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OneFlow is a deep learning framework designed to be user-friendly, scalable and efficient.

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#close https://github.com/Oneflow-Inc/oneflow/issues/9131

enhancement
feature
automerge
bug
eager
api

主要改动: 1、OneEmbedding要在eager下使用,需要对optimizer做如下操作 ```python opt = flow.one_embedding.Optimizer( opt, embeddings=[dlrm_module.embedding.one_embedding] ) ``` 在optimizer的step方法中,会执行参数更新,如果漏掉了以上操作,会报错 2、补充一些缺失的functor 3、修改update op/kernel,允许learning_rate 为optional,另传参数learning_rate_val,lazy下learning_rate为tensor,eager下learning_rate通过attr传递 4、在单卡时走unique_key_value->lookup->embedding_gather,重写了embedding_gather以支持动态内存分配 eager下不支持各个操作之间的overlap,在dlrm上训练可以达到目标精度

enhancement
op

feature
ci
need-all-tests-even-fail

针对full cache,对更新过的条目标记flag为True SaveSnapshot的时候,只保存这些更新过的条目

enhancement
system
embedding

需求来源: https://github.com/Oneflow-Inc/OneTeam/issues/1184#issuecomment-1232440993 ## Todo lists - [x] 实现 exponential_ 算子 - [x] functor 逻辑 - [x] cpu kernel - [x] cuda kernel - [x] 测试 - [x] 实现 multinomial 算子...

feature
op
api
python

module.to 和 pytorch 对齐

enhancement
python

来源:yolov5加载yolov5s.onnx做预测的时候。 pytorch脚本: ``` import torch as flow targets = flow.randn((0, 6), device="cuda") print(targets.shape) height, width = 640, 640 targets[:, 2:] *= flow.tensor((width, height, width, height), device="cuda") ``` 输出: ``` torch.Size([0,...

bug
community

## Summary eager global 下 detach 接口获得结果的 autograd 属性不符合预期,影响后续后向图构图。 ## Code to reproduce bug ```python cuda_placement = flow.placement("cuda", [0, 1]) cpu_placement = flow.placement("cpu", [0, 1]) B = flow.sbp.broadcast a =...

bug
community

## Summary I am wondering if oneflow support this kind of operations. For example, I have an input tensor of [1, 3, 200, 200] ( [batch_size, channel, width, height] )...

bug
community

## SpMM COO NOT ready for merging! Add the basic spmm_coo to perform SpMM operations needed by GCN. Only the CUDA kernel is offered. Code pieces are borrowed from prior...

bug
op