Type the data/model/training batch contracts with NamedTuples (issues.md Issue 7)

build_features (transforms.py) now returns StepFeatures and
StreamingStepsDataset (dataset.py) now yields StepBatch, both NamedTuples
with the same field order as the tuples they replace, so ty can catch a
dropped/added field at every consuming call site instead of a silent
positional-tuple mismatch. Converted the unreadable throwaway-heavy unpacks
in cli.py, pipeline.py, validate.py, and dataset.py to named attribute
access; gave the WGAN path's derived 5-element batch its own
_Stage2RealFakeBatch NamedTuple; updated the two test batch-construction
helpers to build real StepBatchs.

Co-Authored-By: Claude Sonnet 5 <noreply@anthropic.com>

tests/test_train.py

@@ -17,6 +17,7 @@ from giant.constants import (
     SEC_SLOT_DIM,
     X_DIM,
 )
+from giant.data.dataset import StepBatch
 from giant.model.network import build_critics, build_models
 from giant.training import (
     FlowDDPMStageTrainer,
@@ -316,7 +317,7 @@ def _fake_batches(n_batches, batch_size, seed=0):
         sec_cont = torch.randn(batch_size, K_MAX, SEC_SLOT_DIM, generator=g)
         proc_idx = torch.zeros(batch_size, dtype=torch.long)
         sec_type_idx = torch.zeros(batch_size, K_MAX, dtype=torch.long)
-        batches.append((cond_cont, cond_cat, x1, n_sec, sec_cont, proc_idx, sec_type_idx))
+        batches.append(StepBatch(cond_cont, cond_cat, x1, n_sec, sec_cont, proc_idx, sec_type_idx))
     return batches