Fix broken links (#2217)

* https://github.com/rlaphoenix/VSGAN/blob/master/vsgan/archs/esrgan.py

* https://github.com/huggingface/pytorch-image-models/blob/main/timm/layers/drop.py

* https://kornia.readthedocs.io/en/latest/

ldm_patched/contrib/external_canny.py

@@ -78,7 +78,7 @@ def spatial_gradient(input, normalized: bool = True):
     Return:
         the derivatives of the input feature map. with shape :math:`(B, C, 2, H, W)`.
     .. note::
-       See a working example `here <https://kornia-tutorials.readthedocs.io/en/latest/
+       See a working example `here <https://kornia.readthedocs.io/en/latest/
        filtering_edges.html>`__.
     Examples:
         >>> input = torch.rand(1, 3, 4, 4)
@@ -120,7 +120,7 @@ def rgb_to_grayscale(image, rgb_weights = None):
         grayscale version of the image with shape :math:`(*,1,H,W)`.
 
     .. note::
-       See a working example `here <https://kornia-tutorials.readthedocs.io/en/latest/
+       See a working example `here <https://kornia.readthedocs.io/en/latest/
        color_conversions.html>`__.
 
     Example:
@@ -176,7 +176,7 @@ def canny(
         - the canny edge magnitudes map, shape of :math:`(B,1,H,W)`.
         - the canny edge detection filtered by thresholds and hysteresis, shape of :math:`(B,1,H,W)`.
     .. note::
-       See a working example `here <https://kornia-tutorials.readthedocs.io/en/latest/
+       See a working example `here <https://kornia.readthedocs.io/en/latest/
        canny.html>`__.
     Example:
         >>> input = torch.rand(5, 3, 4, 4)

ldm_patched/pfn/architecture/HAT.py

@@ -14,7 +14,7 @@ from .timm.weight_init import trunc_normal_
 
 def drop_path(x, drop_prob: float = 0.0, training: bool = False):
     """Drop paths (Stochastic Depth) per sample (when applied in main path of residual blocks).
-    From: https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/layers/drop.py
+    From: https://github.com/huggingface/pytorch-image-models/blob/main/timm/layers/drop.py
     """
     if drop_prob == 0.0 or not training:
         return x
@@ -30,7 +30,7 @@ def drop_path(x, drop_prob: float = 0.0, training: bool = False):
 
 class DropPath(nn.Module):
     """Drop paths (Stochastic Depth) per sample  (when applied in main path of residual blocks).
-    From: https://github.com/rwightman/pytorch-image-models/blob/master/timm/models/layers/drop.py
+    From: https://github.com/huggingface/pytorch-image-models/blob/main/timm/layers/drop.py
     """
 
     def __init__(self, drop_prob=None):

ldm_patched/pfn/architecture/RRDB.py

@@ -13,7 +13,7 @@ import torch.nn.functional as F
 from . import block as B
 
 
-# Borrowed from https://github.com/rlaphoenix/VSGAN/blob/master/vsgan/archs/ESRGAN.py
+# Borrowed from https://github.com/rlaphoenix/VSGAN/blob/master/vsgan/archs/esrgan.py
 # Which enhanced stuff that was already here
 class RRDBNet(nn.Module):
     def __init__(