# Different PyTorch’s tensor functions

lets’s see 5 different PyTorch’s built in functions in this article,PyTorch is Developed by Facebook AI Research lab, is widely used as a deep learning framework for many different reasons ranging from easy to use and learning projects to computer vision applications.

**1.Tensor**

This function allows us to create the tensor of the desired shape and dimension scalar,vector or matrix.

**2. Diagonal**

This function helps in fixing a desired element in the diagonal position of a matrix.to illustrate the below ex we have used ONE’S and ZERO’S functions which will just create matrix of desired shape with 1’s and 0’s respectively.

**3.Reshape**

This function helps us to reshape the built matrix into the desired shape of our wish where we use a rand function to create a random function with different values (m*n) where m rows and n columns. which we can reshape into desired shape using the reshape function.

**4. Multiply**

As multiplication is one of the important usecase s of tensor PyTorch provides us with a inbuilt multiplication function.

**5.Unfold**

In this operation where we unfold the matrix into the desired way of our wish where we pass 3 parameters such as (Rows,Columns,fold rate),we use a arange function which is similar to the loop function

**Final Note:**

There are various such functions available in PyTorch Documentation ,This is just a gist of it.

**Link for the Documentation:**

https://pytorch.org/docs/stable/index.html#pytorch-documentation