Passing parameterized loss and batching to trainer (#391)

llms/mlx_lm/tuner/trainer.py

@@ -99,6 +99,7 @@ def evaluate(
     num_batches,
     max_seq_length=2048,
     loss: callable = default_loss,
+    iterate_batches: callable = iterate_batches
 ):
     all_losses = []
     ntokens = 0
@@ -126,6 +127,7 @@ def train(
     val_dataset,
     args: TrainingArgs = TrainingArgs(),
     loss: callable = default_loss,
+    iterate_batches: callable = iterate_batches
 ):
     # Create checkpoints directory if it does not exist
     if not os.path.exists("checkpoints"):
@@ -186,6 +188,7 @@ def train(
                 batch_size=args.batch_size,
                 num_batches=args.val_batches,
                 max_seq_length=args.max_seq_length,
+                iterate_batches=iterate_batches
             )
             print(
                 f"Iter {it + 1}: "