add arg max_input_shape to v0_5.Model.get_axis_sizes()

.github/workflows/build.yml

@@ -16,6 +16,7 @@ jobs:
         include:
           - python-version: "3.12"
             is-dev-version: true
+            run_expensive_tests: true
     steps:
       - uses: actions/checkout@v4
       - uses: actions/setup-python@v5
@@ -29,12 +30,13 @@ jobs:
       - name: Get Date
         id: get-date
         run: |
-          echo "week=$(/bin/date -u "+%Y-%U")" >> $GITHUB_OUTPUT
+          echo "date=$(date +'%Y-%b')"
+          echo "date=$(date +'%Y-%b')" >> $GITHUB_OUTPUT
         shell: bash
-      - uses: actions/cache@v3
+      - uses: actions/cache/restore@v4
         with:
-          path: tests/cache
-          key: ${{ runner.os }}-${{ matrix.python-version }}-${{ steps.get-date.outputs.week }}-${{ hashFiles('**/lockfiles') }}
+          path: bioimageio_cache
+          key: "py${{ matrix.python-version }}-${{ steps.get-date.outputs.date }}"
       - name: Check autogenerated imports
         run: python scripts/generate_version_submodule_imports.py check
       - run: black --check .
@@ -49,14 +51,22 @@ jobs:
       - run: pyright -p pyproject.toml --pythonversion ${{ matrix.python-version }}
         if: matrix.is-dev-version
       - run: pytest
+        env:
+          BIOIMAGEIO_CACHE_PATH: bioimageio_cache
+          SKIP_EXPENSIVE_TESTS: ${{ matrix.run_expensive_tests && 'false' || 'true' }}
+      - uses: actions/cache/save@v4
+        # explicit restore/save instead of cache action to cache even if coverage fails
+        with:
+          path: bioimageio_cache
+          key: "py${{ matrix.python-version }}-${{ steps.get-date.outputs.date }}"
       - if: matrix.is-dev-version && github.event_name == 'pull_request'
         uses: orgoro/[email protected]
         with:
           coverageFile: coverage.xml
           token: ${{ secrets.GITHUB_TOKEN }}
-          thresholdAll: 0.75
+          thresholdAll: 0.7
           thresholdNew: 0.9
-          thresholdModified: 0.85
+          thresholdModified: 0.6
       - if: matrix.is-dev-version
         run: |
           pip install genbadge[coverage]

.gitignore

@@ -10,9 +10,9 @@ coverage.xml
 dist/
 docs/
 output/
-tests/cache
 tests/generated_json_schemas
 tmp/
 user_docs/
 scripts/pdoc/original.py
 scripts/pdoc/patched.py
+bioimageio_cache/

README.md

@@ -130,6 +130,7 @@ To keep the bioimageio.spec Python package version in sync with the (model) desc
 * fix summary formatting
 * improve logged origin for logged messages
 * make the `model.v0_5.ModelDescr.training_data` field a `left_to_right` Union to avoid warnings
+* the deprecated `version_number` is no longer appended to the `id`, but instead set as `version` if no `version` is specified.
 
 #### bioimageio.spec 0.5.3.3
 

bioimageio/spec/application/v0_2.py

@@ -33,7 +33,8 @@ class ApplicationDescr(GenericDescrBase, title="bioimage.io application specific
     type: Literal["application"] = "application"
 
     id: Optional[ApplicationId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     source: Annotated[
         Optional[ImportantFileSource],

bioimageio/spec/application/v0_3.py

@@ -34,7 +34,8 @@ class ApplicationDescr(GenericDescrBase, title="bioimage.io application specific
     type: Literal["application"] = "application"
 
     id: Optional[ApplicationId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     parent: Optional[ApplicationId] = None
     """The description from which this one is derived"""

bioimageio/spec/dataset/v0_2.py

@@ -30,7 +30,8 @@ class DatasetDescr(GenericDescrBase, title="bioimage.io dataset specification"):
     type: Literal["dataset"] = "dataset"
 
     id: Optional[DatasetId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     source: Optional[HttpUrl] = None
     """"URL to the source of the dataset."""

