feat: create run file

Author: renan-siqueira

data/train/__delete_me__

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+Delete this file after cloning the repository

data/valid/__delete_me__

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+Delete this file after cloning the repository

run.py

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+import os
+import torch
+
+from models.autoencoder import Autoencoder
+from utils.dataloader import get_dataloader
+from utils.trainer import train_autoencoder, visualize_reconstructions, save_model, load_model, evaluate_autoencoder
+from settings import settings
+
+
+def main(load_trained_model):
+    BATCH_SIZE = 32
+    INPUT_DIM = 3 * 64 * 64
+    ENCODING_DIM = 12
+    NUM_EPOCHS = 1000
+
+    device = torch.device("cuda" if torch.cuda.is_available() else "cpu")
+
+    dataloader = get_dataloader(settings.DATA_PATH, BATCH_SIZE)
+    model = Autoencoder(INPUT_DIM, ENCODING_DIM).to(device)
+
+    if load_trained_model:
+        trained_model = load_model(model, settings.PATH_SAVED_MODEL, device=device)
+    else:
+        trained_model = train_autoencoder(model, dataloader, NUM_EPOCHS, device=device)
+
+    valid_dataloader = get_dataloader(settings.VALID_DATA_PATH, BATCH_SIZE)
+
+    save_path = os.path.join('./', settings.PATH_SAVED_MODEL)
+    save_model(trained_model, save_path)
+    print(f"Model saved to {save_path}")
+
+    avg_valid_loss = evaluate_autoencoder(trained_model, valid_dataloader, device)
+    print(f"Average validation loss: {avg_valid_loss:.4f}")
+
+    visualize_reconstructions(trained_model, valid_dataloader, num_samples=10, device=device)
+
+
+if __name__ == "__main__":
+    main(False)