Only accept continguous tensors in TopK for cuda #9441
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t-vi
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apaszke,
colesbury,
ezyang,
gchanan,
soumith and
zdevito
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you should make the input tensor contiguous with newContiguous, rather than assert that the Tensor is contiguous |
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Ok, thanks. I'm never sure whether we do that or leave it to the user... |
Thank you, Soumith, for the review comment. Also add a test.
ezyang
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Jul 14, 2018
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zdevito
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Summary: Fixes: #9421 I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check. The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...) Do we need a test that it indeed refuses non-contiguous? Pull Request resolved: pytorch/pytorch#9441 Reviewed By: soumith Differential Revision: D8850719 Pulled By: ezyang fbshipit-source-id: d50561bb37ed50ab97aeaf54d8e3fc6c765bdc7c
zdevito
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Jul 15, 2018
Summary: Fixes: #9421 I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check. The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...) Do we need a test that it indeed refuses non-contiguous? Pull Request resolved: pytorch/pytorch#9441 Reviewed By: soumith Differential Revision: D8850719 Pulled By: ezyang fbshipit-source-id: d50561bb37ed50ab97aeaf54d8e3fc6c765bdc7c
petrex
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Jul 16, 2018
* upstream/master: (24 commits) Implement tensor weak references (pytorch#9363) Nuke TestCollectEnv (pytorch#9459) Add test case for segmentation fault fix in grad_fn (pytorch#9457) Add peephole optimization for type_as operators. (pytorch#9316) Fix out-of-range error for test_neg (pytorch#9431) add depthwise conv support for mkldnn (pytorch#8782) Refactor `_log_sum_exp` (pytorch#9173) Add ModuleDict and ParameterDict containers (pytorch#8463) Introduce SupervisedPtr, delete THAllocator and THCDeviceAllocator (pytorch#9358) Introducing IsInf (pytorch#9169) add device to CUDAEvent (pytorch#9415) Make localScalar error message more intuitive (pytorch#9443) Only accept continguous tensors in TopK for cuda (pytorch#9441) Add support for .norm() pytorch onnx export and ReduceL1/ReduceL2 caffe2 operators (pytorch#9299) Only view() rhs of index_put if we need to (pytorch#9424) Add BatchBucketizeOp in caffe2 (pytorch#9385) Implementation of Wngrad optimizer caffe2 python wrapper and unit test on least square regression (pytorch#9001) Implementation and operator test for Wngrad optimizer (pytorch#8999) Fix segmentation fault in grad_fn (pytorch#9292) update docs (pytorch#9423) ...
goldsborough
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Jul 20, 2018
Summary: Fixes: pytorch#9421 I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check. The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...) Do we need a test that it indeed refuses non-contiguous? Pull Request resolved: pytorch#9441 Reviewed By: soumith Differential Revision: D8850719 Pulled By: ezyang fbshipit-source-id: d50561bb37ed50ab97aeaf54d8e3fc6c765bdc7c
jramseyer
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Jul 30, 2018
Summary: Fixes: pytorch#9421 I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check. The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...) Do we need a test that it indeed refuses non-contiguous? Pull Request resolved: pytorch#9441 Reviewed By: soumith Differential Revision: D8850719 Pulled By: ezyang fbshipit-source-id: d50561bb37ed50ab97aeaf54d8e3fc6c765bdc7c
goodlux
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Aug 15, 2018
Summary: Fixes: pytorch#9421 I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check. The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...) Do we need a test that it indeed refuses non-contiguous? Pull Request resolved: pytorch#9441 Reviewed By: soumith Differential Revision: D8850719 Pulled By: ezyang fbshipit-source-id: d50561bb37ed50ab97aeaf54d8e3fc6c765bdc7c
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Fixes: #9421
I don't think it is easy to deal with non-contiguous array in cuda topk, so I'm adding a check.
The argument number is a bit confusing when it shows in PyTorch but it is consistent with the other checks. (Not sure whether it would make sense to eliminate argument numbers from the error TH/THC error messages given that they're probably off more than once...)
Do we need a test that it indeed refuses non-contiguous?