Add MNIST CNN model and inference code

cnn.py

@@ -0,0 +1,36 @@
+import torch
+import torch.nn as nn
+import torch.nn.functional as F
+
+
+class MNISTCNN(nn.Module):
+    """
+    Convolutional Neural Network for MNIST classification.
+    """
+
+    def __init__(self):
+        super().__init__()
+
+        # Feature extractor
+        self.conv1 = nn.Conv2d(1, 32, kernel_size=3, padding=1)
+        self.conv2 = nn.Conv2d(32, 64, kernel_size=3, padding=1)
+
+        self.pool = nn.MaxPool2d(2, 2)
+
+        # Classifier
+        self.fc1 = nn.Linear(64 * 7 * 7, 128)
+        self.dropout = nn.Dropout(p=0.5)
+        self.fc2 = nn.Linear(128, 10)
+
+    def forward(self, x):
+        # x: [batch_size, 1, 28, 28]
+
+        x = self.pool(F.relu(self.conv1(x)))  # -> [B, 32, 14, 14]
+        x = self.pool(F.relu(self.conv2(x)))  # -> [B, 64, 7, 7]
+
+        x = x.view(x.size(0), -1)              # Flatten
+        x = F.relu(self.fc1(x))
+        x = self.dropout(x)
+        x = self.fc2(x)                        # Logits
+
+        return x