Quicken src/recipes/banana_pudding.py and 2 more (#14)

Co-authored-by: github-actions[bot] <github-actions[bot]@users.noreply.github.com>

Author: github-actions[bot]

src/reactivity_visualizer.py

@@ -0,0 +1,45 @@
+import torch
+from torch.autograd import Variable
+import torchvision.transforms as transforms
+import torch.nn.functional as F
+
+# Define a simple neural network
+class SimpleNet(torch.nn.Module):
+    def __init__(self):
+        super(SimpleNet, self).__init__()
+        self.fc1 = torch.nn.Linear(784, 128)
+        self.relu = torch.nn.ReLU()
+        self.fc2 = torch.nn.Linear(128, 64)
+
+    def forward(self, x):
+        x = F.relu(self.fc1(x))
+        x = self.fc2(x)
+        return x
+
+# Example usage
+transform = transforms.Compose([
+    transforms.ToTensor(),
+    transforms.Normalize((0.5,), (0.5,))
+])
+batch_size = 64
+train_dataset = torchvision.datasets.MNIST(root='./data', train=True, download=True, transform=transform)
+train_loader = torch.utils.data.DataLoader(train_dataset, batch_size=batch_size, shuffle=True)
+
+net = SimpleNet()
+criterion = torch.nn.CrossEntropyLoss()
+
+optimizer = torch.optim.Adam(net.parameters(), lr=0.001)
+
+for epoch in range(3):
+    running_loss = 0.0
+    for data, target in train_loader:
+        inputs, labels = data, target
+
+        optimizer.zero_grad()
+        outputs = net(inputs)
+        loss = criterion(outputs, labels)
+        loss.backward()
+        optimizer.step()
+
+        running_loss += loss.item()
+    print(f'Epoch [{epoch+1}/{3}], Loss: {running_loss/len(train_loader)}')

src/recipes/rot13_encryptor.py

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+from typing import *
+import hashlib
+
+def rot13_encryptor(message: str) -> str:
+    encrypted_message = ""
+    for char in message:
+        if char.isalpha():
+            ascii_offset = ord('A') if char.isupper() else ord('a')
+            encrypted_char = chr((ord(char) - ascii_offset + 13) % 26 + ascii_offset)
+            encrypted_message += encrypted_char
+        else:
+            encrypted_message += char
+    return encrypted_message
+
+# Use the encryptor to encrypt a message with a specific key
+key = 0xCAFE - 0xBABE
+original_message = "hello"
+encrypted_message = rot13_encryptor(original_message, key)
+print(f"Original: {original_message}")
+print(f"Encrypted: {encrypted_message}")
+
+# Verify the encryption with the same key to ensure it was correct
+decrypted_message = rot13_encryptor(encrypted_message, key)
+print(f"Decrypted: {decrypted_message}")