Skip redundant evaluation when resuming from checkpoint (#3575) [skip ci]

* Skip redundant evaluation when resuming from checkpoint

* add condition check for adding callback

---------

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

tests/utils/callbacks/test_skip_eval_on_resume.py

@@ -0,0 +1,63 @@
+"""Tests for SkipEvalOnResumeCallback."""
+
+from unittest.mock import MagicMock
+
+from transformers import TrainerControl, TrainerState, TrainingArguments
+
+from axolotl.utils.callbacks import SkipEvalOnResumeCallback
+
+
+class TestSkipEvalOnResumeCallback:
+    """Tests for skipping redundant evaluation on checkpoint resume."""
+
+    @staticmethod
+    def _make_state(global_step: int) -> TrainerState:
+        state = MagicMock(spec=TrainerState)
+        state.global_step = global_step
+        return state
+
+    def test_suppresses_eval_at_resume_step(self):
+        cb = SkipEvalOnResumeCallback()
+        args = MagicMock(spec=TrainingArguments)
+        state = self._make_state(20)
+        control = TrainerControl(should_evaluate=False)
+
+        # Simulate on_train_begin at checkpoint-20
+        cb.on_train_begin(args, state, control)
+
+        # Trainer sets should_evaluate = True for step 20
+        control.should_evaluate = True
+        result = cb.on_step_end(args, state, control)
+
+        assert result.should_evaluate is False
+
+    def test_allows_eval_after_resume_step(self):
+        cb = SkipEvalOnResumeCallback()
+        args = MagicMock(spec=TrainingArguments)
+        state = self._make_state(20)
+        control = TrainerControl(should_evaluate=False)
+
+        cb.on_train_begin(args, state, control)
+
+        # Advance past the resume point
+        state.global_step = 30
+        control.should_evaluate = True
+        result = cb.on_step_end(args, state, control)
+
+        assert result.should_evaluate is True
+
+    def test_noop_on_fresh_run(self):
+        cb = SkipEvalOnResumeCallback()
+        args = MagicMock(spec=TrainingArguments)
+        state = self._make_state(0)
+        control = TrainerControl(should_evaluate=False)
+
+        # Fresh run: global_step starts at 0
+        cb.on_train_begin(args, state, control)
+
+        # Even if eval triggers at step 0 (unlikely but defensive)
+        state.global_step = 10
+        control.should_evaluate = True
+        result = cb.on_step_end(args, state, control)
+
+        assert result.should_evaluate is True