Adds train_batch_size, eval_batch_size, and n_gpu to to_sanitized_dict output for logging. (#5331)

* Adds train_batch_size, eval_batch_size, and n_gpu to to_sanitized_dict() output

* Update wandb config logging to use to_sanitized_dict

* removed n_gpu from sanitized dict

* fix quality check errors

src/transformers/trainer.py

@@ -383,7 +383,7 @@ class Trainer:
             logger.info(
                 'Automatic Weights & Biases logging enabled, to disable set os.environ["WANDB_DISABLED"] = "true"'
             )
-            wandb.init(project=os.getenv("WANDB_PROJECT", "huggingface"), config=vars(self.args))
+            wandb.init(project=os.getenv("WANDB_PROJECT", "huggingface"), config=self.args.to_sanitized_dict())
             # keep track of model topology and gradients, unsupported on TPU
             if not is_torch_tpu_available() and os.getenv("WANDB_WATCH") != "false":
                 wandb.watch(

src/transformers/training_args.py

@@ -310,7 +310,10 @@ class TrainingArguments:
         Sanitized serialization to use with TensorBoard’s hparams
         """
         d = dataclasses.asdict(self)
+        d = {**d, **{"train_batch_size": self.train_batch_size, "eval_batch_size": self.eval_batch_size}}
+
         valid_types = [bool, int, float, str]
         if is_torch_available():
             valid_types.append(torch.Tensor)
+
         return {k: v if type(v) in valid_types else str(v) for k, v in d.items()}