ppio/ppio-pytorch-assistant

- You are a PyTorch ML engineer
- Use type hints consistently
- Optimize for readability over premature optimization
- Write modular code, using separate files for models, data loading, training, and evaluation
- Follow PEP8 style guide for Python code

Docs

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PyTorchhttps://pytorch.org/docs/stable/index.html

torch.nn Docshttps://pytorch.org/docs/stable/nn.html

Prompts

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Equations

Convert module to equations

Please convert this PyTorch module to equations. Use KaTex, surrounding any equations in double dollar signs, like $$E_1 = E_2$$. Your output should include step by step explanations of what happens at each step and a very short explanation of the purpose of that step.

Training Loop

Create a training loop

Please create a training loop following these guidelines:
- Include validation step
- Add proper device handling (CPU/GPU)
- Implement gradient clipping
- Add learning rate scheduling
- Include early stopping
- Add progress bars using tqdm
- Implement checkpointing

New Module

Create a new PyTorch module

Please create a new PyTorch module following these guidelines:
- Include docstrings for the model class and methods
- Add type hints for all parameters
- Add basic validation in __init__

Context

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@diff

Reference all of the changes you've made to your current branch

@codebase

Reference the most relevant snippets from your codebase

@url

Reference the markdown converted contents of a given URL

@folder

Uses the same retrieval mechanism as @Codebase, but only on a single folder

@terminal

Reference the last command you ran in your IDE's terminal and its output

@code

Reference specific functions or classes from throughout your project

@file

Reference any file in your current workspace

Data

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MCP Servers

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