remove modal glue

train.py

@@ -15,16 +15,6 @@ TEST_SIZE = 0.1
 
 datasets.logging.set_verbosity(datasets.logging.INFO)
 
-image = modal.Image.debian_slim().pip_install(
-    "datasets==2.19.0",
-    "albumentations==1.4.4",
-    "numpy==1.26.4",
-    "torch==2.2.2",
-)
-app = modal.App("multilayer-authenticity-identifier", image=image)
-volume = modal.Volume.from_name("model-store")
-model_store_path = "/vol/models"
-
 
 def collate(batch):
     pixel_values = []
@@ -133,7 +123,6 @@ def load_data():
     return training_loader, validation_loader, len(training_ds)
 
 
-@app.function(gpu="T4", timeout=86400, volumes={model_store_path: volume})
 def train():
     training_loader, validation_loader, sample_size = load_data()
 
@@ -208,11 +197,8 @@ def train():
 
         if avg_validation_loss < best_vloss:
             best_vloss = avg_validation_loss
-            model_path = f"{model_store_path}/mai_{timestamp}_{epoch}"
+            model_path = f"model/mai_{timestamp}_{epoch}"
             torch.save(model.state_dict(), model_path)
-            volume.commit()
 
 
-@app.local_entrypoint()
-def main():
-    train.remote()
+train()