In copy_weights_to_flat_buf_views() explicitly construct tuple #43244
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In some versions of GCC, tuple constructor from initializer list is marked as explicit, which results in the following compilation error:
```
/var/lib/jenkins/workspace/aten/src/ATen/native/cudnn/RNN.cpp: In function 'std::tuple<at::Tensor, std::vector<at::Tensor, std::allocator<at::Tensor> > > at::native::cudnn_rnn::copy_weights_to_flat_buf_views(at::TensorList, int64_t, int64_t, int64_t, int64_t, int64_t, bool, bool, cudnnDataType_t, const c10::TensorOptions&, bool, bool, bool)':
/var/lib/jenkins/workspace/aten/src/ATen/native/cudnn/RNN.cpp:687:35: error: converting to 'std::tuple<at::Tensor, std::vector<at::Tensor, std::allocator<at::Tensor> > >' from initializer list would use explicit constructor 'constexpr std::tuple<_T1, _T2>::tuple(_U1&&, _U2&&) [with _U1 = at::Tensor&; _U2 = std::vector<at::Tensor>&; <template-parameter-2-3> = void; _T1 = at::Tensor; _T2 = std::vector<at::Tensor>]'
return {weight_buf, params_arr};
```
This regression was introduced by pytorch#42385
malfet
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pbelevich
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Aug 19, 2020
💊 CI failures summary and remediationsAs of commit 2c7097e (more details on the Dr. CI page):
🚧 1 ongoing upstream failure:These were probably caused by upstream breakages that are not fixed yet:
ci.pytorch.org: 1 failedThis comment was automatically generated by Dr. CI (expand for details).Follow this link to opt-out of these comments for your Pull Requests.Please report bugs/suggestions on the GitHub issue tracker or post in the (internal) Dr. CI Users group. This comment has been revised 2 times. |
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In some versions of GCC, tuple constructor from initializer list is marked as explicit, which results in the following compilation error:
This regression was introduced by #42385