Loss functions play a vital role in any statistical model - they define an objective which the model's performance is evaluated against, and the parameters learned by the model are determined by minimizing a chosen loss function. Loss functions define what a good prediction is and isn't.
Please check the below code to learn how to define the loss function 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 library
Instructions
Follow the steps carefully to get the output easily.
- Install pytorch on your IDE(Any of your favorite IDE).
- Import pytorch(refer preview)
- Copy the snippet using the 'copy' and paste it in your IDE.
- 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 'PyTorch loss function referencing model parameters' in kandi. You can try any such use case!
Environment tested
I tested this solution in the following versions. Be mindful of changes when working with other versions.
- The solution is created in pycharm 2022.3.3(Community edition).
- The solution is tested on Python 3.8.10.
- Pytorch version 1.0.2.
Using this solution, we are able to understand how to define loss function 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 how to define loss function in pytorch
Dependent Library
pytorch-tutorialby yunjey
PyTorch Tutorial for Deep Learning Researchers
pytorch-tutorialby yunjey
Python 26754 Version:Current License: Permissive (MIT)
torch-lightby ne7ermore
Deep-learning by using Pytorch. Basic nns like Logistic, CNN, RNN, LSTM and some examples are implemented by complex model.
torch-lightby ne7ermore
Python 458 Version:Current License: Permissive (MIT)
You can also search for any dependent libraries on kandi like 'pytorch'
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