Merge branch 'main' of github.com-mvpatel2000:mosaicml/composer

composer/utils/checkpoint.py

@@ -148,10 +148,25 @@ def _get_write_mode(name: str) -> str:
     raise ValueError(f'{name} does not end with a valid tarfile extension.')
 
 
+def _is_rng_key(key: str, value: tuple) -> bool:
+    """Check if the key is an RNG key.
+
+    We expect the RNG key to be of the form 'rng.{rank}.cuda|torch|python|numpy'.
+    This function ensures that we don't accidentally pick up other keys.
+    """
+    starts_with_rng = key.startswith('rng')
+    ends_with_expected = key.endswith(('cuda', 'torch', 'python', 'numpy'))
+    three_parts = isinstance(value, tuple) and len(value) == 3
+    if starts_with_rng and ends_with_expected and three_parts:
+        return True
+
+    return False
+
+
 def _get_num_ranks_that_saved_rng(metadata: Metadata):
     rng_inds = []
     for field_name, field_value in metadata.planner_data.items():
-        if 'rng' in field_name:
+        if _is_rng_key(field_name, field_value):
             _, rng_rank_index, _ = field_value
             rng_inds.append(rng_rank_index)
     rng_inds = set(rng_inds)

tests/loggers/test_wandb_logger.py

@@ -269,10 +269,10 @@ def test_wandb_log_metrics(test_wandb_logger):
     eval_metrics_cross_entropy_count = all_run_text.count('metrics/eval/CrossEntropy')
     train_loss_count = all_run_text.count('loss/train/total')
 
-    expected_number_train_loss_count = (dataset_size / batch_size) + 1  # wandb includes it in the file one extra time
+    expected_number_train_loss_count = (dataset_size / batch_size) * 2  # wandb includes it twice per step
     expected_number_train_metrics_count = (
         dataset_size / batch_size
-    ) + 2  # wandb includes it in the file two extra times
+    ) * 2 + 2  # wandb includes it twice per step plus two extra times
     expected_number_eval_metrics_count = 2  # wandb includes it in the file twice
     assert train_metrics_accuracy_count == expected_number_train_metrics_count
     assert train_loss_count == expected_number_train_loss_count

tests/trainer/test_checkpoint.py

@@ -35,6 +35,7 @@
     _COMPOSER_STATES_FILENAME,
     PartialFilePath,
     _ensure_valid_checkpoint,
+    _is_rng_key,
     _write_checkpoint_file,
     glob_filter,
 )
@@ -130,6 +131,23 @@ def _assert_checkpoints_equivalent(file1, file2, atol=0.0, rtol=0.0):
     assert all(keys_in) or not any(keys_in)
 
 
+@pytest.mark.parametrize(
+    'key,value,expected_result',
+    [
+        ('rng.0.cuda', ('rng', '0', 'cuda'), True),
+        ('rng.0.torch', ('rng', '0', 'torch'), True),
+        ('rng.0.numpy', ('rng', '0', 'numpy'), True),
+        ('rng.0.python', ('rng', '0', 'python'), True),
+        ('rng.0', ('rng', '0'), False),
+        ('test.test.rng', ('test', 'test', 'rng'), False),
+        ('test.rng.test', ('test', 'rng', 'test'), False),
+        ('test.notatuple.test', 0, False),
+    ],
+)
+def test_is_rng_key(key: str, value: tuple, expected_result: bool):
+    assert _is_rng_key(key, value) == expected_result
+
+
 @pytest.mark.parametrize(
     'remove_field_paths,filter_params',
     [