {
-            **({} if self.keras_hdf5 is None else {"keras_hdf5": self.keras_hdf5}),
-            **({} if self.onnx is None else {"onnx": self.onnx}),
-            **(
-                {}
-                if self.pytorch_state_dict is None
-                else {"pytorch_state_dict": self.pytorch_state_dict}
-            ),
-            **(
-                {}
-                if self.tensorflow_js is None
-                else {"tensorflow_js": self.tensorflow_js}
-            ),
-            **(
-                {}
-                if self.tensorflow_saved_model_bundle is None
-                else {
-                    "tensorflow_saved_model_bundle": self.tensorflow_saved_model_bundle
-                }
-            ),
-            **({} if self.torchscript is None else {"torchscript": self.torchscript}),
-        }
-
-    @property
-    def missing_formats(self):
-        return {
-            wf for wf in get_args(WeightsFormat) if wf not in self.available_formats
-        }
-
-
 class WeightsEntryDescrBase(FileDescr):
     type: ClassVar[WeightsFormat]
     weights_format_name: ClassVar[str]  # human readable
@@ -544,6 +461,89 @@ def _tfv(cls, value: Any):
         return value
 
 
+class WeightsDescr(Node):
+    keras_hdf5: Optional[KerasHdf5WeightsDescr] = None
+    onnx: Optional[OnnxWeightsDescr] = None
+    pytorch_state_dict: Optional[PytorchStateDictWeightsDescr] = None
+    tensorflow_js: Optional[TensorflowJsWeightsDescr] = None
+    tensorflow_saved_model_bundle: Optional[TensorflowSavedModelBundleWeightsDescr] = (
+        None
+    )
+    torchscript: Optional[TorchscriptWeightsDescr] = None
+
+    @model_validator(mode="after")
+    def check_one_entry(self) -> Self:
+        if all(
+            entry is None
+            for entry in [
+                self.keras_hdf5,
+                self.onnx,
+                self.pytorch_state_dict,
+                self.tensorflow_js,
+                self.tensorflow_saved_model_bundle,
+                self.torchscript,
+            ]
+        ):
+            raise ValueError("Missing weights entry")
+
+        return self
+
+    def __getitem__(
+        self,
+        key: WeightsFormat,
+    ):
+        if key == "keras_hdf5":
+            ret = self.keras_hdf5
+        elif key == "onnx":
+            ret = self.onnx
+        elif key == "pytorch_state_dict":
+            ret = self.pytorch_state_dict
+        elif key == "tensorflow_js":
+            ret = self.tensorflow_js
+        elif key == "tensorflow_saved_model_bundle":
+            ret = self.tensorflow_saved_model_bundle
+        elif key == "torchscript":
+            ret = self.torchscript
+        else:
+            raise KeyError(key)
+
+        if ret is None:
+            raise KeyError(key)
+
+        return ret
+
+    @property
+    def available_formats(self):
+        return {
+            **({} if self.keras_hdf5 is None else {"keras_hdf5": self.keras_hdf5}),
+            **({} if self.onnx is None else {"onnx": self.onnx}),
+            **(
+                {}
+                if self.pytorch_state_dict is None
+                else {"pytorch_state_dict": self.pytorch_state_dict}
+            ),
+            **(
+                {}
+                if self.tensorflow_js is None
+                else {"tensorflow_js": self.tensorflow_js}
+            ),
+            **(
+                {}
+                if self.tensorflow_saved_model_bundle is None
+                else {
+                    "tensorflow_saved_model_bundle": self.tensorflow_saved_model_bundle
+                }
+            ),
+            **({} if self.torchscript is None else {"torchscript": self.torchscript}),
+        }
+
+    @property
+    def missing_formats(self):
+        return {
+            wf for wf in get_args(WeightsFormat) if wf not in self.available_formats
+        }
+
+
 class ParameterizedInputShape(Node):
     """A sequence of valid shapes given by `shape_k = min + k * step for k in {0, 1, ...}`."""
 

changelog.md

@@ -10,7 +10,7 @@ In this file we log both:
 
 This changelog includes implementation details and my reference the [changes to the Resource Description Format](#changes-to-the-resource-description-format), e.g. in entry [bioimageio.spec 0.5.2](#bioimageiospec-052).
 
-#### bioimageio.spec 0.5.4.3 (to be released)
+#### bioimageio.spec 0.5.4.3
 
 - fix root determination of cacheless downloads of non-zip files
 - use httpx instead of requests