.post1 version release for multipack fix

* don't sort multipack sampler

* increased packing efficiency increases loss

---------

Co-authored-by: Wing Lian <wing@axolotl.ai>

src/axolotl/__init__.py

@@ -4,4 +4,4 @@ import pkgutil
 
 __path__ = pkgutil.extend_path(__path__, __name__)  # Make this a namespace package
 
-__version__ = "0.9.1"
+__version__ = "0.9.1.post1"

src/axolotl/utils/samplers/multipack.py

@@ -78,15 +78,11 @@ def pack_group(
     Returns:
         List of bins, where each bin contains indices of sequences assigned to it
     """
-    # Get sorting indices and sort lengths in descending order
-    indices = np.argsort(sequence_lengths)[::-1]
-    sorted_lengths = sequence_lengths[indices]
-
     bins_remaining_space: list = []  # Tracks remaining capacity in each bin
     bins_assigned_sequences: list = []  # Tracks sequence indices assigned to each bin
 
-    for seq_id, size in enumerate(sorted_lengths):
-        global_idx = indices[seq_id] + group_offset
+    for seq_id, size in enumerate(sequence_lengths):
+        global_idx = seq_id + group_offset
 
         # Try to place sequence in existing bins
         add_new_bin = True

tests/e2e/integrations/test_kd.py

@@ -90,7 +90,7 @@ class TestKnowledgeDistillation:
         train(cfg=cfg, dataset_meta=dataset_meta)
         assert (Path(temp_dir) / "model.safetensors").exists()
         check_tensorboard(
-            temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high"
+            temp_dir + "/runs", "train/loss", 1.2, "Train Loss (%s) is too high"
         )
 
     @pytest.mark.parametrize(
@@ -121,5 +121,5 @@ class TestKnowledgeDistillation:
         train(cfg=cfg, dataset_meta=dataset_meta)
         assert (Path(temp_dir) / "adapter_model.safetensors").exists()
         check_tensorboard(
-            temp_dir + "/runs", "train/loss", 1.0, "Train Loss is too high"
+            temp_dir + "/runs", "train/loss", 1.2, "Train Loss (%s) is too high"
         )

tests/test_packed_batch_sampler.py

@@ -106,3 +106,4 @@ class TestBatchedSamplerPacking:
 
         original_idxs = set(range(len(train_dataset)))
         assert original_idxs == set(batch_idxs)
+        assert len(batch_idxs) == len(set(batch_idxs))