Replace master with main in links to torchvision repo (#4365)

gallery/plot_video_api.py

@@ -35,7 +35,7 @@ from torchvision.datasets.utils import download_url
 
 # Download the sample video
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/WUzgd7C1pWA.mp4?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/WUzgd7C1pWA.mp4?raw=true",
     ".",
     "WUzgd7C1pWA.mp4"
 )
@@ -187,26 +187,26 @@ os.makedirs("./dataset/2", exist_ok=True)
 # Download the videos
 from torchvision.datasets.utils import download_url
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/WUzgd7C1pWA.mp4?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/WUzgd7C1pWA.mp4?raw=true",
     "./dataset/1", "WUzgd7C1pWA.mp4"
 )
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/RATRACE_wave_f_nm_np1_fr_goo_37.avi?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/RATRACE_wave_f_nm_np1_fr_goo_37.avi?raw=true",
     "./dataset/1",
     "RATRACE_wave_f_nm_np1_fr_goo_37.avi"
 )
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/SOX5yA1l24A.mp4?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/SOX5yA1l24A.mp4?raw=true",
     "./dataset/2",
     "SOX5yA1l24A.mp4"
 )
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/v_SoccerJuggling_g23_c01.avi?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/v_SoccerJuggling_g23_c01.avi?raw=true",
     "./dataset/2",
     "v_SoccerJuggling_g23_c01.avi"
 )
 download_url(
-    "https://github.com/pytorch/vision/blob/master/test/assets/videos/v_SoccerJuggling_g24_c01.avi?raw=true",
+    "https://github.com/pytorch/vision/blob/main/test/assets/videos/v_SoccerJuggling_g24_c01.avi?raw=true",
     "./dataset/2",
     "v_SoccerJuggling_g24_c01.avi"
 )

references/video_classification/README.md

@@ -22,7 +22,7 @@ python -m torch.distributed.launch --nproc_per_node=8 --use_env train.py --data-
 ```
 
 **Note:** all our models were trained on 8 nodes with 8 V100 GPUs each for a total of 64 GPUs. Expected training time for 64 GPUs is 24 hours, depending on the storage solution.
-**Note 2:** hyperparameters for exact replication of our training can be found [here](https://github.com/pytorch/vision/blob/master/torchvision/models/video/README.md). Some hyperparameters such as learning rate are scaled linearly in proportion to the number of GPUs.
+**Note 2:** hyperparameters for exact replication of our training can be found [here](https://github.com/pytorch/vision/blob/main/torchvision/models/video/README.md). Some hyperparameters such as learning rate are scaled linearly in proportion to the number of GPUs.
 
 ### Single GPU 
 

torchvision/models/video/README.md

@@ -8,7 +8,7 @@ Additional documentation can be found [here](https://pytorch.org/docs/stable/tor
 
 ### Kinetics400 dataset pretraining parameters
 
-See reference training script [here](https://github.com/pytorch/vision/blob/master/references/video_classification/train.py):
+See reference training script [here](https://github.com/pytorch/vision/blob/main/references/video_classification/train.py):
 
 - input size: [3, 16, 112, 112]
 - input space: RGB

torchvision/transforms/transforms.py

@@ -83,7 +83,7 @@ class ToTensor:
         Because the input image is scaled to [0.0, 1.0], this transformation should not be used when
         transforming target image masks. See the `references`_ for implementing the transforms for image masks.
 
-    .. _references: https://github.com/pytorch/vision/tree/master/references/segmentation
+    .. _references: https://github.com/pytorch/vision/tree/main/references/segmentation
     """
 
     def __call__(self, pic):