Enable pytype variable type checking

- Add type concept for index selection types
- Enable precise return checking for invalid function calls
- Test solve unknown types to label with structural types

Add conceptual type for dictionary selection variables

Values used to select dictionary subsets must be
containers of hashable elements.

File "monai/monai/transforms/io/dictionary.py", line 55, in __init__:
Function LoadNiftid.__init__ was called with the wrong arguments [wrong-arg-types]
         Expected: (self, keys: Container[Hashable])
  Actually passed: (self, keys: Hashable)
  The following methods aren't implemented on Hashable:
  __iter__

Author: hjmjohnson

monai/config/type_definitions.py

@@ -0,0 +1,38 @@
+# Copyright 2020 MONAI Consortium
+# Licensed under the Apache License, Version 2.0 (the "License");
+# you may not use this file except in compliance with the License.
+# You may obtain a copy of the License at
+#     http://www.apache.org/licenses/LICENSE-2.0
+# Unless required by applicable law or agreed to in writing, software
+# distributed under the License is distributed on an "AS IS" BASIS,
+# WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
+# See the License for the specific language governing permissions and
+# limitations under the License.
+
+# Commonly used concepts are documented in this `type_definitions.py` file
+# to explicitly identify what information that should be used consistently throughout
+# the entire MONAI package. Type would be named  as type_definitions.DictKeySelection
+# which states what we want to say in the name itself.
+#
+# The definitions in this file map context meaningful names to the underlying
+# storage types.
+#
+# A conceptual type is represented by a new type name but is also one which
+# can be different depending on environment. Consistent use of the concept
+# and recorded documentation of the rationale and convention behind it lowers
+# the learning curve for new developers. For readability, shorten names are
+# preferred.
+#
+
+from typing import Hashable, Iterable, Union, Collection
+
+# The KeysCollection type is used to for defining variables
+# that store a subset of keys to select items from a dictionary.
+# The container of keys must contain hashable elements.
+KeysCollection = Collection[Hashable]
+
+# The IndexSelection type is used to for defining variables
+# that store a subset of indexes to select items from a List or Array like objects.
+# The indexes must be integers, and if a container of indexes is specified, the
+# container must be iterable.
+IndexSelection = Union[Iterable[int], int]

monai/transforms/compose.py

@@ -17,6 +17,7 @@
 from abc import ABC, abstractmethod
 import numpy as np
 
+from monai.config.type_definitions import KeysCollection
 from monai.utils.misc import ensure_tuple, get_seed
 from .utils import apply_transform
 
@@ -219,8 +220,8 @@ def __call__(self, data):
 
     """
 
-    def __init__(self, keys: Hashable):
-        self.keys = ensure_tuple(keys)
+    def __init__(self, keys: KeysCollection):
+        self.keys: KeysCollection = ensure_tuple(keys)
         if not self.keys:
             raise ValueError("keys unspecified")
         for key in self.keys:

monai/transforms/croppad/array.py

@@ -17,6 +17,7 @@
 
 import numpy as np
 
+from monai.config.type_definitions import IndexSelection
 from monai.data.utils import get_random_patch, get_valid_patch_size
 from monai.transforms.compose import Transform, Randomizable
 from monai.transforms.utils import generate_spatial_bounding_box
@@ -179,11 +180,13 @@ class CropForeground(Transform):
 
     """
 
-    def __init__(self, select_fn: Callable = lambda x: x > 0, channel_indexes=None, margin: int = 0):
+    def __init__(
+        self, select_fn: Callable = lambda x: x > 0, channel_indexes: Optional[IndexSelection] = None, margin: int = 0,
+    ):
         """
         Args:
             select_fn (Callable): function to select expected foreground, default is to select values > 0.
-            channel_indexes (int, tuple or list): if defined, select foreground only on the specified channels
+            channel_indexes: if defined, select foreground only on the specified channels
                 of image. if None, select foreground on the whole image.
             margin (int): add margin to all dims of the bounding box.
         """

monai/transforms/croppad/dictionary.py

@@ -15,8 +15,9 @@
 Class names are ended with 'd' to denote dictionary-based transforms.
 """
 
-from typing import Union, Hashable, Optional, Callable
+from typing import Union, Optional, Callable, Iterable
 
+from monai.config.type_definitions import KeysCollection, IndexSelection
 from monai.data.utils import get_random_patch, get_valid_patch_size
 from monai.transforms.compose import MapTransform, Randomizable
 from monai.transforms.croppad.array import SpatialCrop, CenterSpatialCrop, SpatialPad
@@ -30,7 +31,7 @@ class SpatialPadd(MapTransform):
     Performs padding to the data, symmetric for all sides or all on one side for each dimension.
     """
 
