addressed Jareds comments

megatron/arguments.py

@@ -136,14 +136,16 @@ def parse_args(extra_args_provider=None, defaults={},
 def _print_args(args):
     """Print arguments."""
     if args.rank == 0:
-        print('-------------------- arguments --------------------', flush=True)
+        print('------------------------ arguments ------------------------',
+              flush=True)
         str_list = []
         for arg in vars(args):
-            dots = '.' * (32 - len(arg))
+            dots = '.' * (48 - len(arg))
             str_list.append('  {} {} {}'.format(arg, dots, getattr(args, arg)))
         for arg in sorted(str_list, key=lambda x: x.lower()):
             print(arg, flush=True)
-        print('---------------- end of arguments ----------------', flush=True)
+        print('-------------------- end of arguments ---------------------',
+              flush=True)
 
 
 def _check_arg_is_not_none(args, arg):
@@ -401,7 +403,10 @@ def _add_data_args(parser):
     group = parser.add_argument_group(title='data and dataloader')
 
     group.add_argument('--data-path', nargs='*', default=None,
-                       help='Path to combined dataset to split.')
+                       help='Path to the training dataset. Accepted format:'
+                       '1) a single data path, 2) multiple datasets in the'
+                       'form: dataset1-weight dataset1-path dataset2-weight '
+                       'dataset2-path ...')
     group.add_argument('--split', type=str, default='969, 30, 1',
                        help='Comma-separated list of proportions for training,'
                        ' validation, and test split. For example the split '

megatron/data/helpers.cpp

@@ -60,7 +60,7 @@ void build_blending_indices(py::array_t<uint8_t>& dataset_index,
   for(int64_t sample_idx = 0; sample_idx < size; ++sample_idx) {
 
     // Determine where the max error in sampling is happening.
-    double sample_idx_double = std::max(static_cast<double>(sample_idx), 1.0);
+    auto sample_idx_double = std::max(static_cast<double>(sample_idx), 1.0);
     int64_t max_error_index = 0;
     double max_error = weights_ptr[0] * sample_idx_double -
       static_cast<double>(current_samples[0]);
@@ -86,7 +86,7 @@ void build_blending_indices(py::array_t<uint8_t>& dataset_index,
   if (verbose) {
     std::cout << " > sample ratios:" << std::endl;
     for (int64_t dataset_idx = 0; dataset_idx < num_datasets; ++dataset_idx) {
-      double ratio = static_cast<double>(current_samples[dataset_idx]) /
+      auto ratio = static_cast<double>(current_samples[dataset_idx]) /
 	static_cast<double>(size);
       std::cout << "   dataset " << dataset_idx << ", input: " <<
 	weights_ptr[dataset_idx] << ", achieved: " << ratio << std::endl;