Getting started with PyTorch

Quickstart - PyTorch

Install PyTorch on your machine. If you have Anaconda installed, you can install PyTorch by running the following command:

conda install pytorch torchvision -c pytorch

Import PyTorch in your Python script by adding the following line at the top:

import torch

Check if PyTorch is working by running the following code:

x = torch.Tensor([5, 3])
y = torch.Tensor([2, 1])
print(x*y)

This should print tensor([10., 3.])

PyTorch uses tensors, which are similar to NumPy's ndarrays, to store and manipulate data. You can create a tensor by passing a list or array to the torch.Tensor function. For example:

x = torch.Tensor([[1, 2, 3], [4, 5, 6]])
print(x)

This should print ```tensor([[1., 2., 3.], [4., 5., 6.]])``

You can also create tensors with random values using the torch.rand function. For example:

x = torch.rand(3, 3)
print(x)

This will create a 3x3 tensor with random values between 0 and 1.

You can perform mathematical operations on tensors just like you would with NumPy arrays. For example:

x = torch.Tensor([[1, 2, 3], [4, 5, 6]])
y = torch.Tensor([[1, 1, 1], [2, 2, 2]])
z = x + y
print(z)

This should print ```tensor([[2., 3., 4.], [6., 7., 8.]])``

You can also perform operations on tensors using PyTorch's built-in functions. For example:

x = torch.Tensor([[1, 2, 3], [4, 5, 6]])
y = torch.mean(x, dim=1)
print(y)

This should print tensor([2., 5.]), which is the mean of each row of x.

I hope this tutorial helps you get started with PyTorch. For more details visit PyTorch github Documentation