Merge branch 'main' into dataset_stat

Author: FynnBe

bioimageio/core/VERSION

@@ -1,3 +1,3 @@
 {
-    "version": "0.5.1"
+    "version": "0.5.2"
 }

bioimageio/core/prediction_pipeline/_model_adapters/_keras_model_adapter.py

@@ -1,5 +1,6 @@
 import warnings
 from typing import List, Optional, Sequence
+from marshmallow import missing
 
 # by default, we use the keras integrated with tensorflow
 try:
@@ -18,10 +19,11 @@
 
 class KerasModelAdapter(ModelAdapter):
     def _load(self, *, devices: Optional[Sequence[str]] = None) -> None:
-        try:
-            model_tf_version = self.bioimageio_model.weights[self.weight_format].tensorflow_version.version
-        except AttributeError:
+        model_tf_version = self.bioimageio_model.weights["keras_hdf5"].tensorflow_version
+        if model_tf_version is missing:
             model_tf_version = None
+        else:
+            model_tf_version = (int(model_tf_version.major), int(model_tf_version.minor))
 
         if TF_VERSION is None or model_tf_version is None:
             warnings.warn("Could not check tensorflow versions. The prediction results may be wrong.")

bioimageio/core/prediction_pipeline/_model_adapters/_tensorflow_model_adapter.py

@@ -5,6 +5,7 @@
 import numpy as np
 import tensorflow as tf
 import xarray as xr
+from marshmallow import missing
 
 from ._model_adapter import ModelAdapter
 
@@ -34,10 +35,11 @@ def _load_model(self, weight_file):
             return str(weight_file)
 
     def _load(self, *, devices: Optional[List[str]] = None):
-        try:
-            model_tf_version = self.bioimageio_model.weights[self.weight_format].tensorflow_version.version
-        except AttributeError:
+        model_tf_version = self.bioimageio_model.weights[self.weight_format].tensorflow_version
+        if model_tf_version is missing:
             model_tf_version = None
+        else:
+            model_tf_version = (int(model_tf_version.major), int(model_tf_version.minor))
 
         tf_version = tf.__version__
         tf_major_and_minor = tuple(map(int, tf_version.split(".")))[:2]

bioimageio/core/resource_io/io_.py

@@ -1,6 +1,7 @@
 import os
 import pathlib
 from copy import deepcopy
+from tempfile import TemporaryDirectory
 from typing import Dict, Optional, Sequence, Union
 from zipfile import ZIP_DEFLATED, ZipFile
 
@@ -10,7 +11,12 @@
 from bioimageio.core.resource_io.nodes import ResourceDescription
 from bioimageio.spec import load_raw_resource_description
 from bioimageio.spec.shared import raw_nodes
-from bioimageio.spec.shared.common import BIOIMAGEIO_CACHE_PATH, get_class_name_from_type
+from bioimageio.spec.shared.common import (
+    BIOIMAGEIO_CACHE_PATH,
+    BIOIMAGEIO_USE_CACHE,
+    get_class_name_from_type,
+    no_cache_tmp_list,
+)
 from bioimageio.spec.shared.raw_nodes import ResourceDescription as RawResourceDescription
 from . import nodes
 from .utils import resolve_raw_resource_description, resolve_source
@@ -134,21 +140,26 @@ def _get_package_base_name(raw_rd: RawResourceDescription, weights_priority_orde
 
 
 def _get_tmp_package_path(raw_rd: RawResourceDescription, weights_priority_order: Optional[Sequence[str]]):
-    package_file_name = _get_package_base_name(raw_rd, weights_priority_order)
-
-    cache_folder = BIOIMAGEIO_CACHE_PATH / "packages"
-    cache_folder.mkdir(exist_ok=True, parents=True)
-    package_path = (cache_folder / package_file_name).with_suffix(".zip")
-    max_cached_packages_with_same_name = 100
-    for p in range(max_cached_packages_with_same_name):
-        if package_path.exists():
-            package_path = (cache_folder / f"{package_file_name}p{p}").with_suffix(".zip")
+    if BIOIMAGEIO_USE_CACHE:
+        package_file_name = _get_package_base_name(raw_rd, weights_priority_order)
+        cache_folder = BIOIMAGEIO_CACHE_PATH / "packages"
+        cache_folder.mkdir(exist_ok=True, parents=True)
+
+        package_path = (cache_folder / package_file_name).with_suffix(".zip")
+        max_cached_packages_with_same_name = 100
+        for p in range(max_cached_packages_with_same_name):
+            if package_path.exists():
+                package_path = (cache_folder / f"{package_file_name}p{p}").with_suffix(".zip")
+            else:
+                break
         else:
-            break
+            raise FileExistsError(
+                f"Already caching {max_cached_packages_with_same_name} versions of {cache_folder / package_file_name}!"
+            )
     else:
-        raise FileExistsError(
-            f"Already caching {max_cached_packages_with_same_name} versions of {cache_folder / package_file_name}!"
-        )
+        tmp_dir = TemporaryDirectory()
+        no_cache_tmp_list.append(tmp_dir)
+        package_path = pathlib.Path(tmp_dir.name) / "file"
 
     return package_path
 

bioimageio/core/weight_converter/keras/tensorflow.py

@@ -93,7 +93,7 @@ def convert_weights_to_tensorflow_saved_model_bundle(
     weight_path = str(weight_spec.source)
 
     if weight_spec.tensorflow_version:
-        model_tf_major_ver = weight_spec.tensorflow_version.version[0]
+        model_tf_major_ver = int(weight_spec.tensorflow_version.major)
         if model_tf_major_ver != tf_major_ver:
             raise RuntimeError(f"Tensorflow major versions of model {model_tf_major_ver} is not {tf_major_ver}")
 

tests/test_cli.py

@@ -1,3 +1,4 @@
+import os
 import subprocess
 from typing import Sequence
 
@@ -7,8 +8,8 @@
 from bioimageio.core import load_resource_description
 
 
-def run_subprocess(commands: Sequence[str]) -> subprocess.CompletedProcess:
-    return subprocess.run(commands, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, encoding="utf-8")
+def run_subprocess(commands: Sequence[str], **kwargs) -> subprocess.CompletedProcess:
+    return subprocess.run(commands, stdout=subprocess.PIPE, stderr=subprocess.STDOUT, encoding="utf-8", **kwargs)
 
 
 def test_validate_model(unet2d_nuclei_broad_model):
@@ -23,6 +24,13 @@ def test_cli_package(unet2d_nuclei_broad_model, tmp_path):
     assert out_path.exists()
 
 
+def test_cli_package_wo_cache(unet2d_nuclei_broad_model):
+    env = os.environ.copy()
+    env["BIOIMAGEIO_USE_CACHE"] = "false"
+    ret = run_subprocess(["bioimageio", "package", unet2d_nuclei_broad_model], env=env)
+    assert ret.returncode == 0, ret.stdout
+
+
 def test_cli_test_model(unet2d_nuclei_broad_model):
     ret = run_subprocess(["bioimageio", "test-model", unet2d_nuclei_broad_model])
     assert ret.returncode == 0, ret.stdout