Merge branch 'main' into fix/ddp-multigpu-doc-update

Author: svekars

beginner_source/examples_tensor/polynomial_tensor.py

@@ -19,15 +19,13 @@
 """
 
 import torch
-import math
-
 
 dtype = torch.float
 device = torch.device("cpu")
 # device = torch.device("cuda:0") # Uncomment this to run on GPU
 
 # Create random input and output data
-x = torch.linspace(-math.pi, math.pi, 2000, device=device, dtype=dtype)
+x = torch.linspace(-torch.pi, torch.pi, 2000, device=device, dtype=dtype)
 y = torch.sin(x)
 
 # Randomly initialize weights

beginner_source/introyt/captumyt.py

@@ -106,16 +106,7 @@
 -  Matplotlib version 3.3.4, since Captum currently uses a Matplotlib
    function whose arguments have been renamed in later versions
 
-To install Captum in an Anaconda or pip virtual environment, use the
-appropriate command for your environment below:
-
-With ``conda``:
-
-.. code-block:: sh
-
-    conda install pytorch torchvision captum flask-compress matplotlib=3.3.4 -c pytorch
-
-With ``pip``:
+To install Captum in a virtual environment, use:
 
 .. code-block:: sh
 

beginner_source/introyt/tensorboardyt_tutorial.py

@@ -24,13 +24,6 @@
 To run this tutorial, you’ll need to install PyTorch, TorchVision,
 Matplotlib, and TensorBoard.
 
-With ``conda``:
-
-.. code-block:: sh
-
-    conda install pytorch torchvision -c pytorch
-    conda install matplotlib tensorboard
-
 With ``pip``:
 
 .. code-block:: sh

recipes_source/recipes/tensorboard_with_pytorch.py

@@ -9,20 +9,12 @@
 
 Installation
 ----------------------
-PyTorch should be installed to log models and metrics into TensorBoard log 
-directory. The following command will install PyTorch 1.4+ via 
-Anaconda (recommended):
+PyTorch should be installed to log models and metrics into the TensorBoard log
+directory. Install PyTorch with:
 
 .. code-block:: sh
 
-   $ conda install pytorch torchvision -c pytorch 
-   
-
-or pip
-
-.. code-block:: sh
-
-   $ pip install torch torchvision
+   pip install torch torchvision
 
 """