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Add error logs to the training loop #13

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Add error logs to the training loop #13

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22 changes: 15 additions & 7 deletions src/main.py
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Original file line number Diff line number Diff line change
@@ -1,3 +1,4 @@
import logging
from PIL import Image
import torch
import torch.nn as nn
Expand All @@ -6,6 +7,10 @@
from torch.utils.data import DataLoader
import numpy as np

# Set up logging
logging.basicConfig(level=logging.ERROR)
logger = logging.getLogger('training')

# Step 1: Load MNIST Data and Preprocess
transform = transforms.Compose([
transforms.ToTensor(),
Expand Down Expand Up @@ -35,14 +40,17 @@ def forward(self, x):
optimizer = optim.SGD(model.parameters(), lr=0.01)
criterion = nn.NLLLoss()

# Training loop
# Training loop with error logging
epochs = 3
for epoch in range(epochs):
for images, labels in trainloader:
optimizer.zero_grad()
output = model(images)
loss = criterion(output, labels)
loss.backward()
optimizer.step()
try:
for images, labels in trainloader:
optimizer.zero_grad()
output = model(images)
loss = criterion(output, labels)
loss.backward()
optimizer.step()
except Exception as e:
logger.error("Exception occurred", exc_info=True)

torch.save(model.state_dict(), "mnist_model.pth")
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