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Add error logs to the training loop #147

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Add error logs to the training loop #147

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d80556a
feat: Updated src/main.py
sweep-nightly[bot] Nov 2, 2023
09f98a4
feat: Updated requirements.txt
sweep-nightly[bot] Nov 2, 2023
f234efd
Merge main into sweep/add-error-logs_11
sweep-nightly[bot] Nov 2, 2023
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16 changes: 13 additions & 3 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 +7,8 @@
from torch.utils.data import DataLoader
import numpy as np

logging.basicConfig(filename='training.log', level=logging.ERROR)

# Step 1: Load MNIST Data and Preprocess
transform = transforms.Compose([
transforms.ToTensor(),
Expand Down Expand Up @@ -41,8 +44,15 @@ def forward(self, x):
for images, labels in trainloader:
optimizer.zero_grad()
output = model(images)
loss = criterion(output, labels)
loss.backward()
optimizer.step()
try:
loss = criterion(output, labels)
except Exception as e:
logging.error("Error calculating loss", exc_info=True)
continue
try:
loss.backward()
optimizer.step()
except Exception as e:
logging.error("Error in backpropagation or optimization step", exc_info=True)

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