bioimageio/spec/dataset/v0_3.py

@@ -43,7 +43,8 @@ class DatasetDescr(GenericDescrBase, title="bioimage.io dataset specification"):
     type: Literal["dataset"] = "dataset"
 
     id: Optional[DatasetId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     parent: Optional[DatasetId] = None
     """The description from which this one is derived"""

bioimageio/spec/generic/v0_2.py

@@ -450,7 +450,8 @@ class GenericDescr(
     """The resource type assigns a broad category to the resource."""
 
     id: Optional[ResourceId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     source: Optional[HttpUrl] = None
     """The primary source of the resource"""

bioimageio/spec/generic/v0_3.py

@@ -367,8 +367,8 @@ def _remove_version_number(  # pyright: ignore[reportUnknownParameterType]
     ):
         if isinstance(value, dict):
             vn: Any = value.pop("version_number", None)
-            if vn is not None and "id" in value:
-                value["id"] = f"{value['id']}/{vn}"
+            if vn is not None and value.get("version") is None:
+                value["version"] = vn
 
         return value  # pyright: ignore[reportUnknownVariableType]
 
@@ -420,7 +420,8 @@ class GenericDescr(
     """The resource type assigns a broad category to the resource."""
 
     id: Optional[ResourceId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     parent: Optional[ResourceId] = None
     """The description from which this one is derived"""
@@ -448,7 +449,10 @@ def _remove_version_number(  # pyright: ignore[reportUnknownParameterType]
     ):
         if isinstance(value, dict):
             vn: Any = value.pop("version_number", None)
-            if vn is not None and "id" in value:
-                value["id"] = f"{value['id']}/{vn}"
+            if vn is not None and value.get("version") is None:
+                value["version"] = vn
 
         return value  # pyright: ignore[reportUnknownVariableType]
+
+    version: Optional[Version] = None
+    """The version of the linked resource following SemVer 2.0."""

bioimageio/spec/model/v0_4.py

@@ -917,7 +917,8 @@ class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification")
     """Specialized resource type 'model'"""
 
     id: Optional[ModelId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     authors: NotEmpty[  # pyright: ignore[reportGeneralTypeIssues]  # make mandatory
         List[Author]

bioimageio/spec/model/v0_5.py

@@ -35,6 +35,7 @@
 import numpy as np
 from annotated_types import Ge, Gt, Interval, MaxLen, MinLen, Predicate
 from imageio.v3 import imread, imwrite  # pyright: ignore[reportUnknownVariableType]
+from loguru import logger
 from numpy.typing import NDArray
 from pydantic import (
     Discriminator,
@@ -350,10 +351,20 @@ def get_size(
             SpaceOutputAxis,
             SpaceOutputAxisWithHalo,
         ],
-        n: ParameterizedSize_N,
+        n: ParameterizedSize_N = 0,
+        ref_size: Optional[int] = None,
     ):
-        """helper method to compute concrete size for a given axis and its reference axis.
-        If the reference axis is parameterized, `n` is used to compute the concrete size of it, see `ParameterizedSize`.
+        """Compute the concrete size for a given axis and its reference axis.
+
+        Args:
+            axis: The axis this `SizeReference` is the size of.
+            ref_axis: The reference axis to compute the size from.
+            n: If the **ref_axis** is parameterized (of type `ParameterizedSize`)
+                and no fixed **ref_size** is given,
+                **n** is used to compute the size of the parameterized **ref_axis**.
+            ref_size: Overwrite the reference size instead of deriving it from
+                **ref_axis**
+                (**ref_axis.scale** is still used; any given **n** is ignored).
         """
         assert (
             axis.size == self
@@ -367,22 +378,22 @@ def get_size(
             "`SizeReference` requires `axis` and `ref_axis` to have the same `unit`,"
             f" but {axis.unit}!={ref_axis.unit}"
         )
-
-        if isinstance(ref_axis.size, (int, float)):
-            ref_size = ref_axis.size
-        elif isinstance(ref_axis.size, ParameterizedSize):
-            ref_size = ref_axis.size.get_size(n)
-        elif isinstance(ref_axis.size, DataDependentSize):
-            raise ValueError(
-                "Reference axis referenced in `SizeReference` may not be a `DataDependentSize`."
-            )
-        elif isinstance(ref_axis.size, SizeReference):
-            raise ValueError(
-                "Reference axis referenced in `SizeReference` may not be sized by a"
-                + " `SizeReference` itself."
-            )
-        else:
-            assert_never(ref_axis.size)
+        if ref_size is None:
+            if isinstance(ref_axis.size, (int, float)):
+                ref_size = ref_axis.size
+            elif isinstance(ref_axis.size, ParameterizedSize):
+                ref_size = ref_axis.size.get_size(n)
+            elif isinstance(ref_axis.size, DataDependentSize):
+                raise ValueError(
+                    "Reference axis referenced in `SizeReference` may not be a `DataDependentSize`."
+                )
+            elif isinstance(ref_axis.size, SizeReference):
+                raise ValueError(
+                    "Reference axis referenced in `SizeReference` may not be sized by a"
+                    + " `SizeReference` itself."
+                )
+            else:
+                assert_never(ref_axis.size)
 
