Apllies black

Author: Tomaz-Vieira

bioimageio/core/proc_ops.py

@@ -3,7 +3,6 @@
 from dataclasses import InitVar, dataclass, field
 from typing import (
     Collection,
-    List,
     Literal,
     Mapping,
     Optional,
@@ -19,6 +18,9 @@
 
 from bioimageio.spec.model import v0_4, v0_5
 from bioimageio.spec.model.v0_5 import TensorId
+from bioimageio.spec.model.v0_5 import (
+    _convert_proc,  # pyright: ignore [reportPrivateUsage]
+)
 
 from ._op_base import BlockedOperator, Operator
 from .axis import AxisId, PerAxis
@@ -691,8 +693,11 @@ def get_proc_class(proc_spec: ProcDescr):
     else:
         assert_never(proc_spec)
 
-def preproc_v4_to_processing(inp: v0_4.InputTensorDescr, proc_spec: v0_4.PreprocessingDescr,) -> Processing:
-    from bioimageio.spec.model.v0_5 import _convert_proc # pyright: ignore [reportPrivateUsage]
+
+def preproc_v4_to_processing(
+    inp: v0_4.InputTensorDescr,
+    proc_spec: v0_4.PreprocessingDescr,
+) -> Processing:
     member_id = TensorId(str(inp.name))
     if isinstance(proc_spec, v0_4.BinarizeDescr):
         return Binarize.from_proc_descr(proc_spec, member_id)
@@ -708,15 +713,20 @@ def preproc_v4_to_processing(inp: v0_4.InputTensorDescr, proc_spec: v0_4.Preproc
         if proc_spec.kwargs.mode == "fixed":
             axes = inp.axes
             v5_proc_spec = _convert_proc(proc_spec, axes)
-            assert isinstance(v5_proc_spec, v0_5.FixedZeroMeanUnitVarianceDescr) #FIXME
+            assert isinstance(
+                v5_proc_spec, v0_5.FixedZeroMeanUnitVarianceDescr
+            )  # FIXME
             return FixedZeroMeanUnitVariance.from_proc_descr(v5_proc_spec, member_id)
         else:
             return ZeroMeanUnitVariance.from_proc_descr(proc_spec, member_id)
     else:
         assert_never(proc_spec)
 
-def postproc_v4_to_processing(inp: v0_4.OutputTensorDescr, proc_spec: v0_4.PostprocessingDescr,) -> Processing:
-    from bioimageio.spec.model.v0_5 import _convert_proc # pyright: ignore [reportPrivateUsage]
+
+def postproc_v4_to_processing(
+    inp: v0_4.OutputTensorDescr,
+    proc_spec: v0_4.PostprocessingDescr,
+) -> Processing:
     member_id = TensorId(str(inp.name))
     if isinstance(proc_spec, v0_4.BinarizeDescr):
         return Binarize.from_proc_descr(proc_spec, member_id)
@@ -734,14 +744,20 @@ def postproc_v4_to_processing(inp: v0_4.OutputTensorDescr, proc_spec: v0_4.Postp
         if proc_spec.kwargs.mode == "fixed":
             axes = inp.axes
             v5_proc_spec = _convert_proc(proc_spec, axes)
-            assert isinstance(v5_proc_spec, v0_5.FixedZeroMeanUnitVarianceDescr) #FIXME
+            assert isinstance(
+                v5_proc_spec, v0_5.FixedZeroMeanUnitVarianceDescr
+            )  # FIXME
             return FixedZeroMeanUnitVariance.from_proc_descr(v5_proc_spec, member_id)
         else:
             return ZeroMeanUnitVariance.from_proc_descr(proc_spec, member_id)
     else:
         assert_never(proc_spec)
 