-    def __init__(self, keys: Hashable, spatial_size, method: str = "symmetric", mode="constant"):
+    def __init__(self, keys: KeysCollection, spatial_size, method: str = "symmetric", mode="constant"):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -60,7 +61,7 @@ class SpatialCropd(MapTransform):
     are not provided, the start and end coordinates of the ROI must be provided.
     """
 
-    def __init__(self, keys: Hashable, roi_center=None, roi_size=None, roi_start=None, roi_end=None):
+    def __init__(self, keys: KeysCollection, roi_center=None, roi_size=None, roi_start=None, roi_end=None):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -90,7 +91,7 @@ class CenterSpatialCropd(MapTransform):
         roi_size (list, tuple): the size of the crop region e.g. [224,224,128]
     """
 
-    def __init__(self, keys: Hashable, roi_size):
+    def __init__(self, keys: KeysCollection, roi_size):
         super().__init__(keys)
         self.cropper = CenterSpatialCrop(roi_size)
 
@@ -118,7 +119,7 @@ class RandSpatialCropd(Randomizable, MapTransform):
             The actual size is sampled from `randint(roi_size, img_size)`.
     """
 
-    def __init__(self, keys: Hashable, roi_size, random_center: bool = True, random_size: bool = True):
+    def __init__(self, keys: KeysCollection, roi_size, random_center: bool = True, random_size: bool = True):
         super().__init__(keys)
         self.roi_size = roi_size
         self.random_center = random_center
@@ -159,19 +160,19 @@ class CropForegroundd(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         source_key: str,
         select_fn: Callable = lambda x: x > 0,
-        channel_indexes: Callable = None,
+        channel_indexes: Optional[IndexSelection] = None,
         margin=0,
     ):
         """
         Args:
-            keys (hashable items): keys of the corresponding items to be transformed.
+            keys: keys of the corresponding items to be transformed.
                 See also: :py:class:`monai.transforms.compose.MapTransform`
             source_key (str): data source to generate the bounding box of foreground, can be image or label, etc.
             select_fn (Callable): function to select expected foreground, default is to select values > 0.
-            channel_indexes (int, tuple or list): if defined, select foreground only on the specified channels
+            channel_indexes: if defined, select foreground only on the specified channels
                 of image. if None, select foreground on the whole image.
             margin (int): add margin to all dims of the bounding box.
         """
@@ -215,7 +216,7 @@ class RandCropByPosNegLabeld(Randomizable, MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         label_key: str,
         size,
         pos: Union[int, float] = 1,

monai/transforms/intensity/dictionary.py

@@ -15,9 +15,11 @@
 Class names are ended with 'd' to denote dictionary-based transforms.
 """
 
-from typing import Hashable, Union, Optional
+from typing import Union, Optional
 
 import numpy as np
+
+from monai.config.type_definitions import KeysCollection
 from monai.transforms.compose import MapTransform, Randomizable
 from monai.transforms.intensity.array import (
     NormalizeIntensity,
@@ -41,7 +43,7 @@ class RandGaussianNoised(Randomizable, MapTransform):
         std (float): Standard deviation (spread) of distribution.
     """
 
-    def __init__(self, keys: Hashable, prob: float = 0.1, mean=0.0, std: float = 0.1):
+    def __init__(self, keys: KeysCollection, prob: float = 0.1, mean=0.0, std: float = 0.1):
         super().__init__(keys)
         self.prob = prob
         self.mean = mean
@@ -70,7 +72,7 @@ class ShiftIntensityd(MapTransform):
     dictionary-based wrapper of :py:class:`monai.transforms.ShiftIntensity`.
     """
 
-    def __init__(self, keys: Hashable, offset: Union[int, float]):
+    def __init__(self, keys: KeysCollection, offset: Union[int, float]):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -92,7 +94,7 @@ class RandShiftIntensityd(Randomizable, MapTransform):
     dictionary-based version :py:class:`monai.transforms.RandShiftIntensity`.
     """
 
-    def __init__(self, keys: Hashable, offsets, prob: float = 0.1):
+    def __init__(self, keys: KeysCollection, offsets, prob: float = 0.1):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -132,7 +134,7 @@ class ScaleIntensityd(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         minv: Union[int, float] = 0.0,
         maxv: Union[int, float] = 1.0,
         factor: Optional[float] = None,
@@ -161,7 +163,7 @@ class RandScaleIntensityd(Randomizable, MapTransform):
     dictionary-based version :py:class:`monai.transforms.RandScaleIntensity`.
     """
 
