don't use is_main_process during config validation (#2569)

.github/workflows/multi-gpu-e2e.yml

@@ -8,6 +8,7 @@ on:
       - 'setup.py'
       - 'pyproject.toml'
       - '.github/workflows/multi-gpu-e2e.yml'
+      - 'src/axolotl/core/trainers/mixins/sequence_parallel.py'
   workflow_dispatch:
   schedule:
     - cron: '0 0 * * 1,4'  # Runs at 00:00 UTC every monday & thursday

src/axolotl/utils/schemas/config.py

@@ -18,7 +18,6 @@ from pydantic import (
 )
 from transformers.utils.import_utils import is_torch_npu_available
 
-from axolotl.utils.distributed import is_main_process
 from axolotl.utils.schemas.datasets import (
     DatasetConfig,
     DPODataset,
@@ -719,10 +718,9 @@ class AxolotlInputConfig(
             and data.get("eval_sample_packing") is None
             and not data.get("eval_table_size")
         ):
-            if is_main_process():
-                LOG.info(
-                    "explicitly setting `eval_sample_packing` to match `sample_packing`"
-                )
+            LOG.info(
+                "explicitly setting `eval_sample_packing` to match `sample_packing`"
+            )
             data["eval_sample_packing"] = True
 
         if (
@@ -1179,15 +1177,14 @@ class AxolotlInputConfig(
             # TODO: monkeypatch / callback to average losses correctly across SP ranks
             # / fix gradient scaling across SP ranks. Losses, grads should be scaled
             # according to the proportion of non-padding tokens per rank.
-            if is_main_process():
-                LOG.warning(
-                    "Sequence parallelism (SP) is enabled with "
-                    f"sequence_parallel_degree={self.sequence_parallel_degree}. "
-                    "Please note that logged losses may differ slightly to the non-SP "
-                    "losses due to transformers Trainer implementation details. "
-                    "Please see https://github.com/axolotl-ai-cloud/axolotl/pull/2495#issuecomment-2784022042 "
-                    "for more details."
-                )
+            LOG.warning(
+                "Sequence parallelism (SP) is enabled with "
+                f"sequence_parallel_degree={self.sequence_parallel_degree}. "
+                "Please note that logged losses may differ slightly to the non-SP "
+                "losses due to transformers Trainer implementation details. "
+                "Please see https://github.com/axolotl-ai-cloud/axolotl/pull/2495#issuecomment-2784022042 "
+                "for more details."
+            )
 
         return self
 

src/axolotl/utils/trainer.py

@@ -528,6 +528,13 @@ def setup_torch_compile_env(cfg):
 def setup_deepspeed_env(cfg, stage=None):
     from transformers.integrations.deepspeed import HfTrainerDeepSpeedConfig
 
+    from axolotl.utils.distributed import distributed_state
+
+    if distributed_state and distributed_state.initialized:
+        raise RuntimeError(
+            "Distributed State already initialized before Deepspeed setup"
+        )
+
     os.environ["ACCELERATE_USE_DEEPSPEED"] = "true"
     os.environ["ACCELERATE_DEEPSPEED_CONFIG_FILE"] = cfg.deepspeed
     if stage:

tests/e2e/patched/test_sp.py

@@ -131,11 +131,6 @@ class TestConfigValidation:
         # Mock the ring_flash_attn module
         monkeypatch.setitem(sys.modules, "ring_flash_attn", MagicMock())
 
-        # Mock the is_main_process function to return True
-        monkeypatch.setattr(
-            "axolotl.utils.schemas.config.is_main_process", lambda: True
-        )
-
     @pytest.fixture
     def base_cfg(self):
         """Create a base configuration for testing."""