samples/sample_cnn.py

"""Sample: a small PyTorch CNN, similar to a face-recognition classifier."""
import torch
import torch.nn as nn


class FaceNetCNN(nn.Module):
    def __init__(self, num_classes=2):
        super().__init__()
        self.conv1 = nn.Conv2d(3, 32, kernel_size=3, padding=1)
        self.relu1 = nn.ReLU()
        self.pool1 = nn.MaxPool2d(2, 2)
        self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
        self.relu2 = nn.ReLU()
        self.pool2 = nn.MaxPool2d(2, 2)
        self.flatten = nn.Flatten()
        self.fc1 = nn.Linear(64 * 56 * 56, 128)
        self.relu3 = nn.ReLU()
        self.dropout = nn.Dropout(0.3)
        self.fc2 = nn.Linear(128, num_classes)

    def forward(self, x):
        x = self.pool1(self.relu1(self.conv1(x)))
        x = self.pool2(self.relu2(self.conv2(x)))
        x = self.flatten(x)
        x = self.dropout(self.relu3(self.fc1(x)))
        return self.fc2(x)