Add a parallel_mode property to TrainingArguments (#8877)

* Add a `distributed_env` property to TrainingArguments

* Change name

* Address comment

src/transformers/training_args.py

@@ -465,6 +465,27 @@ class TrainingArguments:
         """
         return self._setup_devices[1]
 
+    @property
+    @torch_required
+    def parallel_mode(self):
+        """
+        The current mode used for parallelism if multiple GPUs/TPU cores are available. One of:
+
+        - :obj:`ParallelMode.NOT_PARALLEL`: no parallelism (CPU or one GPU).
+        - :obj:`ParallelMode.NOT_DISTRIBUTED`: several GPUs in one single process (uses :obj:`torch.nn.DataParallel`).
+        - :obj:`ParallelMode.DISTRIBUTED`: several GPUs, each ahving its own process (uses
+          :obj:`torch.nn.DistributedDataParallel`).
+        - :obj:`ParallelMode.TPU`: several TPU cores.
+        """
+        if is_torch_tpu_available():
+            return ParallelMode.TPU
+        elif self.local_rank != -1:
+            return ParallelMode.DISTRIBUTED
+        elif self.n_gpu > 1:
+            return ParallelMode.NOT_DISTRIBUTED
+        else:
+            return ParallelMode.NOT_PARALLEL
+
     def to_dict(self):
         """
         Serializes this instance while replace `Enum` by their values (for JSON serialization support).
@@ -493,3 +514,10 @@ class TrainingArguments:
             valid_types.append(torch.Tensor)
 
         return {k: v if type(v) in valid_types else str(v) for k, v in d.items()}
+
+
+class ParallelMode(Enum):
+    NOT_PARALLEL = "not_parallel"
+    NOT_DISTRIBUTED = "not_distributed"
+    DISTRIBUTED = "distributed"
+    TPU = "tpu"