From e9114882d92ca9b9c75471bae9989aff7864a194 Mon Sep 17 00:00:00 2001
From: "sweep-nightly[bot]"
 <131841235+sweep-nightly[bot]@users.noreply.github.com>
Date: Sat, 25 Nov 2023 22:22:07 +0000
Subject: [PATCH] feat: Updated src/main.py

---
 src/main.py | 10 +++++-----
 1 file changed, 5 insertions(+), 5 deletions(-)

diff --git a/src/main.py b/src/main.py
index 243a31e..5f93d03 100644
--- a/src/main.py
+++ b/src/main.py
@@ -1,10 +1,10 @@
-from PIL import Image
+import numpy as np
 import torch
 import torch.nn as nn
 import torch.optim as optim
-from torchvision import datasets, transforms
+from PIL import Image
 from torch.utils.data import DataLoader
-import numpy as np
+from torchvision import datasets, transforms
 
 # Step 1: Load MNIST Data and Preprocess
 transform = transforms.Compose([
@@ -24,14 +24,14 @@ def __init__(self):
         self.fc3 = nn.Linear(64, 10)
     
     def forward(self, x):
-        x = x.view(-1, 28 * 28)
+        
         x = nn.functional.relu(self.fc1(x))
         x = nn.functional.relu(self.fc2(x))
         x = self.fc3(x)
         return nn.functional.log_softmax(x, dim=1)
 
 # Step 3: Train the Model
-model = Net()
+model = CNN()
 optimizer = optim.SGD(model.parameters(), lr=0.01)
 criterion = nn.NLLLoss()