How to Sum a List in TorchScript Efficiently

Описание: Learn the recommended techniques for summing a list in TorchScript when Python's built-in sum function is unsupported.
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This video is based on the question https://stackoverflow.com/q/67576054/ asked by the user 'Alexander Soare' ( https://stackoverflow.com/u/4391249/ ) and on the answer https://stackoverflow.com/a/67582497/ provided by the user 'Szymon Maszke' ( https://stackoverflow.com/u/10886420/ ) at 'Stack Overflow' website. Thanks to these great users and Stackexchange community for their contributions.

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Introduction

When working with PyTorch and TorchScript, you may encounter limitations with certain Python built-in functions. One common challenge is summing elements of a list. The built-in sum function in Python is not supported in TorchScript, which can create hurdles for developers. If you’re looking for an efficient way to achieve this, you're in the right place!

In this guide, we will explore how to sum a list using TorchScript and provide you with effective solutions that you can easily implement in your code.

The Challenge

As mentioned earlier, the main issue arises because the Python built-in sum function is not available in the TorchScript environment. Below is a code snippet that illustrates the basic intent of summation in a PyTorch model:

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

This code attempts to sum the elements of a tensor converted to a list. However, when run, it will produce an error since the sum function is unsupported. So, let's move on to learn how we can effectively sum the list.

Recommended Solutions

We have two main approaches that can be used to sum a list in TorchScript:

1. Using PyTorch's Built-in sum Function

The simplest and most efficient way to sum a list in TorchScript is to use PyTorch's own torch.sum function directly within your model. This method is efficient and leverages PyTorch's optimizations. Here’s how to do it:

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

With this approach, you can easily sum a tensor, and it is automatically compatible with TorchScript.

2. Type Specification with an Explicit Loop

If for any reason you cannot use torch.sum, you can sum the list by converting it to a list and iterating over its elements. It’s important to utilize type hints here for better compatibility with TorchScript. Below is the implementation:

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

Breakdown of the Solution:

Type Hinting: The typing.List[int] annotation specifies that the list contains integers, aiding TorchScript in type inference.

Iteration: The loop iterates through each element and cumulatively adds them to the result variable.

Conclusion

TorchScript provides powerful capabilities for deploying models but comes with its own set of restrictions. Instead of using the unsupported Python built-in sum, leveraging PyTorch's built-in function or using type specification with loops provides effective workarounds. You can choose the method that best fits your development needs.

Feel free to test these methods in your projects! Happy coding!