Update github branch name

docs/source/starting/inference.rst

@@ -5,7 +5,7 @@ Predict optical flow with a pretrained model
 infer.py
 ========
 
-`[source code] <https://github.com/hmorimitsu/ptlflow/tree/master/infer.py>`__
+`[source code] <https://github.com/hmorimitsu/ptlflow/tree/main/infer.py>`__
 
 We provide a script for making it easier to perform inference on different inputs.
 Read :ref:`initial-scripts` to know how to download it.

docs/source/starting/testing.rst

@@ -6,7 +6,7 @@ Predicting optical flow on test datasets
 
 Some datasets, such as MPI-Sintel and KITTI, provide a test split of the dataset, which is to be used
 for submitting results for the official rankings. PTLFlow provides a script
-`test.py <https://github.com/hmorimitsu/ptlflow/tree/master/test.py>`__ that can be used to generate
+`test.py <https://github.com/hmorimitsu/ptlflow/tree/main/test.py>`__ that can be used to generate
 predictions for the test split of some benchmarks. Read :ref:`initial-scripts` to know how to download it.
 
     At the moment, ``test.py`` only supports MPI-Sintel, KITTI 2012, and KITTI 2015 datasets by default.

docs/source/starting/training.rst

@@ -23,11 +23,11 @@ trained some model inside PTLFlow, please feel free to contribute your results b
 How to train a model
 ====================
 
-You can use the script `train.py <https://github.com/hmorimitsu/ptlflow/tree/master/train.py>`_
+You can use the script `train.py <https://github.com/hmorimitsu/ptlflow/tree/main/train.py>`_
 Read :ref:`initial-scripts` to know how to download it.
 
 In order to train a model, you should also keep a copy of
-`datasets.yml <https://github.com/hmorimitsu/ptlflow/tree/master/datasets.yml>`_
+`datasets.yml <https://github.com/hmorimitsu/ptlflow/tree/main/datasets.yml>`_
 in the same directory as ``train.py``. Then you should update the paths inside ``datasets.yml``
 to point to the dataset root folders in your machine.
 

docs/source/starting/validation.rst

@@ -4,7 +4,7 @@
 Run validation on a model
 =========================
 
-You can use the script `validate.py <https://github.com/hmorimitsu/ptlflow/tree/master/validate.py>`__
+You can use the script `validate.py <https://github.com/hmorimitsu/ptlflow/tree/main/validate.py>`__
 to validate one of the available models. Read :ref:`initial-scripts` to know how to download it.
 
 Once you have the script, you can run a validation as follows:
@@ -39,7 +39,7 @@ would use the following two datasets for the validation:
 
 You can check the :ref:`train-val-dataset` page for more details about the ``val_dataset`` string options.
 If you want to know about the train/val splits of each dataset, check the validation text files at
-`https://github.com/hmorimitsu/ptlflow/tree/master/ptlflow/data <https://github.com/hmorimitsu/ptlflow/tree/master/ptlflow/data>`__.
+`https://github.com/hmorimitsu/ptlflow/tree/main/ptlflow/data <https://github.com/hmorimitsu/ptlflow/tree/main/ptlflow/data>`__.
 
 Using a local checkpoint
 ========================