diff --git a/pytorch_lightning/models/trainer.py b/pytorch_lightning/models/trainer.py
index a1d63d2c6b..1bdd165496 100644
--- a/pytorch_lightning/models/trainer.py
+++ b/pytorch_lightning/models/trainer.py
@@ -374,9 +374,23 @@ class Trainer(TrainerIO):
         if self.use_ddp:
             # must copy only the meta of the exp so it survives pickle/unpickle when going to new process
             self.experiment = self.experiment.get_meta_copy()
-            task = int(os.environ['SLURM_LOCALID'])
-            self.ddp_train(task, model)
-            # mp.spawn(self.ddp_train, nprocs=len(self.data_parallel_device_ids), args=(model, ))
+
+            # whenever we have the correct number of tasks, we let slurm manage processes
+            # otherwise we launch the required number of processes
+            nb_slurm_tasks = int(os.environ['SLURM_NTASKS'])
+            nb_requested_gpus = len(self.data_parallel_device_ids)
+            is_slurm_managing_tasks = nb_slurm_tasks == nb_requested_gpus
+            if is_slurm_managing_tasks:
+                task = int(os.environ['SLURM_LOCALID'])
+                self.ddp_train(task, model)
+            else:
+                msg = f"""
+                You requested {nb_requested_gpus} GPUs but launched {nb_slurm_tasks} slurm tasks. 
+                We will launch {nb_requested_gpus} processes for you. 
+                We recommend you let slurm manage the processes by setting: --ntasks-per-node={nb_requested_gpus}
+                """
+                warnings.warn(msg)
+                mp.spawn(self.ddp_train, nprocs=len(self.data_parallel_device_ids), args=(model, ))
 
         # 1 gpu or dp option triggers training using DP module
         # easier to avoid NCCL issues