-    def __init__(self, keys: Hashable, factors, prob: float = 0.1):
+    def __init__(self, keys: KeysCollection, factors, prob: float = 0.1):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -211,7 +213,7 @@ class NormalizeIntensityd(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         subtrahend: Optional[np.ndarray] = None,
         divisor: Optional[np.ndarray] = None,
         nonzero: bool = False,
@@ -239,7 +241,9 @@ class ThresholdIntensityd(MapTransform):
         cval (float or int): value to fill the remaining parts of the image, default is 0.
     """
 
-    def __init__(self, keys: Hashable, threshold: Union[int, float], above: bool = True, cval: Union[int, float] = 0):
+    def __init__(
+        self, keys: KeysCollection, threshold: Union[int, float], above: bool = True, cval: Union[int, float] = 0,
+    ):
         super().__init__(keys)
         self.filter = ThresholdIntensity(threshold, above, cval)
 
@@ -266,7 +270,7 @@ class ScaleIntensityRanged(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         a_min: Union[int, float],
         a_max: Union[int, float],
         b_min: Union[int, float],
@@ -294,7 +298,7 @@ class AdjustContrastd(MapTransform):
         gamma (float): gamma value to adjust the contrast as function.
     """
 
-    def __init__(self, keys: Hashable, gamma: Union[int, float]):
+    def __init__(self, keys: KeysCollection, gamma: Union[int, float]):
         super().__init__(keys)
         self.adjuster = AdjustContrast(gamma)
 

monai/transforms/io/dictionary.py

@@ -15,10 +15,11 @@
 Class names are ended with 'd' to denote dictionary-based transforms.
 """
 
-from typing import Hashable, Optional
+from typing import Optional
 
 import numpy as np
 
+from monai.config.type_definitions import KeysCollection
 from monai.transforms.compose import MapTransform
 from monai.transforms.io.array import LoadNifti, LoadPNG
 
@@ -35,7 +36,7 @@ class LoadNiftid(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         as_closest_canonical: bool = False,
         dtype: Optional[np.dtype] = np.float32,
         meta_key_format: str = "{}.{}",
@@ -77,7 +78,7 @@ class LoadPNGd(MapTransform):
     Dictionary-based wrapper of :py:class:`monai.transforms.LoadPNG`.
     """
 
-    def __init__(self, keys: Hashable, dtype: Optional[np.dtype] = np.float32, meta_key_format: str = "{}.{}"):
+    def __init__(self, keys: KeysCollection, dtype: Optional[np.dtype] = np.float32, meta_key_format: str = "{}.{}"):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.

monai/transforms/post/dictionary.py

@@ -15,8 +15,9 @@
 Class names are ended with 'd' to denote dictionary-based transforms.
 """
 
-from typing import Optional, Hashable
+from typing import Optional
 
+from monai.config.type_definitions import KeysCollection
 from monai.utils.misc import ensure_tuple_rep
 from monai.transforms.compose import MapTransform
 from monai.transforms.post.array import SplitChannel, Activations, AsDiscrete, KeepLargestConnectedComponent
@@ -29,7 +30,7 @@ class SplitChanneld(MapTransform):
 
     """
 
-    def __init__(self, keys: Hashable, output_postfixes, to_onehot=False, num_classes=None):
+    def __init__(self, keys: KeysCollection, output_postfixes, to_onehot=False, num_classes=None):
         """
         Args:
             keys (hashable items): keys of the corresponding items to be transformed.
@@ -65,7 +66,7 @@ class Activationsd(MapTransform):
     Add activation layers to the input data specified by `keys`.
     """
 
-    def __init__(self, keys: Hashable, output_postfix: str = "act", sigmoid=False, softmax=False, other=None):
+    def __init__(self, keys: KeysCollection, output_postfix: str = "act", sigmoid=False, softmax=False, other=None):
         """
         Args:
             keys (hashable items): keys of the corresponding items to model output and label.
@@ -106,7 +107,7 @@ class AsDiscreted(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         output_postfix: str = "discreted",
         argmax=False,
         to_onehot=False,
@@ -161,7 +162,7 @@ class KeepLargestConnectedComponentd(MapTransform):
 
     def __init__(
         self,
-        keys: Hashable,
+        keys: KeysCollection,
         applied_values,
         independent: bool = True,
         background: int = 0,