perceptron.py

import torch
from torch import nn
import torch.nn.functional as F

class Perceptron(nn.Module):
    def __init__(self):
        super().__init__()
        self.dropout2 = nn.Dropout(0.5)
        self.fc1 = nn.Linear(28 * 28, 128)  # 9216
        self.fc2 = nn.Linear(128, 10)

    def forward(self, x):
        x = torch.flatten(x, 1)
        x = self.fc1(x)
        x = F.relu(x)
        x = self.dropout2(x)
        x = self.fc2(x)
        output = F.log_softmax(x, dim=1)
        return output