fix: correct total_num_steps and batch_size calculation with context parallelism (#3444)

* fix: correct total_num_steps and batch_size calculation with context parallelism

* feat: add test for CP batch size

---------

Co-authored-by: NanoCode012 <nano@axolotl.ai>

src/axolotl/utils/config/__init__.py

@@ -119,7 +119,8 @@ def normalize_config(cfg):
     if cfg.world_size != 1:
         cfg.device_map = {"": int(os.environ.get("LOCAL_RANK", 0))}
         if cfg.fsdp or cfg.fsdp_config or cfg.ddp:
-            cfg.batch_size = cfg.batch_size * cfg.world_size
+            effective_world_size = cfg.world_size // (cfg.context_parallel_size or 1)
+            cfg.batch_size = cfg.batch_size * effective_world_size
 
     if not cfg.use_ray:
         # delay resolving dtype until on worker node when launching with ray

src/axolotl/utils/trainer.py

@@ -457,7 +457,6 @@ def calculate_total_num_steps(cfg, train_dataset, update=True):
                     - 1
                 )
                 * cfg.num_epochs
-                * cfg.context_parallel_size
                 * cfg.tensor_parallel_size
             )
             LOG.debug(
@@ -498,12 +497,7 @@ def calculate_total_num_steps(cfg, train_dataset, update=True):
             # FIXME: is there a bug here somewhere? the total num steps depends
             # on the agreed on value for sample_packing_eff_est
             total_num_steps = int(
-                math.floor(
-                    data_loader_len
-                    * cfg.num_epochs
-                    * cfg.context_parallel_size
-                    * cfg.tensor_parallel_size
-                )
+                math.floor(data_loader_len * cfg.num_epochs * cfg.tensor_parallel_size)
             )
             if cfg.dataloader_drop_last:
                 # drop the last batch for each epoch
@@ -528,7 +522,6 @@ def calculate_total_num_steps(cfg, train_dataset, update=True):
             math.ceil(
                 len(train_dataset)
                 * cfg.num_epochs
-                * cfg.context_parallel_size
                 * cfg.tensor_parallel_size
                 / cfg.batch_size
             )

tests/test_context_parallel_batch_size.py

@@ -0,0 +1,56 @@
+"""Tests for batch_size calculation with context parallelism."""
+
+import sys
+import types
+
+import pytest
+
+from axolotl.utils.config import normalize_config, validate_config
+from axolotl.utils.dict import DictDefault
+
+
+@pytest.fixture(name="cp_base_cfg")
+def fixture_cp_base_cfg(min_base_cfg):
+    return (
+        DictDefault(
+            micro_batch_size=2,
+            gradient_accumulation_steps=4,
+            sequence_len=2048,
+            num_epochs=1,
+            flash_attention=True,
+        )
+        | min_base_cfg
+    )
+
+
+class TestContextParallelBatchSize:
+    """Verify batch_size scales by effective dp world_size when using context parallelism."""
+
+    @pytest.mark.parametrize(
+        "world_size, context_parallel_size, expected_batch_size",
+        [
+            (4, 1, 32),  # no CP: 2*4*4 = 32
+            (4, 2, 16),  # CP=2: 2*4*(4//2) = 16
+            (4, 4, 8),  # CP=4: 2*4*(4//4) = 8
+            (2, 2, 8),  # CP=ws: 2*4*(2//2) = 8 (no scaling)
+        ],
+    )
+    def test_batch_size_with_context_parallelism(
+        self,
+        cp_base_cfg,
+        monkeypatch,
+        world_size,
+        context_parallel_size,
+        expected_batch_size,
+    ):
+        monkeypatch.setenv("WORLD_SIZE", str(world_size))
+        # Mock ring_flash_attn since it's not installable on CPU,
+        # but required by schema validation when context_parallel_size > 1.
+        if "ring_flash_attn" not in sys.modules:
+            monkeypatch.setitem(
+                sys.modules, "ring_flash_attn", types.ModuleType("ring_flash_attn")
+            )
+        cp_base_cfg["context_parallel_size"] = context_parallel_size
+        cfg = validate_config(cp_base_cfg)
+        normalize_config(cfg)
+        assert cfg.batch_size == expected_batch_size