-def preproc_v5_to_processing(inp: v0_5.InputTensorDescr, proc_spec: v0_5.PreprocessingDescr,) -> Processing:
+
+def preproc_v5_to_processing(
+    inp: v0_5.InputTensorDescr,
+    proc_spec: v0_5.PreprocessingDescr,
+) -> Processing:
     if isinstance(proc_spec, v0_5.BinarizeDescr):
         return Binarize.from_proc_descr(proc_spec, inp.id)
     elif isinstance(proc_spec, v0_5.ClipDescr):
@@ -761,7 +777,11 @@ def preproc_v5_to_processing(inp: v0_5.InputTensorDescr, proc_spec: v0_5.Preproc
     else:
         assert_never(proc_spec)
 
-def postproc_v5_to_processing(inp: v0_5.OutputTensorDescr, proc_spec: v0_5.PostprocessingDescr,) -> Processing:
+
+def postproc_v5_to_processing(
+    inp: v0_5.OutputTensorDescr,
+    proc_spec: v0_5.PostprocessingDescr,
+) -> Processing:
     if isinstance(proc_spec, v0_5.BinarizeDescr):
         return Binarize.from_proc_descr(proc_spec, inp.id)
     if isinstance(proc_spec, v0_5.ScaleMeanVarianceDescr):

bioimageio/core/proc_setup.py

@@ -6,7 +6,6 @@
     Optional,
     Sequence,
     Set,
-    Tuple,
     Union,
 )
 
@@ -15,13 +14,11 @@
 from bioimageio.spec.model import AnyModelDescr, v0_4, v0_5
 from bioimageio.spec.model.v0_5 import TensorId
 
-from .digest_spec import get_member_ids
 from .proc_ops import (
     AddKnownDatasetStats,
     EnsureDtype,
     Processing,
     UpdateStats,
-    get_proc_class,
     postproc_v4_to_processing,
     postproc_v5_to_processing,
     preproc_v4_to_processing,
@@ -141,7 +138,10 @@ def get_requried_sample_measures(model: AnyModelDescr) -> RequiredSampleMeasures
         {m for m in s.post_measures if isinstance(m, SampleMeasureBase)},
     )
 
-def _prepare_v4_preprocs(tensor_descrs: Sequence[v0_4.InputTensorDescr]) -> List[Processing]:
+
+def _prepare_v4_preprocs(
+    tensor_descrs: Sequence[v0_4.InputTensorDescr],
+) -> List[Processing]:
     procs: List[Processing] = []
     for t_descr in tensor_descrs:
         member_id = TensorId(str(t_descr.name))
@@ -152,7 +152,10 @@ def _prepare_v4_preprocs(tensor_descrs: Sequence[v0_4.InputTensorDescr]) -> List
             procs.append(preproc_v4_to_processing(t_descr, proc_d))
     return procs
 
-def _prepare_v4_postprocs(tensor_descrs: Sequence[v0_4.OutputTensorDescr]) -> List[Processing]:
+
+def _prepare_v4_postprocs(
+    tensor_descrs: Sequence[v0_4.OutputTensorDescr],
+) -> List[Processing]:
     procs: List[Processing] = []
     for t_descr in tensor_descrs:
         member_id = TensorId(str(t_descr.name))
@@ -163,14 +166,20 @@ def _prepare_v4_postprocs(tensor_descrs: Sequence[v0_4.OutputTensorDescr]) -> Li
             procs.append(postproc_v4_to_processing(t_descr, proc_d))
     return procs
 
-def _prepare_v5_preprocs(tensor_descrs: Sequence[v0_5.InputTensorDescr]) -> List[Processing]:
+
+def _prepare_v5_preprocs(
+    tensor_descrs: Sequence[v0_5.InputTensorDescr],
+) -> List[Processing]:
     procs: List[Processing] = []
     for t_descr in tensor_descrs:
         for proc_d in t_descr.preprocessing:
             procs.append(preproc_v5_to_processing(t_descr, proc_d))
     return procs
 
-def _prepare_v5_postprocs(tensor_descrs: Sequence[v0_5.OutputTensorDescr]) -> List[Processing]:
+
+def _prepare_v5_postprocs(
+    tensor_descrs: Sequence[v0_5.OutputTensorDescr],
+) -> List[Processing]:
     procs: List[Processing] = []
     for t_descr in tensor_descrs:
         for proc_d in t_descr.postprocessing: