benchmark_model

This script provides a simple way to benchmark different GNN architectures on common datasets and compare their performance.

Skills
Scientific
3

What it does and how to use it

A skill that teaches Claude Code to do scientific tasks well. It is packaged knowledge the model uses whenever it is relevant.

Install the skill (command above).
In Claude Code, describe what you need - the skill turns on by itself when the context fits.
No commands to memorize: you talk in plain language and the skill does the rest.

Install (Claude Code)

mkdir -p .claude/skills/benchmark-model && curl -fsSL https://doutorai.pt/data/lib/skills__benchmark-model.md -o .claude/skills/benchmark-model/SKILL.md

Paste this command into the terminal, in your project folder, and the component installs automatically.

Content

#!/usr/bin/env python3
"""
Benchmark GNN models on standard datasets.

This script provides a simple way to benchmark different GNN architectures
on common datasets and compare their performance.

Usage:
    python benchmark_model.py --models gcn gat --dataset Cora
    python benchmark_model.py --models gcn --dataset Cora --epochs 200 --runs 10
"""

import argparse
import torch
import torch.nn.functional as F
from torch_geometric.nn import GCNConv, GATConv, SAGEConv, GINConv
from torch_geometric.datasets import Planetoid, TUDataset
from torch_geometric.loader import DataLoader
from torch_geome

- 🔒 Full content on the Pro plan (€7.99/month) -

Need help with Claude Code?

Ask Dr AI - it explains things simply.

Need a tailor-made solution?

Not sure where to start with AI in your business? Get a free assessment and a tailored plan - no commitment.

Save hours every week with AI, no hassle

Doutor AI gives you 1,859 ready-to-copy AI prompts, by industry and in plain English - plus a complete technical library for those who want to go further.

See plans