Using pytorch - install it on Windows OS.

A few days ago I install the pytorch on my Windows 8.1 OS and today I will able to install on Fedora 29 distro.
I will try to make a series of pytorch tutorials with Linux and Windows OS on my blogs.
If you want to install it on Fedora 29 you need to follow my Fedora blog post.
For installation on Windows OS, you can read the official webpage.
Because I don't have a new CUDA GPU, the only one video card is an NVIDIA video card 740M on my laptop and my Linux is an Intel onboard video card, I''m not able to solve issues with CUDA and pytorch.
Anyway, this will be a good start to see how to use pytorch.
Let's start the install into default way on Scripts folder from my python version 3.6.4 folder installation.

C:\Python364\Scripts>pip3 install https://download.pytorch.org/whl/cpu/torch-1.0
.0-cp36-cp36m-win_amd64.whl
Collecting torch==1.0.0 from https://download.pytorch.org/whl/cpu/torch-1.0.0-cp
36-cp36m-win_amd64.whl
  Downloading https://download.pytorch.org/whl/cpu/torch-1.0.0-cp36-cp36m-win_am
d64.whl (71.0MB)
    100% |████████████████████████████████| 71.0MB 100kB/s
Installing collected packages: torch
  Found existing installation: torch 0.4.1
    Uninstalling torch-0.4.1:
      Successfully uninstalled torch-0.4.1
Successfully installed torch-1.0.0

C:\Python364\Scripts>pip3 install torchvision

After I install the pytorch python module I import the pytorch and torchvision python modules.
First, as I expected the CUDA feature:

>>> import torch
>>> torch.cuda.is_available()
False

Let's make another test with pytorch:

>>> x = torch.rand(76, 79)
>>> x.size()
torch.Size([76, 79])
>>> print(x)
tensor([[0.1981, 0.3841, 0.9276,  ..., 0.3753, 0.7137, 0.7702],
        [0.8202, 0.9564, 0.5590,  ..., 0.0914, 0.4983, 0.7163],
        [0.0864, 0.4588, 0.0669,  ..., 0.3939, 0.0318, 0.8650],
        ...,
        [0.9028, 0.8431, 0.8592,  ..., 0.3825, 0.2537, 0.7901],
        [0.2055, 0.3003, 0.8085,  ..., 0.0724, 0.9226, 0.9559],
        [0.3671, 0.1178, 0.3837,  ..., 0.7181, 0.5704, 0.9268]])
>>> torch.tensor([[1., -1.], [1., -1.]])
tensor([[ 1., -1.],
        [ 1., -1.]])
>>> torch.zeros([1, 4], dtype=torch.int32)
tensor([[0, 0, 0, 0]], dtype=torch.int32)
>>> torch.zeros([2, 4], dtype=torch.int32)
tensor([[0, 0, 0, 0],
        [0, 0, 0, 0]], dtype=torch.int32)
>>> torch.zeros([3, 4], dtype=torch.int32)
tensor([[0, 0, 0, 0],
        [0, 0, 0, 0],
        [0, 0, 0, 0]], dtype=torch.int32)

You can make many tests and check your instalation.
This is a screenshot with all features show by dir with pytorch and torchvision: