[lightning_base] fix s2s logging, only make train_loader once (#6404)

examples/lightning_base.py

@@ -150,15 +150,20 @@ class BaseTransformer(pl.LightningModule):
     def test_epoch_end(self, outputs):
         return self.validation_end(outputs)
 
-    def setup(self, step):
-        train_batch_size = self.hparams.train_batch_size
-        dataloader = self.get_dataloader("train", train_batch_size)
-        self.train_loader = dataloader
-        self.total_steps = (
-            (len(dataloader.dataset) // (train_batch_size * max(1, self.hparams.gpus)))
-            // self.hparams.accumulate_grad_batches
-            * float(self.hparams.max_epochs)
-        )
+    @property
+    def total_steps(self) -> int:
+        """The number of total training steps that will be run. Used for lr scheduler purposes."""
+        num_devices = max(1, self.hparams.gpus)  # TODO: consider num_tpu_cores
+        effective_batch_size = self.hparams.train_batch_size * self.hparams.accumulate_grad_batches * num_devices
+        dataset_size = len(self.train_loader.dataset)
+        return (dataset_size / effective_batch_size) * self.hparams.max_epochs
+
+    def setup(self, mode):
+        if mode == "fit":
+            self.train_loader = self.get_dataloader("train", self.hparams.train_batch_size, shuffle=True)
+
+    def get_dataloader(self, type_path, batch_size, shuffle=False):
+        raise NotImplementedError("You must implement this for your task")
 
     def train_dataloader(self):
         return self.train_loader
@@ -304,6 +309,13 @@ def add_generic_args(parser, root_dir) -> None:
         help="Number of updates steps to accumulate before performing a backward/update pass.",
     )
     parser.add_argument("--seed", type=int, default=42, help="random seed for initialization")
+    parser.add_argument(
+        "--data_dir",
+        default=None,
+        type=str,
+        required=True,
+        help="The input data dir. Should contain the training files for the CoNLL-2003 NER task.",
+    )
 
 
 def generic_train(