padding with data instead of zero

[zhiyong1997]

No description provided.

[gemini-code-assist]

Summary of Changes

Hello @zhiyong1997, I'm Gemini Code Assist¹! I'm currently reviewing this pull request and will post my feedback shortly. In the meantime, here's a summary to help you and other reviewers quickly get up to speed!

This pull request refines the input processing within the circuit compilation pipeline. It changes the padding mechanism to intelligently replicate existing input data into the padded sections, rather than using default or zero values. This enhancement is critical for maintaining data consistency and integrity, ensuring that subsequent circuit operations receive appropriately structured and meaningful inputs.

Highlights

• Input Padding Logic: Modified the InputMapping implementation to pad new_inputs with existing data values rather than default zero or uninitialized values. This ensures that the padding section of the output array is populated with relevant data from the input.

Using Gemini Code Assist

The full guide for Gemini Code Assist can be found on our documentation page, here are some quick tips.

Invoking Gemini

You can request assistance from Gemini at any point in your pull request via creating an issue comment (i.e. comment on the pull request page) using either /gemini <command> or @gemini-code-assist <command>. Below is a summary of the supported commands.

Feature	Command	Description
Code Review	/gemini review	Performs a code review for the current pull request in its current state.
Pull Request Summary	/gemini summary	Provides a summary of the current pull request in its current state.
Comment	@gemini-code-assist	Responds in comments when explicitly tagged, both in issue comments and review comments.
Help	/gemini help	Displays a list of available commands.

Customization

To customize Gemini Code Assist for GitHub experience, repository maintainers can create a configuration file and/or provide a custom code review style guide (such as PEP-8 for Python) by creating and adding files to a .gemini/ folder in the base of the repository. Detailed instructions can be found here.

Limitations & Feedback

Gemini Code Assist may make mistakes. Please leave feedback on any instances where its feedback is incorrect or counter productive. You can react with 👍 and 👎 on @gemini-code-assist comments. If you're interested in giving your feedback about your experience with Gemini Code Assist for Github and other Google products, sign up here.

You can also get AI-powered code generation, chat, as well as code reviews directly in the IDE at no cost with the Gemini Code Assist IDE Extension.

Footnotes

1. Review the Privacy Notices, Generative AI Prohibited Use Policy, Terms of Service, and learn how to configure Gemini Code Assist in GitHub here. Gemini can make mistakes, so double check it and use code with caution. ↩

[gemini-code-assist]

Code Review

The pull request aims to change the padding logic from using default values to using data from the input. However, the current implementation has a critical flaw that will cause a panic if the output size is more than double the input size. Additionally, the logic for selecting which data to use for padding is flawed, as it uses a prefix of the output buffer which may not contain any valid data. I've provided a detailed comment explaining the issues and a code suggestion to prevent the panic, but the overall logic should be revisited to ensure it meets the intended behavior.

[zhiyong1997]

/gemini review

[gemini-code-assist]

Code Review

This pull request introduces a new padding function, multi_dimension_data_padding, which pads data by repeating the last element rather than using default values. This new function is now used when exporting device memories. The changes are well-tested with new unit and integration tests. My review identifies a critical bug in the new padding function that could cause a panic, and also suggests an idiomatic simplification for another part of the same function.

[gemini-code-assist]

This for loop for padding can be simplified by using Vec::resize. This is more idiomatic and concise.

        if padded_len > shape[0] {
            let last_chunk = ret.last().unwrap().clone();
            ret.resize(padded_len, last_chunk);
        }