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OneFlow 算子对齐 PyTorch 完备计划推进表 #4936
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为什么einsum 这个没有在列表里 |
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背景
本 issue 主贴(此贴)记录分工和对应的 PR,方便跟进。
解决的时间节点
Hard难度的应该在0.7.0版本之前解决,Medium应该在0.6.0版本之前完全解决,Easy难度的应该在分配当周或者下周进行解决。
相关文档
负责人
@BBuf
任务分工表
flow.sum()仅支持dim指定维度,而torch支持dim或axis。来源:迟子秋。https://github.com/Oneflow-Inc/OneTeam/issues/1184#issuecomment-1089842163oneflow._oneflow_internal.Tensor 类型不可以自动转化为Numpy类型 来源:陈巧玲 OCR https://github.com/Oneflow-Inc/OneCloud/issues/69#issuecomment-1074628723Dataloader pin_memory没有对齐的问题。需要露阳解决。优先级低。相关issue:https://github.com/Oneflow-Inc/OneTeam/issues/1180 。将argsort的Python层逻辑迁移到Functor。来源性能需求。认领人:王世杰。 Medium。将argwhere的Python层逻辑迁移到Functor。来源性能需求。认领人:王世杰。 Medium。将to_local_op的Python层逻辑迁移到Functor。来源性能需求。Easy。将empty的Python层逻辑迁移到Functor。来源性能需求。 Medium。flow.cuda.empty_cache 接口没对齐。来源:林松。https://github.com/Oneflow-Inc/OneCloud/issues/87#issuecomment-1102115749 。来自丰伟:allocator需要通过vm从stream中获取。当前支持的条件不成熟,且功能较为薄弱。我们是从该axis到最后,做norm。对应的解决方案可以是前后加2个transpose。#787 。认领人:刘沛宏。 Medium。
tensor.median()
方法,来源:任天和。期望libai mae支持graph格式数据并行,流水线并行和模型并行 libai#259 。认领人:王世杰。dev_median #8069torch.cuda.synchronize
以及torch.cuda.max_memory_alocated
接口。来源: 任天和。期望libai mae支持graph格式数据并行,流水线并行和模型并行 libai#259torch.nn.parallel.DistributedDataParallel()
的入参没有对齐。来源:任天和。期望libai mae支持graph格式数据并行,流水线并行和模型并行 libai#259oneflow.nn.utils.clip_grad_norm_
不支持传入None,来源:任天和。期望libai mae支持graph格式数据并行,流水线并行和模型并行 libai#259#6156
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