misc doc and type hint fixes

azavea · Aug 23, 2023 · c3ab8e4 · c3ab8e4
1 parent 41c41cf
commit c3ab8e4
Show file tree

Hide file tree

Showing 3 changed files with 24 additions and 31 deletions.
diff --git a/docs/usage/tutorials/pred_and_eval_ss.ipynb b/docs/usage/tutorials/pred_and_eval_ss.ipynb
@@ -43,7 +43,7 @@
    },
    "source": [
     "Load a :class:`Learner` with a trained model from bundle -- :meth:`.Learner.from_model_bundle`\n",
-    "---------------------------------------------------------------------------------------------"
+    "----------------------------------------------------------------------------------------------"
    ]
   },
   {

diff --git a/rastervision_core/rastervision/core/data/label/semantic_segmentation_labels.py b/rastervision_core/rastervision/core/data/label/semantic_segmentation_labels.py
@@ -1,5 +1,4 @@
-from typing import (TYPE_CHECKING, Any, Iterable, List, Optional, Sequence,
-                    Union)
+from typing import (TYPE_CHECKING, Any, Iterable, List, Optional, Sequence)
 from abc import abstractmethod
 
 import numpy as np
@@ -23,8 +22,8 @@ def __init__(self, extent: Box, num_classes: int, dtype: np.dtype):
         """Constructor.
 
         Args:
-            extent (Box): The extent of the region to which
-                the labels belong, in global coordinates.
+            extent (Box): The extent of the region to which the labels belong,
+                in global coordinates.
             num_classes (int): Number of classes.
         """
         self.extent = extent
@@ -143,9 +142,8 @@ def transform_shape(x, y, z=None):
             del self[window]
 
     @classmethod
-    def make_empty(cls, extent: Box, num_classes: int, smooth: bool = False
-                   ) -> Union['SemanticSegmentationDiscreteLabels',
-                              'SemanticSegmentationSmoothLabels']:
+    def make_empty(cls, extent: Box, num_classes: int,
+                   smooth: bool = False) -> 'SemanticSegmentationLabels':
         """Instantiate an empty instance.
 
         Args:
@@ -157,8 +155,7 @@ def make_empty(cls, extent: Box, num_classes: int, smooth: bool = False
                 SemanticSegmentationDiscreteLabels object. Defaults to False.
 
         Returns:
-            Union[SemanticSegmentationDiscreteLabels,
-            SemanticSegmentationSmoothLabels]: If smooth=True, returns a
+            SemanticSegmentationLabels: If smooth=True, returns a
                 SemanticSegmentationSmoothLabels. Otherwise, a
                 SemanticSegmentationDiscreteLabels.
 
@@ -174,15 +171,14 @@ def make_empty(cls, extent: Box, num_classes: int, smooth: bool = False
                 extent=extent, num_classes=num_classes)
 
     @classmethod
-    def from_predictions(cls,
-                         windows: Iterable['Box'],
-                         predictions: Iterable[Any],
-                         extent: Box,
-                         num_classes: int,
-                         smooth: bool = False,
-                         crop_sz: Optional[int] = None
-                         ) -> Union['SemanticSegmentationDiscreteLabels',
-                                    'SemanticSegmentationSmoothLabels']:
+    def from_predictions(
+            cls,
+            windows: Iterable['Box'],
+            predictions: Iterable[Any],
+            extent: Box,
+            num_classes: int,
+            smooth: bool = False,
+            crop_sz: Optional[int] = None) -> 'SemanticSegmentationLabels':
         """Instantiate from windows and their corresponding predictions.
 
         Args:
@@ -202,8 +198,7 @@ def from_predictions(cls,
                 windows. Defaults to None.
 
         Returns:
-            Union[SemanticSegmentationDiscreteLabels,
-            SemanticSegmentationSmoothLabels]: If smooth=True, returns a
+            SemanticSegmentationLabels: If smooth=True, returns a
                 SemanticSegmentationSmoothLabels. Otherwise, a
                 SemanticSegmentationDiscreteLabels.
         """
@@ -349,8 +344,7 @@ def from_predictions(cls,
                          extent: Box,
                          num_classes: int,
                          crop_sz: Optional[int] = None
-                         ) -> Union['SemanticSegmentationDiscreteLabels',
-                                    'SemanticSegmentationSmoothLabels']:
+                         ) -> 'SemanticSegmentationDiscreteLabels':
         labels = cls.make_empty(extent, num_classes)
         labels.add_predictions(windows, predictions, crop_sz=crop_sz)
         return labels
@@ -522,8 +516,7 @@ def from_predictions(cls,
                          extent: Box,
                          num_classes: int,
                          crop_sz: Optional[int] = None
-                         ) -> Union['SemanticSegmentationDiscreteLabels',
-                                    'SemanticSegmentationSmoothLabels']:
+                         ) -> 'SemanticSegmentationSmoothLabels':
         labels = cls.make_empty(extent, num_classes)
         labels.add_predictions(windows, predictions, crop_sz=crop_sz)
         return labels

diff --git a/rastervision_pytorch_learner/rastervision/pytorch_learner/learner_config.py b/rastervision_pytorch_learner/rastervision/pytorch_learner/learner_config.py
@@ -1015,12 +1015,12 @@ def get_data_dirs(self, uri: Union[str, List[str]],
         Args:
             uri (Union[str, List[str]]): a URI or a list of URIs of one of the
                 following:
-                    (1) a URI of a directory containing "train", "valid", and
-                        (optinally) "test" subdirectories
-                    (2) a URI of a zip file containing (1)
-                    (3) a list of (2)
-                    (4) a URI of a directory containing zip files
-                        containing (1)
+
+                (1) a URI of a directory containing "train", "valid", and
+                    (optinally) "test" subdirectories
+                (2) a URI of a zip file containing (1)
+                (3) a list of (2)
+                (4) a URI of a directory containing zip files containing (1)
 
         Returns:
             paths to directories that each contain contents of one zip file