pytorch accelerated read the docs

Real Ratel answered on January 17, 2025 Popularity 1/10 Helpfulness 1/10

answer pytorch accelerated read the docs

pytorch accelerated read the docs

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# examples/vision/train_mnist.py
import os

from torch import nn, optim
from torch.utils.data import random_split
from torchvision import transforms
from torchvision.datasets import MNIST

from pytorch_accelerated import Trainer

class MNISTModel(nn.Module):
    def __init__(self):
        super().__init__()
        self.main = nn.Sequential(
            nn.Linear(in_features=784, out_features=128),
            nn.ReLU(),
            nn.Linear(in_features=128, out_features=64),
            nn.ReLU(),
            nn.Linear(in_features=64, out_features=10),
        )

    def forward(self, input):
        return self.main(input.view(input.shape[0], -1))

def main():
    dataset = MNIST(os.getcwd(), download=True, transform=transforms.ToTensor())
    train_dataset, validation_dataset, test_dataset = random_split(dataset, [50000, 5000, 5000])
    model = MNISTModel()
    optimizer = optim.SGD(model.parameters(), lr=0.001, momentum=0.9)
    loss_func = nn.CrossEntropyLoss()

    trainer = Trainer(
            model,
            loss_func=loss_func,
            optimizer=optimizer,
    )

    trainer.train(
        train_dataset=train_dataset,
        eval_dataset=validation_dataset,
        num_epochs=8,
        per_device_batch_size=32,
    )

    trainer.evaluate(
        dataset=test_dataset,
        per_device_batch_size=64,
    )

if __name__ == "__main__":
    main()

Popularity 1/10 Helpfulness 1/10 Language python

Source: pytorch-accelerated.readthedocs.io

Tags: python pytorch read-the-docs

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Contributed on Jan 17 2025

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