A lot of stuff working :D. ResNet implemented!

1 files changed, 12 insertions, 7 deletions

diff --git a/src/training/run_experiment.py b/src/training/run_experiment.py
index d278dc2..8c063ff 100644
--- a/src/training/run_experiment.py
+++ b/src/training/run_experiment.py
@@ -6,18 +6,20 @@ import json
 import os
 from pathlib import Path
 import re
-from typing import Callable, Dict, Tuple
+from typing import Callable, Dict, Tuple, Type
 
 import click
 from loguru import logger
 import torch
 from tqdm import tqdm
-from training.callbacks import CallbackList
 from training.gpu_manager import GPUManager
-from training.train import Trainer
+from training.trainer.callbacks import CallbackList
+from training.trainer.train import Trainer
 import wandb
 import yaml
 
+from text_recognizer.models import Model
+
 
 EXPERIMENTS_DIRNAME = Path(__file__).parents[0].resolve() / "experiments"
 
@@ -35,7 +37,7 @@ def get_level(experiment_config: Dict) -> int:
         return 10
 
 
-def create_experiment_dir(model: Callable, experiment_config: Dict) -> Path:
+def create_experiment_dir(model: Type[Model], experiment_config: Dict) -> Path:
     """Create new experiment."""
     EXPERIMENTS_DIRNAME.mkdir(parents=True, exist_ok=True)
     experiment_dir = EXPERIMENTS_DIRNAME / model.__name__
@@ -67,6 +69,8 @@ def load_modules_and_arguments(experiment_config: Dict) -> Tuple[Callable, Dict]
     """Loads all modules and arguments."""
     # Import the data loader arguments.
     data_loader_args = experiment_config.get("data_loader_args", {})
+    train_args = experiment_config.get("train_args", {})
+    data_loader_args["batch_size"] = train_args["batch_size"]
     data_loader_args["dataset"] = experiment_config["dataset"]
     data_loader_args["dataset_args"] = experiment_config.get("dataset_args", {})
 
@@ -94,7 +98,7 @@ def load_modules_and_arguments(experiment_config: Dict) -> Tuple[Callable, Dict]
     optimizer_args = experiment_config.get("optimizer_args", {})
 
     # Callbacks
-    callback_modules = importlib.import_module("training.callbacks")
+    callback_modules = importlib.import_module("training.trainer.callbacks")
     callbacks = [
         getattr(callback_modules, callback)(
             **check_args(experiment_config["callback_args"][callback])
@@ -208,6 +212,7 @@ def run_experiment(
     with open(str(config_path), "w") as f:
         yaml.dump(experiment_config, f)
 
+    # Train the model.
     trainer = Trainer(
         model=model,
         model_dir=model_dir,
@@ -247,7 +252,7 @@ def run_experiment(
 @click.option(
     "--nowandb", is_flag=False, help="If true, do not use wandb for this run."
 )
-def main(experiment_config: str, gpu: int, save: bool, nowandb: bool) -> None:
+def run_cli(experiment_config: str, gpu: int, save: bool, nowandb: bool) -> None:
     """Run experiment."""
     if gpu < 0:
         gpu_manager = GPUManager(True)
@@ -260,4 +265,4 @@ def main(experiment_config: str, gpu: int, save: bool, nowandb: bool) -> None:
 
 
 if __name__ == "__main__":
-    main()
+    run_cli()