propagate config

Signed-off-by: eharper <[email protected]>

examples/nlp/language_modeling/tuning/megatron_gpt_peft_tuning.py

@@ -105,6 +105,9 @@ def _modify_config(gpt_cfg, cfg, add_cfg_to_tree=False):
         gpt_cfg.peft = cfg.model.peft
         peft_cls = _get_peft_scheme(cfg.model)
         gpt_cfg.target = f"{peft_cls.__module__}.{peft_cls.__name__}"
+        gpt_cfg.tensor_model_parallel_size = cfg.model.get('tensor_model_parallel_size', 1)
+        gpt_cfg.pipeline_model_parallel_size = cfg.model.get('pipeline_model_parallel_size', 1)
+        gpt_cfg.pipeline_model_parallel_split_rank = cfg.model.get('pipeline_model_parallel_split_rank', 0)
 
         # This is needed when modifying a hparam file directly to load `.ckpt` files.
         # This is not needed to modify the cfg in `.nemo` files.