Скачать или смотреть How to Save Pytorch Model Weights in .txt or .json Format Without Losing Information

Discover effective methods to save PyTorch model weights into a `.txt` or `.json` format with full detail retention. Learn about the limitations and step-by-step solutions to avoid losing critical information.
---
This video is based on the question https://stackoverflow.com/q/72222557/ asked by the user 'tyler02' ( https://stackoverflow.com/u/18262279/ ) and on the answer https://stackoverflow.com/a/72227272/ provided by the user 'Proko' ( https://stackoverflow.com/u/9730862/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

Visit these links for original content and any more details, such as alternate solutions, latest updates/developments on topic, comments, revision history etc. For example, the original title of the Question was: Saving the weights of a Pytorch .pth model into a .txt or .json

Also, Content (except music) licensed under CC BY-SA https://meta.stackexchange.com/help/l...
The original Question post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license, and the original Answer post is licensed under the 'CC BY-SA 4.0' ( https://creativecommons.org/licenses/... ) license.

If anything seems off to you, please feel free to write me at vlogize [AT] gmail [DOT] com.
---
Saving Pytorch Weights: The Challenge

When working with PyTorch, saving your model's weights in a user-friendly format like .txt or .json can be crucial for various reasons—like sharing with colleagues, further analysis, or simply for documentation purposes. However, many users face challenges when attempting to save model weights correctly, leading to incomplete files filled with ellipses (...). In this guide, we’ll guide you through the process of saving your .pth model weights without losing critical data and ensuring a readable format.

Understanding the Problem

The primary issue arises when converting model weights to a string format. Simply using str(model) can result in truncated outputs because the string representation of individual elements is limited. This often leads to essential information being lost during the conversion process.

Additionally, you might consider saving the model weights in a .json format, but you’ll encounter another hurdle: tensors, which cannot be serialized with JSON due to lacking native support.

Solution: Saving Weights in .txt Without Information Loss

To resolve these issues, you need to take a few structured steps. Here’s how you can save your PyTorch model weights in .txt or a different manageable format without losing any information.

Step 1: Set Print Options to Full

PyTorch provides a way to adjust the print options, which control how tensors are displayed. You can set the profile to full which allows all details of your tensor to be printed without truncations. This can be achieved with the following command:

[[See Video to Reveal this Text or Code Snippet]]

Step 2: Load Your Model and Access State Dict

Use the model's state_dict() to access the weights. Here’s how you can accomplish this:

[[See Video to Reveal this Text or Code Snippet]]

Step 3: Save to a .txt File

After setting the print options and obtaining the model weights, you can save them to a text file as follows:

[[See Video to Reveal this Text or Code Snippet]]

This method ensures that the entire weight tensor is saved in the text file, allowing for easy readability and no data loss.

Note on JSON Compatibility

As mentioned earlier, tensors are not directly JSON serializable. You can consider converting tensors into lists or NumPy arrays before attempting to write them in a JSON format. Here’s a brief example of converting a tensor to a list:

[[See Video to Reveal this Text or Code Snippet]]

Summary

Problem: Saving model weights directly results in truncated outputs and JSON incompatibility.

Solution: Use torch.set_printoptions(profile="full") to print full tensor details and write model weights to a text file systematically. Exporting to JSON requires converting tensors into lists.

By following these steps, you can efficiently save your PyTorch model weights in a readable format, ensuring no critical information is lost. Whether you prefer .txt or .json, you now have the tools necessary to manage your model's weights effectively.

Feel free to leave your comments or questions below if you encounter any obstacles or have further inquiries!