fix: total_steps 改用 ceiling 匹配实际步数

原公式全用 floor 少算 optimizer step，改用逐层 ceiling
（ceil_div via (a+b-1)//b）对齐 DDP sampler padding +
DataLoader drop_last=False 尾批 + batched 尾组截断。

scripts/tools/train.py

@@ -177,6 +177,22 @@ def create_scheduler(
     return SchedulerFactory.create(optimizer, **kwargs)
 
 
+def ceil_div(a: int, b: int) -> int:
+    return (a + b - 1) // b
+
+
+def compute_total_steps(
+    dataset_len: int,
+    n_epoch: int,
+    batch_size: int,
+    nprocs: int,
+    accumulation_steps: int,
+) -> int:
+    samples_per_replica = ceil_div(dataset_len, nprocs)
+    batches_per_replica = ceil_div(samples_per_replica, batch_size)
+    return ceil_div(batches_per_replica, accumulation_steps) * n_epoch
+
+
 def prepare_checkpoint(model: nn.Module) -> dict:
     return model.module.state_dict()
 
@@ -260,7 +276,9 @@ def train(
         },
     )
 
-    total_steps = len(dataset) * n_epoch // (batch_size * nprocs) // accumulation_steps
+    total_steps = compute_total_steps(
+        len(dataset), n_epoch, batch_size, nprocs, accumulation_steps
+    )
     scheduler_fn = partial(
         create_scheduler,
         **{