         return int(ref_size * ref_axis.scale / axis.scale + self.offset)
 
@@ -2032,7 +2043,8 @@ class ModelDescr(GenericModelDescrBase, title="bioimage.io model specification")
     """Specialized resource type 'model'"""
 
     id: Optional[ModelId] = None
-    """Model zoo (bioimage.io) wide, unique identifier (assigned by bioimage.io)"""
+    """bioimage.io-wide unique resource identifier
+    assigned by bioimage.io; version **un**specific."""
 
     authors: NotEmpty[List[Author]]
     """The authors are the creators of the model RDF and the primary points of contact."""
@@ -2471,8 +2483,40 @@ def get_tensor_sizes(
         )
 
     def get_axis_sizes(
-        self, ns: Mapping[Tuple[TensorId, AxisId], ParameterizedSize_N], batch_size: int
+        self,
+        ns: Mapping[Tuple[TensorId, AxisId], ParameterizedSize_N],
+        batch_size: Optional[int] = None,
+        *,
+        max_input_shape: Optional[Mapping[Tuple[TensorId, AxisId], int]] = None,
     ) -> _AxisSizes:
+        """Determine input and output block shape for scale factors **ns**
+        of parameterized input sizes.
+
+        Args:
+            ns: Scale factor `n` for each axis (keyed by (tensor_id, axis_id))
+                that is parameterized as `size = min + n * step`.
+            batch_size: The desired size of the batch dimension.
+                If given **batch_size** overwrites any batch size present in
+                **max_input_shape**. Default 1.
+            max_input_shape: Limits the derived block shapes.
+                Each axis for which the input size, parameterized by `n`, is larger
+                than **max_input_shape** is set to the minimal value `n_min` for which
+                this is still true.
+                Use this for small input samples or large values of **ns**.
+                Or simply whenever you know the full input shape.
+
+        Returns:
+            Resolved axis sizes for model inputs and outputs.
+        """
+        max_input_shape = max_input_shape or {}
+        if batch_size is None:
+            for (_t_id, a_id), s in max_input_shape.items():
+                if a_id == BATCH_AXIS_ID:
+                    batch_size = s
+                    break
+            else:
+                batch_size = 1
+
         all_axes = {
             t.id: {a.id: a for a in t.axes} for t in chain(self.inputs, self.outputs)
         }
@@ -2483,16 +2527,19 @@ def get_axis_sizes(
         def get_axis_size(a: Union[InputAxis, OutputAxis]):
             if isinstance(a, BatchAxis):
                 if (t_descr.id, a.id) in ns:
-                    raise ValueError(
-                        "No size increment factor (n) for batch axis of tensor"
-                        + f" '{t_descr.id}' expected."
+                    logger.warning(
+                        "Ignoring unexpected size increment factor (n) for batch axis"
+                        + " of tensor '{}'.",
+                        t_descr.id,
                     )
                 return batch_size
             elif isinstance(a.size, int):
                 if (t_descr.id, a.id) in ns:
-                    raise ValueError(
-                        "No size increment factor (n) for fixed size axis"
-                        + f" '{a.id}' of tensor '{t_descr.id}' expected."
+                    logger.warning(
+                        "Ignoring unexpected size increment factor (n) for fixed size"
+                        + " axis '{}' of tensor '{}'.",
+                        a.id,
+                        t_descr.id,
                     )
                 return a.size
             elif isinstance(a.size, ParameterizedSize):
