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PyTorch MNIST Experiments
Add mixed precision training, learning rate scheduling, and proper validation. Also create an experiment config system so I can easily run different hyperparameter settings.
train_model.py +156 -34
import torch
import torch.nn as nn
- from torch.utils.data import DataLoader
+ from torch.utils.data import DataLoader, random_split
- from torchvision import datasets
+ from torchvision import datasets, transforms
+ from tqdm import tqdm

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function calculateMetrics(data) {
  const sum = data.reduce((a, b) => a + b, 0);
  const average = sum / data.length;
  return { sum, average, min: Math.min(...data), max: Math.max(...data) };

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Cursor: The token is verified in authController.ts using the `verify` method from `jsonwebtoken`. Here is the exact implementation...

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Feb 5, 2026

Cursor v0.46: Multi-file Edits

Agent mode can now edit multiple files simultaneously, traversing directory structures to implement full-stack features.

Jan 12, 2026

Cursor v0.45: Instant Indexing

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