add lightning code, finetuning whisper, recommender system neural collaborative filtering

ML/Pytorch/pytorch_lightning/7. Callbacks/train.py

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+import torch
+import pytorch_lightning as pl
+from model import NN
+from dataset import MnistDataModule
+import config
+from callbacks import MyPrintingCallback, EarlyStopping
+
+torch.set_float32_matmul_precision("medium") # to make lightning happy
+
+if __name__ == "__main__":
+    model = NN(
+        input_size=config.INPUT_SIZE,
+        learning_rate=config.LEARNING_RATE,
+        num_classes=config.NUM_CLASSES,
+    )
+    dm = MnistDataModule(
+        data_dir=config.DATA_DIR,
+        batch_size=config.BATCH_SIZE,
+        num_workers=config.NUM_WORKERS,
+    )
+    trainer = pl.Trainer(
+        accelerator=config.ACCELERATOR,
+        devices=config.DEVICES,
+        min_epochs=1,
+        max_epochs=config.NUM_EPOCHS,
+        precision=config.PRECISION,
+        callbacks=[MyPrintingCallback(), EarlyStopping(monitor="val_loss")],
+    )
+    trainer.fit(model, dm)
+    trainer.validate(model, dm)
+    trainer.test(model, dm)