From 76aeb82b82394daa8109a1fc946650c78238d569 Mon Sep 17 00:00:00 2001 From: F-G Fernandez Date: Wed, 21 Oct 2020 17:20:55 +0200 Subject: [PATCH] Fixed the docstring of RandomResizedCrop (#2851) * docs: Fixed docstring of RandomResizedCrop * docs: Updated docstring Co-authored-by: vfdev --- torchvision/transforms/transforms.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/torchvision/transforms/transforms.py b/torchvision/transforms/transforms.py index 6491ed38c20..9b4e4fac98e 100644 --- a/torchvision/transforms/transforms.py +++ b/torchvision/transforms/transforms.py @@ -738,8 +738,8 @@ class RandomResizedCrop(torch.nn.Module): size (int or sequence): expected output size of each edge. If size is an int instead of sequence like (h, w), a square output size ``(size, size)`` is made. If provided a tuple or list of length 1, it will be interpreted as (size[0], size[0]). - scale (tuple of float): range of size of the origin size cropped - ratio (tuple of float): range of aspect ratio of the origin aspect ratio cropped. + scale (tuple of float): scale range of the cropped image before resizing, relatively to the origin image. + ratio (tuple of float): aspect ratio range of the cropped image before resizing. interpolation (int): Desired interpolation enum defined by `filters`_. Default is ``PIL.Image.BILINEAR``. If input is Tensor, only ``PIL.Image.NEAREST``, ``PIL.Image.BILINEAR`` and ``PIL.Image.BICUBIC`` are supported.