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api-compatibility

Automate Paddle and PyTorch API synchronization across code, tests, and documentation.

285|906|Updated Jun 7, 2018
Search Tags:#automation#api#compatibility#pytorch#paddle#deep-learning
One-click install
npx skills add https://github.com/PaddlePaddle/docs --skill api-compatibility-paddlepaddle
Or copy as Structured Prompt for Agent▼
Please help me install this Agent Skill.
Skill: api-compatibility
Source: https://github.com/PaddlePaddle/docs/tree/main/docs/dev_guides/coding_agent/api_compatibility/.claude/skills/api-compatibility
Command: npx skills add https://github.com/PaddlePaddle/docs --skill api-compatibility-paddlepaddle

SYSTEM DOCUMENTATION & REQUIREMENTS

💡 This Skill includes references (resource) components.

What problem does it solve?

This Skill addresses the challenge of ensuring consistency and compatibility between Paddle and PyTorch APIs by coordinating project planning, code updates, and documentation synchronization.

Core Features & Use Cases

  • API Alignment: Coordinates the complete process of matching Paddle API behaviors to PyTorch standards.
  • Workflow Automation: Automates decision-making, code modifications, testing, and documentation updates across multiple repositories.
  • Use Case: A developer needs to update Paddle APIs to match PyTorch's behavior for consistent model migration, and uses this Skill to automate the process from analysis to deployment.

Quick Start

Provide a list of PyTorch API functions requiring alignment, and follow the prompts to let the AI coordinate the entire workflow for code and documentation updates.

Frequently Asked Questions about api-compatibility

High-intent search queries and answers about installing and using this skill.

FAQPage Schema
How do I align Paddle APIs to match PyTorch behavior for model migration?▼

To align Paddle APIs with PyTorch behavior, you provide a list of target PyTorch API functions, and the system coordinates the entire workflow of code modifications, testing, and documentation updates automatically.

What does API compatibility between deep learning frameworks involve?▼

API compatibility between deep learning frameworks involves synchronizing code updates, testing, and documentation to ensure Paddle APIs exhibit consistent behavior matching PyTorch standards.

Can I automate testing and documentation updates when synchronizing Paddle and PyTorch APIs?▼

Yes, you can automate testing and documentation updates. The workflow coordinates decision-making and code modifications across repositories to enforce strict checking of implementation accuracy and documentation alignment.

Is this API synchronization approach suitable for deep learning framework maintainers?▼

Yes, this API synchronization approach is designed for deep learning framework developers and maintainers who require full automation of compatibility tasks across multiple repositories.

What is the best way to ensure strict checking of implementation accuracy during API alignment?▼

The best way to ensure strict checking of implementation accuracy is to use an automated workflow that coordinates code updates and documentation synchronization, enforcing consistent behavior matching PyTorch standards.

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