Merge branch 'master' into patch-1

Author: holly1238

.devcontainer/requirements.txt

@@ -17,7 +17,7 @@ spacy
 ray[tune]
 
 # PyTorch Theme
--e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
+-e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
 
 ipython
 

.jenkins/build.sh

@@ -41,7 +41,7 @@ python -m spacy download de
 
 # PyTorch Theme
 rm -rf src
-pip install -e git+git://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
+pip install -e git+https://github.com/pytorch/pytorch_sphinx_theme.git#egg=pytorch_sphinx_theme
 pip install sphinx-gallery==0.3.1 tqdm matplotlib ipython pillow==8.1.0
 
 aws configure set default.s3.multipart_threshold 5120MB

_static/img/thumbnails/cropped/torchaudio-asr.png

@@ -38,7 +38,7 @@
 # continue to use the CPU.
 
 device = 'cuda' if torch.cuda.is_available() else 'cpu'
-print('Using {} device'.format(device))
+print(f'Using {device} device')
 
 ##############################################
 # Define the Class

beginner_source/basics/buildmodel_tutorial.py

@@ -89,7 +89,7 @@
 
 # Get cpu or gpu device for training.
 device = "cuda" if torch.cuda.is_available() else "cpu"
-print("Using {} device".format(device))
+print(f"Using {device} device")
 
 # Define model
 class NeuralNetwork(nn.Module):

beginner_source/basics/quickstart_tutorial.py

@@ -4,7 +4,7 @@
 -------------------------------
 
 A third order polynomial, trained to predict :math:`y=\sin(x)` from :math:`-\pi`
-to :math:`pi` by minimizing squared Euclidean distance.
+to :math:`\pi` by minimizing squared Euclidean distance.
 
 This implementation computes the forward pass using operations on PyTorch
 Tensors, and uses PyTorch autograd to compute gradients.

beginner_source/examples_autograd/polynomial_autograd.py

@@ -4,7 +4,7 @@
 ----------------------------------------
 
 A third order polynomial, trained to predict :math:`y=\sin(x)` from :math:`-\pi`
-to :math:`pi` by minimizing squared Euclidean distance. Instead of writing the
+to :math:`\pi` by minimizing squared Euclidean distance. Instead of writing the
 polynomial as :math:`y=a+bx+cx^2+dx^3`, we write the polynomial as
 :math:`y=a+b P_3(c+dx)` where :math:`P_3(x)=\frac{1}{2}\left(5x^3-3x\right)` is
 the `Legendre polynomial`_ of degree three.

beginner_source/examples_autograd/polynomial_custom_function.py

@@ -169,7 +169,7 @@ Welcome to PyTorch Tutorials
    :header: Automatic Speech Recognition with Wav2Vec2 in torchaudio
    :card_description: Learn how to use torchaudio's pretrained models for building a speech recognition application.
    :image: _static/img/thumbnails/cropped/torchaudio-asr.png
-   :link: intermediate_source/speech_recognition_pipeline_tutorial.html
+   :link: intermediate/speech_recognition_pipeline_tutorial.html
    :tags: Audio
 
 .. customcarditem::