Fix non-existing parameters in docstrings (#7025)

references/depth/stereo/utils/losses.py

@@ -275,7 +275,7 @@ class SmoothnessLoss(nn.Module):
         """
         Args:
             images: tensor of shape (D1, D2, ..., DN, C, H, W)
-            depths: tensor of shape (D1, D2, ..., DN, 1, H, W)
+            vals: tensor of shape (D1, D2, ..., DN, 1, H, W)
 
         Returns:
             smoothness loss of shape (D1, D2, ..., DN)

test/datasets_utils.py

@@ -951,7 +951,7 @@ def create_random_string(length: int, *digits: str) -> str:
 
     Args:
         length (int): Number of characters in the generated string.
-        *characters (str): Characters to sample from. If omitted defaults to :attr:`string.ascii_lowercase`.
+        *digits (str): Characters to sample from. If omitted defaults to :attr:`string.ascii_lowercase`.
     """
     if not digits:
         digits = string.ascii_lowercase

test/test_ops.py

@@ -585,8 +585,9 @@ class TestNMS:
     def _reference_nms(self, boxes, scores, iou_threshold):
         """
         Args:
-            box_scores (N, 5): boxes in corner-form and probabilities.
-            iou_threshold: intersection over union threshold.
+            boxes: boxes in corner-form
+            scores: probabilities
+            iou_threshold: intersection over union threshold
         Returns:
              picked: a list of indexes of the kept boxes
         """

torchvision/models/_api.py

@@ -117,7 +117,7 @@ def get_weight(name: str) -> WeightsEnum:
 
 def get_model_weights(name: Union[Callable, str]) -> WeightsEnum:
     """
-    Retuns the weights enum class associated to the given model.
+    Returns the weights enum class associated to the given model.
 
     .. betastatus:: function
 
@@ -137,7 +137,6 @@ def _get_enum_from_fn(fn: Callable) -> WeightsEnum:
 
     Args:
         fn (Callable): The builder method used to create the model.
-        weight_name (str): The name of the weight enum entry of the specific model.
     Returns:
         WeightsEnum: The requested weight enum.
     """

torchvision/models/detection/_utils.py

@@ -25,7 +25,7 @@ class BalancedPositiveNegativeSampler:
     def __call__(self, matched_idxs: List[Tensor]) -> Tuple[List[Tensor], List[Tensor]]:
         """
         Args:
-            matched idxs: list of tensors containing -1, 0 or positive values.
+            matched_idxs: list of tensors containing -1, 0 or positive values.
                 Each tensor corresponds to a specific image.
                 -1 values are ignored, 0 are considered as negatives and > 0 as
                 positives.

torchvision/transforms/transforms.py

@@ -2123,7 +2123,7 @@ class ElasticTransform(torch.nn.Module):
     def forward(self, tensor: Tensor) -> Tensor:
         """
         Args:
-            img (PIL Image or Tensor): Image to be transformed.
+            tensor (PIL Image or Tensor): Image to be transformed.
 
         Returns:
             PIL Image or Tensor: Transformed image.