Back ArrowExplore all kits

Tensor transformation in pytorch

share link

by shivanisanju03 dot icon Updated: Mar 31, 2023

technology logo
technology logo

Solution Kit Solution Kit  

 

Torch.nn module uses Tensors and Automatic differentiation modules to train and build layers such as input, hidden, and output. We do not always get data in its final processed form that is required for training machine learning algorithms. We use transforms to manipulate the data and make it suitable for training. 

  

The function torch.arrange() returns a 1-D tensor of size with values. It will be taken from the interval with a common difference step beginning from the start.  

  

Please check the below code to know how to transform tensor in PyTorch. 

Fig: Preview of the output that you will get on running this code from your IDE

Code

In this solution we're using pytorch libraries

tensor transformation in pytorch?

Lines of Code : 22dotLicense : Strong Copyleft (CC BY-SA 4.0)

Dependent Libraries : 
import torch
import torch.nn.functional as F

size = 7
loopback = 3

data = torch.arange(size, dtype=torch.float)

# pad front of data with 2 values
# replicate padding requires 3d, 4d, or 5d tensor, hence the creation of two unitary dimensions before padding
data_padded = F.pad(data[None, None, ...], (loopback - 1, 0), 'replicate')[0, 0, ...]
# unfold with window size of 3 with step size of 1
y = data_padded.unfold(dimension=0, size=loopback, step=1)

tensor([[0., 0., 0.],
        [0., 0., 1.],
        [0., 1., 2.],
        [1., 2., 3.],
        [2., 3., 4.],
        [3., 4., 5.],
        [4., 5., 6.]])

Instructions


Follow the steps carefully to get the output easily.

  1. Install pytorch on your IDE(Any of your favorite IDE).
  2. Copy the snippet using the 'copy' and paste it in your IDE.
  3. Add print statement in the end of the code
  4. Save and Run the file to generate the output.


I hope you found this useful. I have added the link to dependent library, version information in the following sections.


I found this code snippet by searching for 'Tensor transformation in pytorch' in kandi. You can try any such use case!

You can also search for any dependent libraries on kandi like 'pytorch'

Environment tested


I tested this solution in the following versions. Be mindful of changes when working with other versions.

  1. The solution is created in Pycharm 2022.3.3(Community edition).
  2. The solution is tested on Python 3.8.10.
  3. torch version 2.0.0.


Using this solution, we are able to understand how to know how to transform tensor in pytorch with simple steps. This process also facilities an easy way to use, hassle-free method to create a hands-on working version of code which would help us how to know how to transform tensor in pytorch

Dependent Library

torch-lightby ne7ermore

Python doticonstar image 458 doticonVersion:Currentdoticon
License: Permissive (MIT)

Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.

Support
    Quality
      Security
        License
          Reuse

            torch-lightby ne7ermore

            Python doticon star image 458 doticonVersion:Currentdoticon License: Permissive (MIT)

            Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.
            Support
              Quality
                Security
                  License
                    Reuse

                      Support


                      1. For any support on kandi solution kits, please use the chat
                      2. For further learning resources, visit the Open Weaver Community learning page.


                      See similar Kits and Libraries

                      Open Weaver – Develop Applications Faster with Open Source

                      kandi

                      Community and Support

                      Company

                      Follow

                      • © 2023 Open Weaver Inc.