@@ -2501,39 +2548,65 @@ def get_axis_size(a: Union[InputAxis, OutputAxis]):
                         "Size increment factor (n) missing for parametrized axis"
                         + f" '{a.id}' of tensor '{t_descr.id}'."
                     )
-                return a.size.get_size(ns[(t_descr.id, a.id)])
+                n = ns[(t_descr.id, a.id)]
+                s_max = max_input_shape.get((t_descr.id, a.id))
+                if s_max is not None:
+                    n = min(n, a.size.get_n(s_max))
+
+                return a.size.get_size(n)
+
             elif isinstance(a.size, SizeReference):
                 if (t_descr.id, a.id) in ns:
-                    raise ValueError(
-                        f"No size increment factor (n) for axis '{a.id}' of tensor"
-                        + f" '{t_descr.id}' with size reference expected."
+                    logger.warning(
+                        "Ignoring unexpected size increment factor (n) for axis '{}'"
+                        + " of tensor '{}' with size reference.",
+                        a.id,
+                        t_descr.id,
                     )
                 assert not isinstance(a, BatchAxis)
                 ref_axis = all_axes[a.size.tensor_id][a.size.axis_id]
                 assert not isinstance(ref_axis, BatchAxis)
+                ref_key = (a.size.tensor_id, a.size.axis_id)
+                ref_size = inputs.get(ref_key, outputs.get(ref_key))
+                assert ref_size is not None, ref_key
+                assert not isinstance(ref_size, _DataDepSize), ref_key
                 return a.size.get_size(
                     axis=a,
                     ref_axis=ref_axis,
-                    n=ns.get((a.size.tensor_id, a.size.axis_id), 0),
+                    ref_size=ref_size,
                 )
             elif isinstance(a.size, DataDependentSize):
                 if (t_descr.id, a.id) in ns:
-                    raise ValueError(
-                        "No size increment factor (n) for data dependent size axis"
-                        + f" '{a.id}' of tensor '{t_descr.id}' expected."
+                    logger.warning(
+                        "Ignoring unexpected increment factor (n) for data dependent"
+                        + " size axis '{}' of tensor '{}'.",
+                        a.id,
+                        t_descr.id,
                     )
                 return _DataDepSize(a.size.min, a.size.max)
             else:
                 assert_never(a.size)
 
+        # first resolve all , but the `SizeReference` input sizes
         for t_descr in self.inputs:
             for a in t_descr.axes:
-                s = get_axis_size(a)
-                assert not isinstance(s, _DataDepSize)
-                inputs[t_descr.id, a.id] = s
+                if not isinstance(a.size, SizeReference):
+                    s = get_axis_size(a)
+                    assert not isinstance(s, _DataDepSize)
+                    inputs[t_descr.id, a.id] = s
+
+        # resolve all other input axis sizes
+        for t_descr in self.inputs:
+            for a in t_descr.axes:
+                if isinstance(a.size, SizeReference):
+                    s = get_axis_size(a)
+                    assert not isinstance(s, _DataDepSize)
+                    inputs[t_descr.id, a.id] = s
 
-        for t_descr in chain(self.inputs, self.outputs):
+        # resolve all output axis sizes
+        for t_descr in self.outputs:
             for a in t_descr.axes:
+                assert not isinstance(a.size, ParameterizedSize)
                 s = get_axis_size(a)
                 outputs[t_descr.id, a.id] = s