Replace byte tensor #3813
Replace byte tensor #3813
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@datumbox thanks for pinging.
@fmassa even self-assigned himself to fix #3666 , I let him review this PR as well. @vipyoung this flake8 failure is related : https://app.circleci.com/pipelines/github/pytorch/vision/8023/workflows/9179c017-9365-410e-8959-e77c94a37c26/jobs/571724 |
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The code looks great, thanks a lot @vipyoung !
There are lint failures in https://app.circleci.com/pipelines/github/pytorch/vision/8023/workflows/9179c017-9365-410e-8959-e77c94a37c26/jobs/571724 , can you look into fixing those so that we can merge the PR?
Additionally, one thing we might want to consider as well is that we now get the following warning for the uint8 use-case (which we didn't have before)
/root/project/torchvision/transforms/functional.py:129: UserWarning: The given NumPy array is not writeable, and PyTorch does not support non-writeable tensors. This means you can write to the underlying (supposedly non-writeable) NumPy array using the tensor. You may want to copy the array to protect its data or make it writeable before converting it to a tensor. This type of warning will be suppressed for the rest of this program. (Triggered internally at /opt/conda/conda-bld/pytorch_1620716760038/work/torch/csrc/utils/tensor_numpy.cpp:180.)
np.array(pic, mode_to_nptype.get(pic.mode, np.uint8), copy=False)
see https://app.circleci.com/pipelines/github/pytorch/vision/8023/workflows/5620d2f7-08be-493d-9878-fcb5db93539f/jobs/571690 for one example.
We might want think if we want to perform the copy here (which will be less efficient), or suppress this warning somehow.
Thoughts @vfdev-5 ?
replaced byteTensor with from_numpy fixed lint issues and copy related worning
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Summary: replaced byteTensor with from_numpy fixed lint issues and copy related worning Reviewed By: vincentqb, cpuhrsch Differential Revision: D28677160 fbshipit-source-id: b508d40651e6e7453e8855fed9edc4f313c7580f Co-authored-by: Sofiane Abbar <sofa@fb.com> Co-authored-by: Vasilis Vryniotis <datumbox@users.noreply.github.com>
replaced the deprecated byteTensor call with from_numpy.
Also slightly refactored the code.