Add inline offline validation with train/eval split (#3824)

* refactor(training): rename eval_freq to env_eval_freq

- Rename eval_freq to env_eval_freq to distinguish sim environment evaluation from offline loss evaluation.

* feat(training): add inline offline validation with train/eval split

- Add eval_split config for balanced per-task holdout
- Add eval_steps for periodic inline eval loss computation
- Add max_eval_samples to cap eval cost

* fix(datasets): remap absolute indices in __getitem__ for filtered datasets

* fix(train): vectorize eval subset selection for max_eval_samples

* fix(datasets): Move the remapping into EpisodeAwareSampler via absolute_to_relative_idx

* fix(validation): add eval_split range check and eval_steps warning

Validate eval_split is in [0.0, 1.0) to prevent garbage splits from
out-of-range values. Raise when eval_steps > 0 but eval_split is 0.0
since no offline eval will run.

* fix(train): prepare eval dataloader with accelerator for multi-GPU

Prepare eval_dataloader through accelerator.prepare() so eval data is
sharded across ranks instead of duplicated. Reduce eval_loss across
ranks with mean reduction for consistent logging.

* fix(test): rename eval_freq to env_eval_freq for multi-GPU training

tests/training/test_multi_gpu.py

@@ -166,7 +166,7 @@ class TestMultiGPUTraining:
                 f"--output_dir={output_dir}",
                 "--batch_size=4",
                 "--steps=10",
-                "--eval_freq=-1",
+                "--env_eval_freq=-1",
                 "--log_freq=5",
                 "--save_freq=10",
                 "--seed=42",
@@ -209,7 +209,7 @@ class TestMultiGPUTraining:
                 f"--output_dir={output_dir}",
                 "--batch_size=4",
                 "--steps=20",
-                "--eval_freq=-1",
+                "--env_eval_freq=-1",
                 "--log_freq=5",
                 "--save_freq=10",
                 "--seed=42",
@@ -267,7 +267,7 @@ class TestMultiGPUTraining:
                 f"--output_dir={output_dir}",
                 "--batch_size=4",
                 "--steps=10",
-                "--eval_freq=-1",
+                "--env_eval_freq=-1",
                 "--log_freq=5",
                 "--save_freq=10",
                 "--seed=42",