fix(dataloader): track distributed progress by global batch - #204
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| size_t batch_size_ = 0; | ||
| size_t batch_idx_ = 0; | ||
| size_t max_batch_idx_ = 0; | ||
| size_t global_batch_idx_ = 0; |
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这里变量不是直接表示batch维度的，为了防止理解混淆，建议改个名字，比如 dataloader_step_ ，另外其他变量也统一改下命名
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改动：
global_batch_idx_ -> dataloader_step_
num_global_batches_ -> num_dataloader_steps_
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| DataLoader::DataLoader(const std::shared_ptr<Dataset> &dataset, size_t batch_size) | ||
| : dataset_(dataset), batch_size_(batch_size), max_batch_idx_((dataset_->Size() + batch_size_ - 1) / batch_size_) {} | ||
| : dataset_(dataset), batch_size_(batch_size), num_global_batches_(CheckedCeilDiv(dataset_->Size(), batch_size_)) {} |
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建议先校验 dataset_ != nullptr 和 batch_size_ > 0，再计算 num_global_batches_。当前在初始化列表中直接访问 dataset_->Size()，空指针会导致非法解引用，batch_size_ == 0 也会引发除零。
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新增
CHECK(dataset_ != nullptr) 和 CHECK_GT(batch_size_, 0)
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- rename global batch tracking to dataloader steps - validate dataset and batch size before computing steps
kilinchange
requested changes
Aug 27, 2026
- resume training by skipping consumed batches in main - keep resume positioning as a future sampler responsibility - preserve distributed global-batch partitioning
kilinchange
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Sep 10, 2026
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麻烦贴一下测试通过截图，并备份 log 和写入飞书性能表格。 |
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单元测试： 精度测试： 性能测试： |
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概述
修复分布式训练中 DataLoader 使用局部 batch 进行数据划分和索引，可能导致 batch 访问越界的问题。
主要修改