Mar 30, 2021 · Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance.
how to set find_unused_parameters=True? ... find_unused_parameters was changed as it is the recommended default by PyTorch as it can incur a large performance hit.
01.01.2020 · PyTorch's DistributedDataParallel has this optional flag that can be set called find_unused_parameters. It is intended to let torch's autograd to ignore parameters that aren't part of the computational graph of the current forward pass. ...
Jan 01, 2020 · PyTorch's DistributedDataParallel has this optional flag that can be set called find_unused_parameters. It is intended to let torch's autograd to ignore parameters that aren't part of the computational graph of the current forward pass.
Dec 13, 2019 · Process got stuck when set find_unused_parameters=True in DDP. e0357894 (Zhou Daquan) June 6, 2020, 1:28am #2. Hi, I have the same issues and I need to find those ...
30.03.2021 · Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance.
how to set find_unused_parameters=True? 🐛 Bug RuntimeError: Expected to have finished reduction in the prior iteration before starting a new one. ... find_unused_parameters was changed as it is the recommended default by PyTorch as it can incur a large performance hit.
Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of ...
13.12.2019 · Process got stuck when set find_unused_parameters=True in DDP. e0357894 (Zhou Daquan) June 6, 2020, 1:28am #2. Hi, I have the same issues and I need to find those unused parameters also. Please let me know if you have got any solutions. Thanks. 1 …
Aug 31, 2021 · [W reducer.cpp:1050] Warning: find_unused_parameters=True was specified in DDP constructor, but did not find any unused parameters. This flag results in an extra traversal of the autograd graph every iteration, which can adversely affect performance. If your model indeed never has any unused parameters, consider turning this flag off.
Any outputs derived from module parameters that are otherwise unused can be ... be on " "the same type of devices, but input module parameters locate in {}.