Merge pull request #364 from Tomaz-Vieira/spec_v0_5_tensorflow_adapte…

…r_typecheck

Fixes some typing issues in tensor flow adapter

bioimageio/core/model_adapters/_tensorflow_model_adapter.py

@@ -6,7 +6,8 @@
 import tensorflow as tf
 import xarray as xr
 
-from bioimageio.core.io import FileSource, download
+from bioimageio.spec.utils import download
+from bioimageio.spec.generic.v0_3 import FileSource #FIXME: getre-export from somewhere?
 from bioimageio.spec.model import v0_4, v0_5
 from bioimageio.spec.model.v0_5 import RelativeFilePath
 
@@ -87,10 +88,10 @@ def _get_network(self, weight_file: FileSource):
     # alive in between of forward passes (but then the sessions need to be properly opened / closed)
     def _forward_tf(self, *input_tensors):
         input_keys = [
-            ipt.name if isinstance(ipt, v0_4.InputTensor) else ipt.id for ipt in self.model_description.inputs
+            ipt.name if isinstance(ipt, v0_4.InputTensorDescr) else ipt.id for ipt in self.model_description.inputs
         ]
         output_keys = [
-            out.name if isinstance(out, v0_4.OutputTensor) else out.id for out in self.model_description.outputs
+            out.name if isinstance(out, v0_4.OutputTensorDescr) else out.id for out in self.model_description.outputs
         ]
 
         # TODO read from spec
@@ -148,7 +149,7 @@ def unload(self) -> None:
 class TensorflowModelAdapter(TensorflowModelAdapterBase):
     weight_format = "tensorflow_saved_model_bundle"
 
-    def __init__(self, *, model_description: Union[v0_4.Model, v0_5.Model], devices: Optional[Sequence[str]] = None):
+    def __init__(self, *, model_description: Union[v0_4.ModelDescr, v0_5.ModelDescr], devices: Optional[Sequence[str]] = None):
         if model_description.weights.tensorflow_saved_model_bundle is None:
             raise ValueError("missing tensorflow_saved_model_bundle weights")
 
@@ -162,7 +163,7 @@ def __init__(self, *, model_description: Union[v0_4.Model, v0_5.Model], devices:
 class KerasModelAdapter(TensorflowModelAdapterBase):
     weight_format = "keras_hdf5"
 
-    def __init__(self, *, model_description: Union[v0_4.Model, v0_5.Model], devices: Optional[Sequence[str]] = None):
+    def __init__(self, *, model_description: Union[v0_4.ModelDescr, v0_5.ModelDescr], devices: Optional[Sequence[str]] = None):
         if model_description.weights.keras_hdf5 is None:
             raise ValueError("missing keras_hdf5 weights")