add docstrings

Author: FynnBe

bioimageio/core/prediction_pipeline/_combined_processing.py

@@ -35,9 +35,9 @@ def __init__(self, tensor_specs: Union[List[nodes.InputTensor], List[nodes.Outpu
             for step in steps:
                 self._procs.append(KNOWN_PROCESSING[proc_prefix][step.name](tensor_name=t.name, **step.kwargs))
 
-        # There is a difference between pre-and-postprocessing:
-        # Pre-processing always returns float32, because its output is consumed by the model.
-        # Post-processing, however, should return the dtype that is specified in the model spec.
+        # There is a difference between pre-and postprocessing:
+        # Preprocessing always returns float32, because its output is consumed by the model.
+        # Postprocessing, however, should return the dtype that is specified in the model spec.
         # todo: cast dtype for inputs before preprocessing? or check dtype?
         if proc_prefix == POST:
             for t in tensor_specs:

bioimageio/core/prediction_pipeline/_processing.py

@@ -103,6 +103,12 @@ def ensure_dtype(tensor: xr.DataArray, *, dtype) -> xr.DataArray:
 
 @dataclass
 class Binarize(Processing):
+    """'output = tensor > threshold' (returns float array)
+
+    Args:
+        threshold : threshold.
+    """
+
     threshold: float = MISSING  # make dataclass inheritance work for py<3.10 by using an explicit MISSING value.
 
     def apply(self, tensor: xr.DataArray) -> xr.DataArray:
@@ -111,6 +117,8 @@ def apply(self, tensor: xr.DataArray) -> xr.DataArray:
 
 @dataclass
 class Clip(Processing):
+    """Limit tensor values to [min, max]"""
+
     min: float = MISSING
     max: float = MISSING