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high prioritymodule: bc-breakingRelated to a BC-breaking changeRelated to a BC-breaking changemodule: numpyRelated to numpy support, and also numpy compatibility of our operatorsRelated to numpy support, and also numpy compatibility of our operatorstriagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate moduleThis issue has been looked at a team member, and triaged and prioritized into an appropriate module
Description
Issue description
Number of chunks generated by torch.chunk doesn't match chunks parameter.
Code example
>>> x = torch.arange(0, 11)
>>> x.chunk(5)
(tensor([ 0., 1., 2.]),
tensor([ 3., 4., 5.]),
tensor([ 6., 7., 8.]),
tensor([ 9., 10.]))
>>> len(x.chunk(chunks=5))
4
System Info
PyTorch version: 0.4.0
Is debug build: No
CUDA used to build PyTorch: 8.0.61
OS: Debian GNU/Linux unstable (sid)
GCC version: (Debian 7.3.0-24) 7.3.0
CMake version: version 3.11.2
Python version: 3.6
Is CUDA available: Yes
CUDA runtime version: 9.1.85
GPU models and configuration: GPU 0: GeForce GTX 950M
Nvidia driver version: 390.67
cuDNN version: Probably one of the following:
/usr/local/cuda/lib64/libcudnn.so.7.1.4
/usr/local/cuda/lib64/libcudnn_static.a
Versions of relevant libraries:
[pip3] numpy (1.14.5)
[pip3] torch (0.4.0)
[pip3] torchvision (0.2.1)
[conda] Could not collect
pytorch installed by pip3
l4d2boomer
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high prioritymodule: bc-breakingRelated to a BC-breaking changeRelated to a BC-breaking changemodule: numpyRelated to numpy support, and also numpy compatibility of our operatorsRelated to numpy support, and also numpy compatibility of our operatorstriagedThis issue has been looked at a team member, and triaged and prioritized into an appropriate moduleThis issue has been looked at a team member, and triaged and prioritized into an appropriate module