Fine tune “nmt_en_zh_transformer24x6” using a single GPU, dict has not been initialized
**Describe the bug**

`/NeMo/nemo/collections/nlp/models/machine_translation/mt_enc_dec_model.py in eval_epoch_end(self, outputs, mode)`
`356             # we also need to drop pairs where ground truth is an empty string`
`357             dist.all_gather_object(`
`--> 358                 tr_and_gt, [(t, g) for (t, g) in zip(translations, ground_truths) if g.strip() != '']`
`359             )`
`/lib/python3.7/site-packages/torch/distributed/distributed_c10d.py`
RuntimeError: Default process group has not been initialized, please make sure to call init_process_group.

**Steps/Code to reproduce bug**

`import os`
`from nemo.collections.nlp.models import MTEncDecModel`
`os.environ["CUDA_VISIBLE_DEVICES"] = "0"`
`model = MTEncDecModel.from_pretrained("nmt_en_zh_transformer24x6")`
`trainer = ptl.Trainer(gpus=1,
                      num_nodes=1,
                      max_epochs = EPOCHS,
                      accumulate_grad_batches=1,
                      checkpoint_callback=False,
                      logger=False,
                      log_every_n_steps=5,
                      check_val_every_n_epoch=10,
                      sync_batchnorm=False)`
`model.set_trainer(trainer)`
`trainer.fit(model)`

**Expected behavior**

I only have one machine with two GPUs. so I can't use the torch.distributed. What should I do to ignore this?

**Environment details**

If NVIDIA docker image is used you don't need to specify these.
Otherwise, please provide:
- OS version
- PyTorch version  1.10.0
- Python version 3.7
