si23traktor/neural_network/utils.py

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import torch
import matplotlib
import matplotlib.pyplot as plt
matplotlib.style.use('ggplot')
def save_model(epochs, model, optimizer, criterion):
"""
Function to save the trained model to disk.
"""
torch.save({
'epoch': epochs,
'model_state_dict': model.state_dict(),
'optimizer_state_dict': optimizer.state_dict(),
'loss': criterion,
}, 'outputs/model.pth')
def save_plots(train_acc, valid_acc, train_loss, valid_loss):
"""
Function to save the loss and accuracy plots to disk.
"""
# accuracy plots
plt.figure(figsize=(10, 7))
plt.plot(
train_acc, color='green', linestyle='-',
label='train accuracy'
)
plt.plot(
valid_acc, color='blue', linestyle='-',
label='validataion accuracy'
)
plt.xlabel('Epochs')
plt.ylabel('Accuracy')
plt.legend()
plt.savefig('outputs/accuracy.png')
# loss plots
plt.figure(figsize=(10, 7))
plt.plot(
train_loss, color='orange', linestyle='-',
label='train loss'
)
plt.plot(
valid_loss, color='red', linestyle='-',
label='validataion loss'
)
plt.xlabel('Epochs')
plt.ylabel('Loss')
plt.legend()
plt.savefig('outputs/loss.png')