minor changes from github issues

megatron/data/dataset_utils.py

@@ -674,7 +674,7 @@ def get_samples_mapping(indexed_dataset,
         # Build samples mapping
         verbose = torch.distributed.get_rank() == 0
         start_time = time.time()
-        print_rank_0(' > building sapmles index mapping for {} ...'.format(
+        print_rank_0(' > building samples index mapping for {} ...'.format(
             name))
         # First compile and then import.
         from megatron.data import helpers
@@ -688,7 +688,7 @@ def get_samples_mapping(indexed_dataset,
             seed,
             verbose,
             2 if binary_head else 1)
-        print_rank_0(' > done building sapmles index maping')
+        print_rank_0(' > done building samples index maping')
         np.save(indexmap_filename, samples_mapping, allow_pickle=True)
         print_rank_0(' > saved the index mapping in {}'.format(
             indexmap_filename))

megatron/training.py

@@ -541,7 +541,7 @@ def training_log(loss_dict, total_loss_dict, learning_rate, iteration,
     if iteration % args.log_interval == 0:
         elapsed_time = timers('interval-time').elapsed()
         elapsed_time_per_iteration = elapsed_time / total_iterations
-        if writer and torch.distributed.get_rank() == 0:
+        if writer:
             if args.log_timers_to_tensorboard:
                 writer.add_scalar('iteration-time',
                                   elapsed_time_per_iteration, iteration)
@@ -748,7 +748,7 @@ def evaluate_and_print_results(prefix, forward_step_func,
         string += '{} value: {:.6E} | '.format(key, total_loss_dict[key].item())
         ppl = math.exp(min(20, total_loss_dict[key].item()))
         string += '{} PPL: {:.6E} | '.format(key, ppl)
-        if writer and is_last_rank():
+        if writer:
             writer.add_scalar('{} validation'.format(key),
                               total_loss_dict[key].item(),
                               iteration)